chore(deps): bump actions/setup-python from 5 to 6

Bumps [actions/setup-python](https://github.com/actions/setup-python) from 5 to 6.
- [Release notes](https://github.com/actions/setup-python/releases)
- [Commits](https://github.com/actions/setup-python/compare/v5...v6)

---
updated-dependencies:
- dependency-name: actions/setup-python
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>

.github/workflows/bandit.yaml

@@ -21,7 +21,7 @@ jobs:
         uses: actions/checkout@v4
 
       - name: Set up Python
-        uses: actions/setup-python@v5
+        uses: actions/setup-python@v6
         with:
           python-version: '3.12'
       - name: Install dependencies

.github/workflows/pytest.yml

@@ -10,21 +10,21 @@ jobs:
     steps:
       - uses: actions/checkout@v4
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v5
+        uses: actions/setup-python@v6
         with:
           python-version: ${{ matrix.python-version }}
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
+          pip install pytest pytest-cov
           cd application
           if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
-          cd ../tests
-          if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
       - name: Test with pytest and generate coverage report
         run: |
-          python -m pytest --cov=application --cov-report=xml --cov-report=term-missing
+          python -m pytest --cov=application --cov-report=xml
       - name: Upload coverage reports to Codecov
         if: github.event_name == 'pull_request' && matrix.python-version == '3.12'
         uses: codecov/codecov-action@v5
         env:
           CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
+

.vscode/launch.json

@@ -2,11 +2,15 @@
   "version": "0.2.0",
   "configurations": [
     {
-      "name": "Frontend Debug (npm)",
-      "type": "node-terminal",
+      "name": "Docker Debug Frontend",
       "request": "launch",
-      "command": "npm run dev",
-      "cwd": "${workspaceFolder}/frontend"
+      "type": "chrome",
+      "preLaunchTask": "docker-compose: debug:frontend",
+      "url": "http://127.0.0.1:5173",
+      "webRoot": "${workspaceFolder}/frontend",
+      "skipFiles": [
+        "<node_internals>/**"
+      ]
     },
     {
         "name": "Flask Debugger",
@@ -45,27 +49,6 @@
         "--pool=solo"
       ],
       "cwd": "${workspaceFolder}"
-    },
-    {
-      "name": "Dev Containers (Mongo + Redis)",
-      "type": "node-terminal",
-      "request": "launch",
-      "command": "docker compose -f deployment/docker-compose-dev.yaml up --build",
-      "cwd": "${workspaceFolder}"
-    }
-  ],
-  "compounds": [
-    {
-      "name": "DocsGPT: Full Stack",
-      "configurations": [
-        "Frontend Debug (npm)",
-        "Flask Debugger",
-        "Celery Debugger"
-      ],
-      "presentation": {
-        "group": "DocsGPT",
-        "order": 1
-      }
     }
   ]
 }

.vscode/tasks.json

@@ -0,0 +1,21 @@
+{
+  "version": "2.0.0",
+  "tasks": [
+    {
+      "type": "docker-compose",
+      "label": "docker-compose: debug:frontend",
+      "dockerCompose": {
+        "up": {
+          "detached": true,
+          "services": [
+            "frontend"
+          ],
+          "build": true
+        },
+        "files": [
+          "${workspaceFolder}/docker-compose.yaml"
+        ]
+      }
+    }
+  ]
+}

HACKTOBERFEST.md

@@ -1,39 +0,0 @@
-# **🎉 Join the Hacktoberfest with DocsGPT and win a Free T-shirt for a meaningful PR! 🎉**
-
-Welcome, contributors! We're excited to announce that DocsGPT is participating in Hacktoberfest. Get involved by submitting meaningful pull requests.
-
-All Meaningful contributors with accepted PRs that were created for issues with the `hacktoberfest` label (set by our maintainer team: dartpain, siiddhantt, pabik, ManishMadan2882) will receive a cool T-shirt! 🤩.
-<img width="1331" height="678" alt="hacktoberfest-mocks-preview" src="https://github.com/user-attachments/assets/633f6377-38db-48f5-b519-a8b3855a9eb4" />
-
-Fill in [this form](https://forms.gle/Npaba4n9Epfyx56S8
-) after your PR was merged please 
-
-If you are in doubt don't hesitate to ping us on discord, ping me - Alex (dartpain).
-
-## 📜 Here's How to Contribute:
-```text
-🛠️ Code: This is the golden ticket! Make meaningful contributions through PRs.
-
-🧩 API extension: Build an app utilising DocsGPT API. We prefer submissions that showcase original ideas and turn the API into an AI agent.
-They can be a completely separate repos. 
-For example: 
-https://github.com/arc53/tg-bot-docsgpt-extenstion or 
-https://github.com/arc53/DocsGPT-cli
-
-Non-Code Contributions:
-
-📚 Wiki: Improve our documentation, create a guide.
-
-🖥️ Design: Improve the UI/UX or design a new feature.
-```
-
-### 📝 Guidelines for Pull Requests:
-- Familiarize yourself with the current contributions and our [Roadmap](https://github.com/orgs/arc53/projects/2).
-- Before contributing check existing [issues](https://github.com/arc53/DocsGPT/issues) or [create](https://github.com/arc53/DocsGPT/issues/new/choose) an issue and wait to get assigned.
-- Once you are finished with your contribution, please fill in this [form](https://forms.gle/Npaba4n9Epfyx56S8).
-- Refer to the [Documentation](https://docs.docsgpt.cloud/).
-- Feel free to join our [Discord](https://discord.gg/n5BX8dh8rU) server. We're here to help newcomers, so don't hesitate to jump in! Join us [here](https://discord.gg/n5BX8dh8rU).
-  
-Thank you very much for considering contributing to DocsGPT during Hacktoberfest! 🙏 Your contributions (not just simple typos) could earn you a stylish new t-shirt.
-
-We will publish a t-shirt design later into the October.

README.md

@@ -17,7 +17,7 @@
   <a href="https://github.com/arc53/DocsGPT/blob/main/LICENSE">![link to license file](https://img.shields.io/github/license/arc53/docsgpt)</a>
   <a href="https://www.bestpractices.dev/projects/9907"><img src="https://www.bestpractices.dev/projects/9907/badge"></a>
   <a href="https://discord.gg/n5BX8dh8rU">![link to discord](https://img.shields.io/discord/1070046503302877216)</a>
-  <a href="https://x.com/docsgptai">![X (formerly Twitter) URL](https://img.shields.io/twitter/follow/docsgptai)</a>
+  <a href="https://twitter.com/docsgptai">![X (formerly Twitter) URL](https://img.shields.io/twitter/follow/docsgptai)</a>
 
 <a href="https://docs.docsgpt.cloud/quickstart">⚡️ Quickstart</a> • <a href="https://app.docsgpt.cloud/">☁️ Cloud Version</a> • <a href="https://discord.gg/n5BX8dh8rU">💬 Discord</a>
 <br>
@@ -25,17 +25,7 @@
 <br>
 
 </div>
-
 <div align="center">
-  <br>
-🎃 <a href="https://github.com/arc53/DocsGPT/blob/main/HACKTOBERFEST.md"> Hacktoberfest Prizes, Rules & Q&A </a> 🎃
-  <br>
-  <br>
-</div>
-
-
-<div align="center">
-  <br>
 <img src="https://d3dg1063dc54p9.cloudfront.net/videos/demov7.gif" alt="video-example-of-docs-gpt" width="800" height="450">
 </div>
 <h3 align="left">
@@ -65,11 +55,9 @@
 - [x] Agent optimisations (May 2025)
 - [x] Filesystem sources update (July 2025)
 - [x] Json Responses (August 2025)
-- [x] MCP support (August 2025)
-- [x] Google Drive integration (September 2025)
-- [x] Add OAuth 2.0 authentication for MCP (September 2025)
-- [ ] SharePoint integration (October 2025)
-- [ ] Deep Agents (October 2025)
+- [ ] Sharepoint integration (August 2025)
+- [ ] MCP support (August 2025)
+- [ ] Add OAuth 2.0 authentication for tools and sources (August 2025)
 - [ ] Agent scheduling
 
 You can find our full roadmap [here](https://github.com/orgs/arc53/projects/2). Please don't hesitate to contribute or create issues, it helps us improve DocsGPT!
@@ -118,7 +106,7 @@ A more detailed [Quickstart](https://docs.docsgpt.cloud/quickstart) is available
    PowerShell -ExecutionPolicy Bypass -File .\setup.ps1
    ```
 
-Either script will guide you through setting up DocsGPT. Five options available: using the public API, running locally, connecting to a local inference engine, using a cloud API provider, or build the docker image locally. Scripts will automatically configure your `.env` file and handle necessary downloads and installations based on your chosen option.
+Either script will guide you through setting up DocsGPT. Four options available: using the public API, running locally, connecting to a local inference engine, or using a cloud API provider. Scripts will automatically configure your `.env` file and handle necessary downloads and installations based on your chosen option.
 
 **Navigate to http://localhost:5173/**
 

application/agents/base.py

@@ -30,10 +30,6 @@ class BaseAgent(ABC):
         decoded_token: Optional[Dict] = None,
         attachments: Optional[List[Dict]] = None,
         json_schema: Optional[Dict] = None,
-        limited_token_mode: Optional[bool] = False,
-        token_limit: Optional[int] = settings.DEFAULT_AGENT_LIMITS["token_limit"],
-        limited_request_mode: Optional[bool] = False,
-        request_limit: Optional[int] = settings.DEFAULT_AGENT_LIMITS["request_limit"],
     ):
         self.endpoint = endpoint
         self.llm_name = llm_name
@@ -42,7 +38,7 @@ class BaseAgent(ABC):
         self.user_api_key = user_api_key
         self.prompt = prompt
         self.decoded_token = decoded_token or {}
-        self.user: str = self.decoded_token.get("sub")
+        self.user: str = decoded_token.get("sub")
         self.tool_config: Dict = {}
         self.tools: List[Dict] = []
         self.tool_calls: List[Dict] = []
@@ -58,10 +54,6 @@ class BaseAgent(ABC):
         )
         self.attachments = attachments or []
         self.json_schema = json_schema
-        self.limited_token_mode = limited_token_mode
-        self.token_limit = token_limit
-        self.limited_request_mode = limited_request_mode
-        self.request_limit = request_limit
 
     @log_activity()
     def gen(
@@ -148,28 +140,28 @@ class BaseAgent(ABC):
         tool_id, action_name, call_args = parser.parse_args(call)
 
         call_id = getattr(call, "id", None) or str(uuid.uuid4())
-
+        
         # Check if parsing failed
         if tool_id is None or action_name is None:
             error_message = f"Error: Failed to parse LLM tool call. Tool name: {getattr(call, 'name', 'unknown')}"
             logger.error(error_message)
-
+            
             tool_call_data = {
                 "tool_name": "unknown",
                 "call_id": call_id,
-                "action_name": getattr(call, "name", "unknown"),
+                "action_name": getattr(call, 'name', 'unknown'),
                 "arguments": call_args or {},
                 "result": f"Failed to parse tool call. Invalid tool name format: {getattr(call, 'name', 'unknown')}",
             }
             yield {"type": "tool_call", "data": {**tool_call_data, "status": "error"}}
             self.tool_calls.append(tool_call_data)
             return "Failed to parse tool call.", call_id
-
+        
         # Check if tool_id exists in available tools
         if tool_id not in tools_dict:
             error_message = f"Error: Tool ID '{tool_id}' extracted from LLM call not found in available tools_dict. Available IDs: {list(tools_dict.keys())}"
             logger.error(error_message)
-
+            
             # Return error result
             tool_call_data = {
                 "tool_name": "unknown",
@@ -181,7 +173,7 @@ class BaseAgent(ABC):
             yield {"type": "tool_call", "data": {**tool_call_data, "status": "error"}}
             self.tool_calls.append(tool_call_data)
             return f"Tool with ID {tool_id} not found.", call_id
-
+        
         tool_call_data = {
             "tool_name": tools_dict[tool_id]["name"],
             "call_id": call_id,
@@ -221,25 +213,18 @@ class BaseAgent(ABC):
                 ):
                     target_dict[param] = value
         tm = ToolManager(config={})
-
-        # Prepare tool_config and add tool_id for memory tools
-        if tool_data["name"] == "api_tool":
-            tool_config = {
-                "url": tool_data["config"]["actions"][action_name]["url"],
-                "method": tool_data["config"]["actions"][action_name]["method"],
-                "headers": headers,
-                "query_params": query_params,
-            }
-        else:
-            tool_config = tool_data["config"].copy() if tool_data["config"] else {}
-            # Add tool_id from MongoDB _id for tools that need instance isolation (like memory tool)
-            # Use MongoDB _id if available, otherwise fall back to enumerated tool_id
-            tool_config["tool_id"] = str(tool_data.get("_id", tool_id))
-
         tool = tm.load_tool(
             tool_data["name"],
-            tool_config=tool_config,
-            user_id=self.user,  # Pass user ID for MCP tools credential decryption
+            tool_config=(
+                {
+                    "url": tool_data["config"]["actions"][action_name]["url"],
+                    "method": tool_data["config"]["actions"][action_name]["method"],
+                    "headers": headers,
+                    "query_params": query_params,
+                }
+                if tool_data["name"] == "api_tool"
+                else tool_data["config"]
+            ),
         )
         if tool_data["name"] == "api_tool":
             print(
@@ -278,15 +263,7 @@ class BaseAgent(ABC):
         query: str,
         retrieved_data: List[Dict],
     ) -> List[Dict]:
-        docs_with_filenames = []
-        for doc in retrieved_data:
-            filename = doc.get("filename") or doc.get("title") or doc.get("source")
-            if filename:
-                chunk_header = str(filename)
-                docs_with_filenames.append(f"{chunk_header}\n{doc['text']}")
-            else:
-                docs_with_filenames.append(doc["text"])
-        docs_together = "\n\n".join(docs_with_filenames)
+        docs_together = "\n".join([doc["text"] for doc in retrieved_data])
         p_chat_combine = system_prompt.replace("{summaries}", docs_together)
         messages_combine = [{"role": "system", "content": p_chat_combine}]
 

application/agents/react_agent.py

@@ -20,10 +20,9 @@ with open(
     "r",
 ) as f:
     final_prompt_template = f.read()
-
+    
 MAX_ITERATIONS_REASONING = 10
 
-
 class ReActAgent(BaseAgent):
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
@@ -39,69 +38,49 @@ class ReActAgent(BaseAgent):
         collected_content = []
         if isinstance(resp, str):
             collected_content.append(resp)
-        elif (  # OpenAI non-streaming or Anthropic non-streaming (older SDK style)
+        elif ( # OpenAI non-streaming or Anthropic non-streaming (older SDK style)
             hasattr(resp, "message")
             and hasattr(resp.message, "content")
             and resp.message.content is not None
         ):
             collected_content.append(resp.message.content)
-        elif (  # OpenAI non-streaming (Pydantic model), Anthropic new SDK non-streaming
-            hasattr(resp, "choices")
-            and resp.choices
-            and hasattr(resp.choices[0], "message")
-            and hasattr(resp.choices[0].message, "content")
-            and resp.choices[0].message.content is not None
+        elif ( # OpenAI non-streaming (Pydantic model), Anthropic new SDK non-streaming
+            hasattr(resp, "choices") and resp.choices and
+            hasattr(resp.choices[0], "message") and
+            hasattr(resp.choices[0].message, "content") and
+            resp.choices[0].message.content is not None
         ):
-            collected_content.append(resp.choices[0].message.content)  # OpenAI
-        elif (  # Anthropic new SDK non-streaming content block
-            hasattr(resp, "content")
-            and isinstance(resp.content, list)
-            and resp.content
-            and hasattr(resp.content[0], "text")
+            collected_content.append(resp.choices[0].message.content) # OpenAI
+        elif ( # Anthropic new SDK non-streaming content block
+             hasattr(resp, "content") and isinstance(resp.content, list) and resp.content and
+             hasattr(resp.content[0], "text")
         ):
-            collected_content.append(resp.content[0].text)  # Anthropic
+            collected_content.append(resp.content[0].text) # Anthropic
         else:
             # Assume resp is a stream if not a recognized object
-            chunk = None
             try:
-                for (
-                    chunk
-                ) in (
-                    resp
-                ):  # This will fail if resp is not iterable (e.g. a non-streaming response object)
+                for chunk in resp: # This will fail if resp is not iterable (e.g. a non-streaming response object)
                     content_piece = ""
                     # OpenAI-like stream
-                    if (
-                        hasattr(chunk, "choices")
-                        and len(chunk.choices) > 0
-                        and hasattr(chunk.choices[0], "delta")
-                        and hasattr(chunk.choices[0].delta, "content")
-                        and chunk.choices[0].delta.content is not None
-                    ):
+                    if hasattr(chunk, 'choices') and len(chunk.choices) > 0 and \
+                       hasattr(chunk.choices[0], 'delta') and \
+                       hasattr(chunk.choices[0].delta, 'content') and \
+                       chunk.choices[0].delta.content is not None:
                         content_piece = chunk.choices[0].delta.content
                     # Anthropic-like stream (ContentBlockDelta)
-                    elif (
-                        hasattr(chunk, "type")
-                        and chunk.type == "content_block_delta"
-                        and hasattr(chunk, "delta")
-                        and hasattr(chunk.delta, "text")
-                    ):
+                    elif hasattr(chunk, 'type') and chunk.type == 'content_block_delta' and \
+                         hasattr(chunk, 'delta') and hasattr(chunk.delta, 'text'):
                         content_piece = chunk.delta.text
-                    elif isinstance(chunk, str):  # Simplest case: stream of strings
+                    elif isinstance(chunk, str): # Simplest case: stream of strings
                         content_piece = chunk
 
                     if content_piece:
                         collected_content.append(content_piece)
-            except (
-                TypeError
-            ):  # If resp is not iterable (e.g. a final response object that wasn't caught above)
-                logger.debug(
-                    f"Response type {type(resp)} could not be iterated as a stream. It might be a non-streaming object not handled by specific checks."
-                )
+            except TypeError: # If resp is not iterable (e.g. a final response object that wasn't caught above)
+                logger.debug(f"Response type {type(resp)} could not be iterated as a stream. It might be a non-streaming object not handled by specific checks.")
             except Exception as e:
-                logger.error(
-                    f"Error processing potential stream chunk: {e}, chunk was: {getattr(chunk, '__dict__', chunk) if chunk is not None else 'N/A'}"
-                )
+                logger.error(f"Error processing potential stream chunk: {e}, chunk was: {getattr(chunk, '__dict__', chunk)}")
+
 
         return "".join(collected_content)
 
@@ -133,9 +112,8 @@ class ReActAgent(BaseAgent):
                 yield {"thought": line_chunk}
             self.plan = "".join(current_plan_parts)
             if self.plan:
-                self.observations.append(
-                    f"Plan: {self.plan} Iteration: {iterating_reasoning}"
-                )
+                self.observations.append(f"Plan: {self.plan} Iteration: {iterating_reasoning}")
+
 
             max_obs_len = 20000
             obs_str = "\n".join(self.observations)
@@ -147,55 +125,34 @@ class ReActAgent(BaseAgent):
                 + f"\n\nObservations:\n{obs_str}"
                 + f"\n\nIf there is enough data to complete user query '{query}', Respond with 'SATISFIED' only. Otherwise, continue. Dont Menstion 'SATISFIED' in your response if you are not ready. "
             )
-
+            
             messages = self._build_messages(execution_prompt_str, query, retrieved_data)
 
             resp_from_llm_gen = self._llm_gen(messages, log_context)
 
-            initial_llm_thought_content = self._extract_content_from_llm_response(
-                resp_from_llm_gen
-            )
+            initial_llm_thought_content = self._extract_content_from_llm_response(resp_from_llm_gen)
             if initial_llm_thought_content:
-                self.observations.append(
-                    f"Initial thought/response: {initial_llm_thought_content}"
-                )
+                self.observations.append(f"Initial thought/response: {initial_llm_thought_content}")
             else:
-                logger.info(
-                    "ReActAgent: Initial LLM response (before handler) had no textual content (might be only tool calls)."
-                )
-            resp_after_handler = self._llm_handler(
-                resp_from_llm_gen, tools_dict, messages, log_context
-            )
-
-            for (
-                tool_call_info
-            ) in (
-                self.tool_calls
-            ):  # Iterate over self.tool_calls populated by _llm_handler
+                logger.info("ReActAgent: Initial LLM response (before handler) had no textual content (might be only tool calls).")
+            resp_after_handler = self._llm_handler(resp_from_llm_gen, tools_dict, messages, log_context)
+            
+            for tool_call_info in self.tool_calls: # Iterate over self.tool_calls populated by _llm_handler
                 observation_string = (
                     f"Executed Action: Tool '{tool_call_info.get('tool_name', 'N/A')}' "
                     f"with arguments '{tool_call_info.get('arguments', '{}')}'. Result: '{str(tool_call_info.get('result', ''))[:200]}...'"
                 )
                 self.observations.append(observation_string)
 
-            content_after_handler = self._extract_content_from_llm_response(
-                resp_after_handler
-            )
+            content_after_handler = self._extract_content_from_llm_response(resp_after_handler)
             if content_after_handler:
-                self.observations.append(
-                    f"Response after tool execution: {content_after_handler}"
-                )
+                self.observations.append(f"Response after tool execution: {content_after_handler}")
             else:
-                logger.info(
-                    "ReActAgent: LLM response after handler had no textual content."
-                )
+                logger.info("ReActAgent: LLM response after handler had no textual content.")
 
             if log_context:
                 log_context.stacks.append(
-                    {
-                        "component": "agent_tool_calls",
-                        "data": {"tool_calls": self.tool_calls.copy()},
-                    }
+                    {"component": "agent_tool_calls", "data": {"tool_calls": self.tool_calls.copy()}}
                 )
 
             yield {"sources": retrieved_data}
@@ -208,17 +165,13 @@ class ReActAgent(BaseAgent):
                 display_tool_calls.append(cleaned_tc)
             if display_tool_calls:
                 yield {"tool_calls": display_tool_calls}
-
+            
             if "SATISFIED" in content_after_handler:
-                logger.info(
-                    "ReActAgent: LLM satisfied with the plan and data. Stopping reasoning."
-                )
+                logger.info("ReActAgent: LLM satisfied with the plan and data. Stopping reasoning.")
                 break
 
         # 3. Create Final Answer based on all observations
-        final_answer_stream = self._create_final_answer(
-            query, self.observations, log_context
-        )
+        final_answer_stream = self._create_final_answer(query, self.observations, log_context)
         for answer_chunk in final_answer_stream:
             yield {"answer": answer_chunk}
         logger.info("ReActAgent: Finished generating final answer.")
@@ -231,16 +184,12 @@ class ReActAgent(BaseAgent):
             summaries = docs_data if docs_data else "No documents retrieved."
             plan_prompt_filled = plan_prompt_filled.replace("{summaries}", summaries)
         plan_prompt_filled = plan_prompt_filled.replace("{prompt}", self.prompt or "")
-        plan_prompt_filled = plan_prompt_filled.replace(
-            "{observations}", "\n".join(self.observations)
-        )
+        plan_prompt_filled = plan_prompt_filled.replace("{observations}", "\n".join(self.observations))
 
         messages = [{"role": "user", "content": plan_prompt_filled}]
 
         plan_stream_from_llm = self.llm.gen_stream(
-            model=self.gpt_model,
-            messages=messages,
-            tools=getattr(self, "tools", None),  # Use self.tools
+            model=self.gpt_model, messages=messages, tools=getattr(self, 'tools', None) # Use self.tools
         )
         if log_context:
             data = build_stack_data(self.llm)
@@ -257,12 +206,8 @@ class ReActAgent(BaseAgent):
         observation_string = "\n".join(observations)
         max_obs_len = 10000
         if len(observation_string) > max_obs_len:
-            observation_string = (
-                observation_string[:max_obs_len] + "\n...[observations truncated]"
-            )
-            logger.warning(
-                "ReActAgent: Truncated observations for final answer prompt due to length."
-            )
+            observation_string = observation_string[:max_obs_len] + "\n...[observations truncated]"
+            logger.warning("ReActAgent: Truncated observations for final answer prompt due to length.")
 
         final_answer_prompt_filled = final_prompt_template.format(
             query=query, observations=observation_string
@@ -281,4 +226,4 @@ class ReActAgent(BaseAgent):
         for chunk in final_answer_stream_from_llm:
             content_piece = self._extract_content_from_llm_response(chunk)
             if content_piece:
-                yield content_piece
+                yield content_piece

application/agents/tools/mcp_tool.py

@@ -1,861 +0,0 @@
-import asyncio
-import base64
-import json
-import logging
-import time
-from typing import Any, Dict, List, Optional
-from urllib.parse import parse_qs, urlparse
-
-from application.agents.tools.base import Tool
-from application.api.user.tasks import mcp_oauth_status_task, mcp_oauth_task
-from application.cache import get_redis_instance
-
-from application.core.mongo_db import MongoDB
-
-from application.core.settings import settings
-
-from application.security.encryption import decrypt_credentials
-from fastmcp import Client
-from fastmcp.client.auth import BearerAuth
-from fastmcp.client.transports import (
-    SSETransport,
-    StdioTransport,
-    StreamableHttpTransport,
-)
-from mcp.client.auth import OAuthClientProvider, TokenStorage
-from mcp.shared.auth import OAuthClientInformationFull, OAuthClientMetadata, OAuthToken
-
-from pydantic import AnyHttpUrl, ValidationError
-from redis import Redis
-
-mongo = MongoDB.get_client()
-db = mongo[settings.MONGO_DB_NAME]
-
-_mcp_clients_cache = {}
-
-
-class MCPTool(Tool):
-    """
-    MCP Tool
-    Connect to remote Model Context Protocol (MCP) servers to access dynamic tools and resources.
-    """
-
-    def __init__(self, config: Dict[str, Any], user_id: Optional[str] = None):
-        """
-        Initialize the MCP Tool with configuration.
-
-        Args:
-            config: Dictionary containing MCP server configuration:
-                - server_url: URL of the remote MCP server
-                - transport_type: Transport type (auto, sse, http, stdio)
-                - auth_type: Type of authentication (bearer, oauth, api_key, basic, none)
-                - encrypted_credentials: Encrypted credentials (if available)
-                - timeout: Request timeout in seconds (default: 30)
-                - headers: Custom headers for requests
-                - command: Command for STDIO transport
-                - args: Arguments for STDIO transport
-                - oauth_scopes: OAuth scopes for oauth auth type
-                - oauth_client_name: OAuth client name for oauth auth type
-            user_id: User ID for decrypting credentials (required if encrypted_credentials exist)
-        """
-        self.config = config
-        self.user_id = user_id
-        self.server_url = config.get("server_url", "")
-        self.transport_type = config.get("transport_type", "auto")
-        self.auth_type = config.get("auth_type", "none")
-        self.timeout = config.get("timeout", 30)
-        self.custom_headers = config.get("headers", {})
-
-        self.auth_credentials = {}
-        if config.get("encrypted_credentials") and user_id:
-            self.auth_credentials = decrypt_credentials(
-                config["encrypted_credentials"], user_id
-            )
-        else:
-            self.auth_credentials = config.get("auth_credentials", {})
-        self.oauth_scopes = config.get("oauth_scopes", [])
-        self.oauth_task_id = config.get("oauth_task_id", None)
-        self.oauth_client_name = config.get("oauth_client_name", "DocsGPT-MCP")
-        self.redirect_uri = f"{settings.API_URL}/api/mcp_server/callback"
-
-        self.available_tools = []
-        self._cache_key = self._generate_cache_key()
-        self._client = None
-
-        # Only validate and setup if server_url is provided and not OAuth
-
-        if self.server_url and self.auth_type != "oauth":
-            self._setup_client()
-
-    def _generate_cache_key(self) -> str:
-        """Generate a unique cache key for this MCP server configuration."""
-        auth_key = ""
-        if self.auth_type == "oauth":
-            scopes_str = ",".join(self.oauth_scopes) if self.oauth_scopes else "none"
-            auth_key = f"oauth:{self.oauth_client_name}:{scopes_str}"
-        elif self.auth_type in ["bearer"]:
-            token = self.auth_credentials.get(
-                "bearer_token", ""
-            ) or self.auth_credentials.get("access_token", "")
-            auth_key = f"bearer:{token[:10]}..." if token else "bearer:none"
-        elif self.auth_type == "api_key":
-            api_key = self.auth_credentials.get("api_key", "")
-            auth_key = f"apikey:{api_key[:10]}..." if api_key else "apikey:none"
-        elif self.auth_type == "basic":
-            username = self.auth_credentials.get("username", "")
-            auth_key = f"basic:{username}"
-        else:
-            auth_key = "none"
-        return f"{self.server_url}#{self.transport_type}#{auth_key}"
-
-    def _setup_client(self):
-        """Setup FastMCP client with proper transport and authentication."""
-        global _mcp_clients_cache
-        if self._cache_key in _mcp_clients_cache:
-            cached_data = _mcp_clients_cache[self._cache_key]
-            if time.time() - cached_data["created_at"] < 1800:
-                self._client = cached_data["client"]
-                return
-            else:
-                del _mcp_clients_cache[self._cache_key]
-        transport = self._create_transport()
-        auth = None
-
-        if self.auth_type == "oauth":
-            redis_client = get_redis_instance()
-            auth = DocsGPTOAuth(
-                mcp_url=self.server_url,
-                scopes=self.oauth_scopes,
-                redis_client=redis_client,
-                redirect_uri=self.redirect_uri,
-                task_id=self.oauth_task_id,
-                db=db,
-                user_id=self.user_id,
-            )
-        elif self.auth_type == "bearer":
-            token = self.auth_credentials.get(
-                "bearer_token", ""
-            ) or self.auth_credentials.get("access_token", "")
-            if token:
-                auth = BearerAuth(token)
-        self._client = Client(transport, auth=auth)
-        _mcp_clients_cache[self._cache_key] = {
-            "client": self._client,
-            "created_at": time.time(),
-        }
-
-    def _create_transport(self):
-        """Create appropriate transport based on configuration."""
-        headers = {"Content-Type": "application/json", "User-Agent": "DocsGPT-MCP/1.0"}
-        headers.update(self.custom_headers)
-
-        if self.auth_type == "api_key":
-            api_key = self.auth_credentials.get("api_key", "")
-            header_name = self.auth_credentials.get("api_key_header", "X-API-Key")
-            if api_key:
-                headers[header_name] = api_key
-        elif self.auth_type == "basic":
-            username = self.auth_credentials.get("username", "")
-            password = self.auth_credentials.get("password", "")
-            if username and password:
-                credentials = base64.b64encode(
-                    f"{username}:{password}".encode()
-                ).decode()
-                headers["Authorization"] = f"Basic {credentials}"
-        if self.transport_type == "auto":
-            if "sse" in self.server_url.lower() or self.server_url.endswith("/sse"):
-                transport_type = "sse"
-            else:
-                transport_type = "http"
-        else:
-            transport_type = self.transport_type
-        if transport_type == "sse":
-            headers.update({"Accept": "text/event-stream", "Cache-Control": "no-cache"})
-            return SSETransport(url=self.server_url, headers=headers)
-        elif transport_type == "http":
-            return StreamableHttpTransport(url=self.server_url, headers=headers)
-        elif transport_type == "stdio":
-            command = self.config.get("command", "python")
-            args = self.config.get("args", [])
-            env = self.auth_credentials if self.auth_credentials else None
-            return StdioTransport(command=command, args=args, env=env)
-        else:
-            return StreamableHttpTransport(url=self.server_url, headers=headers)
-
-    def _format_tools(self, tools_response) -> List[Dict]:
-        """Format tools response to match expected format."""
-        if hasattr(tools_response, "tools"):
-            tools = tools_response.tools
-        elif isinstance(tools_response, list):
-            tools = tools_response
-        else:
-            tools = []
-        tools_dict = []
-        for tool in tools:
-            if hasattr(tool, "name"):
-                tool_dict = {
-                    "name": tool.name,
-                    "description": tool.description,
-                }
-                if hasattr(tool, "inputSchema"):
-                    tool_dict["inputSchema"] = tool.inputSchema
-                tools_dict.append(tool_dict)
-            elif isinstance(tool, dict):
-                tools_dict.append(tool)
-            else:
-                if hasattr(tool, "model_dump"):
-                    tools_dict.append(tool.model_dump())
-                else:
-                    tools_dict.append({"name": str(tool), "description": ""})
-        return tools_dict
-
-    async def _execute_with_client(self, operation: str, *args, **kwargs):
-        """Execute operation with FastMCP client."""
-        if not self._client:
-            raise Exception("FastMCP client not initialized")
-        async with self._client:
-            if operation == "ping":
-                return await self._client.ping()
-            elif operation == "list_tools":
-                tools_response = await self._client.list_tools()
-                self.available_tools = self._format_tools(tools_response)
-                return self.available_tools
-            elif operation == "call_tool":
-                tool_name = args[0]
-                tool_args = kwargs
-                return await self._client.call_tool(tool_name, tool_args)
-            elif operation == "list_resources":
-                return await self._client.list_resources()
-            elif operation == "list_prompts":
-                return await self._client.list_prompts()
-            else:
-                raise Exception(f"Unknown operation: {operation}")
-
-    def _run_async_operation(self, operation: str, *args, **kwargs):
-        """Run async operation in sync context."""
-        try:
-            try:
-                loop = asyncio.get_running_loop()
-                import concurrent.futures
-
-                def run_in_thread():
-                    new_loop = asyncio.new_event_loop()
-                    asyncio.set_event_loop(new_loop)
-                    try:
-                        return new_loop.run_until_complete(
-                            self._execute_with_client(operation, *args, **kwargs)
-                        )
-                    finally:
-                        new_loop.close()
-
-                with concurrent.futures.ThreadPoolExecutor() as executor:
-                    future = executor.submit(run_in_thread)
-                    return future.result(timeout=self.timeout)
-            except RuntimeError:
-                loop = asyncio.new_event_loop()
-                asyncio.set_event_loop(loop)
-                try:
-                    return loop.run_until_complete(
-                        self._execute_with_client(operation, *args, **kwargs)
-                    )
-                finally:
-                    loop.close()
-        except Exception as e:
-            print(f"Error occurred while running async operation: {e}")
-            raise
-
-    def discover_tools(self) -> List[Dict]:
-        """
-        Discover available tools from the MCP server using FastMCP.
-
-        Returns:
-            List of tool definitions from the server
-        """
-        if not self.server_url:
-            return []
-        if not self._client:
-            self._setup_client()
-        try:
-            tools = self._run_async_operation("list_tools")
-            self.available_tools = tools
-            return self.available_tools
-        except Exception as e:
-            raise Exception(f"Failed to discover tools from MCP server: {str(e)}")
-
-    def execute_action(self, action_name: str, **kwargs) -> Any:
-        """
-        Execute an action on the remote MCP server using FastMCP.
-
-        Args:
-            action_name: Name of the action to execute
-            **kwargs: Parameters for the action
-
-        Returns:
-            Result from the MCP server
-        """
-        if not self.server_url:
-            raise Exception("No MCP server configured")
-        if not self._client:
-            self._setup_client()
-        cleaned_kwargs = {}
-        for key, value in kwargs.items():
-            if value == "" or value is None:
-                continue
-            cleaned_kwargs[key] = value
-        try:
-            result = self._run_async_operation(
-                "call_tool", action_name, **cleaned_kwargs
-            )
-            return self._format_result(result)
-        except Exception as e:
-            raise Exception(f"Failed to execute action '{action_name}': {str(e)}")
-
-    def _format_result(self, result) -> Dict:
-        """Format FastMCP result to match expected format."""
-        if hasattr(result, "content"):
-            content_list = []
-            for content_item in result.content:
-                if hasattr(content_item, "text"):
-                    content_list.append({"type": "text", "text": content_item.text})
-                elif hasattr(content_item, "data"):
-                    content_list.append({"type": "data", "data": content_item.data})
-                else:
-                    content_list.append(
-                        {"type": "unknown", "content": str(content_item)}
-                    )
-            return {
-                "content": content_list,
-                "isError": getattr(result, "isError", False),
-            }
-        else:
-            return result
-
-    def test_connection(self) -> Dict:
-        """
-        Test the connection to the MCP server and validate functionality.
-
-        Returns:
-            Dictionary with connection test results including tool count
-        """
-        if not self.server_url:
-            return {
-                "success": False,
-                "message": "No MCP server URL configured",
-                "tools_count": 0,
-                "transport_type": self.transport_type,
-                "auth_type": self.auth_type,
-                "error_type": "ConfigurationError",
-            }
-        if not self._client:
-            self._setup_client()
-        try:
-            if self.auth_type == "oauth":
-                return self._test_oauth_connection()
-            else:
-                return self._test_regular_connection()
-        except Exception as e:
-            return {
-                "success": False,
-                "message": f"Connection failed: {str(e)}",
-                "tools_count": 0,
-                "transport_type": self.transport_type,
-                "auth_type": self.auth_type,
-                "error_type": type(e).__name__,
-            }
-
-    def _test_regular_connection(self) -> Dict:
-        """Test connection for non-OAuth auth types."""
-        try:
-            self._run_async_operation("ping")
-            ping_success = True
-        except Exception:
-            ping_success = False
-        tools = self.discover_tools()
-
-        message = f"Successfully connected to MCP server. Found {len(tools)} tools."
-        if not ping_success:
-            message += " (Ping not supported, but tool discovery worked)"
-        return {
-            "success": True,
-            "message": message,
-            "tools_count": len(tools),
-            "transport_type": self.transport_type,
-            "auth_type": self.auth_type,
-            "ping_supported": ping_success,
-            "tools": [tool.get("name", "unknown") for tool in tools],
-        }
-
-    def _test_oauth_connection(self) -> Dict:
-        """Test connection for OAuth auth type with proper async handling."""
-        try:
-            task = mcp_oauth_task.delay(config=self.config, user=self.user_id)
-            if not task:
-                raise Exception("Failed to start OAuth authentication")
-            return {
-                "success": True,
-                "requires_oauth": True,
-                "task_id": task.id,
-                "status": "pending",
-                "message": "OAuth flow started",
-            }
-        except Exception as e:
-            return {
-                "success": False,
-                "message": f"OAuth connection failed: {str(e)}",
-                "tools_count": 0,
-                "transport_type": self.transport_type,
-                "auth_type": self.auth_type,
-                "error_type": type(e).__name__,
-            }
-
-    def get_actions_metadata(self) -> List[Dict]:
-        """
-        Get metadata for all available actions.
-
-        Returns:
-            List of action metadata dictionaries
-        """
-        actions = []
-        for tool in self.available_tools:
-            input_schema = (
-                tool.get("inputSchema")
-                or tool.get("input_schema")
-                or tool.get("schema")
-                or tool.get("parameters")
-            )
-
-            parameters_schema = {
-                "type": "object",
-                "properties": {},
-                "required": [],
-            }
-
-            if input_schema:
-                if isinstance(input_schema, dict):
-                    if "properties" in input_schema:
-                        parameters_schema = {
-                            "type": input_schema.get("type", "object"),
-                            "properties": input_schema.get("properties", {}),
-                            "required": input_schema.get("required", []),
-                        }
-
-                        for key in ["additionalProperties", "description"]:
-                            if key in input_schema:
-                                parameters_schema[key] = input_schema[key]
-                    else:
-                        parameters_schema["properties"] = input_schema
-            action = {
-                "name": tool.get("name", ""),
-                "description": tool.get("description", ""),
-                "parameters": parameters_schema,
-            }
-            actions.append(action)
-        return actions
-
-    def get_config_requirements(self) -> Dict:
-        """Get configuration requirements for the MCP tool."""
-        return {
-            "server_url": {
-                "type": "string",
-                "description": "URL of the remote MCP server (e.g., https://api.example.com/mcp or https://docs.mcp.cloudflare.com/sse)",
-                "required": True,
-            },
-            "transport_type": {
-                "type": "string",
-                "description": "Transport type for connection",
-                "enum": ["auto", "sse", "http", "stdio"],
-                "default": "auto",
-                "required": False,
-                "help": {
-                    "auto": "Automatically detect best transport",
-                    "sse": "Server-Sent Events (for real-time streaming)",
-                    "http": "HTTP streaming (recommended for production)",
-                    "stdio": "Standard I/O (for local servers)",
-                },
-            },
-            "auth_type": {
-                "type": "string",
-                "description": "Authentication type",
-                "enum": ["none", "bearer", "oauth", "api_key", "basic"],
-                "default": "none",
-                "required": True,
-                "help": {
-                    "none": "No authentication",
-                    "bearer": "Bearer token authentication",
-                    "oauth": "OAuth 2.1 authentication (with frontend integration)",
-                    "api_key": "API key authentication",
-                    "basic": "Basic authentication",
-                },
-            },
-            "auth_credentials": {
-                "type": "object",
-                "description": "Authentication credentials (varies by auth_type)",
-                "required": False,
-                "properties": {
-                    "bearer_token": {
-                        "type": "string",
-                        "description": "Bearer token for bearer auth",
-                    },
-                    "access_token": {
-                        "type": "string",
-                        "description": "Access token for OAuth (if pre-obtained)",
-                    },
-                    "api_key": {
-                        "type": "string",
-                        "description": "API key for api_key auth",
-                    },
-                    "api_key_header": {
-                        "type": "string",
-                        "description": "Header name for API key (default: X-API-Key)",
-                    },
-                    "username": {
-                        "type": "string",
-                        "description": "Username for basic auth",
-                    },
-                    "password": {
-                        "type": "string",
-                        "description": "Password for basic auth",
-                    },
-                },
-            },
-            "oauth_scopes": {
-                "type": "array",
-                "description": "OAuth scopes to request (for oauth auth_type)",
-                "items": {"type": "string"},
-                "required": False,
-                "default": [],
-            },
-            "oauth_client_name": {
-                "type": "string",
-                "description": "Client name for OAuth registration (for oauth auth_type)",
-                "default": "DocsGPT-MCP",
-                "required": False,
-            },
-            "headers": {
-                "type": "object",
-                "description": "Custom headers to send with requests",
-                "required": False,
-            },
-            "timeout": {
-                "type": "integer",
-                "description": "Request timeout in seconds",
-                "default": 30,
-                "minimum": 1,
-                "maximum": 300,
-                "required": False,
-            },
-            "command": {
-                "type": "string",
-                "description": "Command to run for STDIO transport (e.g., 'python')",
-                "required": False,
-            },
-            "args": {
-                "type": "array",
-                "description": "Arguments for STDIO command",
-                "items": {"type": "string"},
-                "required": False,
-            },
-        }
-
-
-class DocsGPTOAuth(OAuthClientProvider):
-    """
-    Custom OAuth handler for DocsGPT that uses frontend redirect instead of browser.
-    """
-
-    def __init__(
-        self,
-        mcp_url: str,
-        redirect_uri: str,
-        redis_client: Redis | None = None,
-        redis_prefix: str = "mcp_oauth:",
-        task_id: str = None,
-        scopes: str | list[str] | None = None,
-        client_name: str = "DocsGPT-MCP",
-        user_id=None,
-        db=None,
-        additional_client_metadata: dict[str, Any] | None = None,
-    ):
-        """
-        Initialize custom OAuth client provider for DocsGPT.
-
-        Args:
-            mcp_url: Full URL to the MCP endpoint
-            redirect_uri: Custom redirect URI for DocsGPT frontend
-            redis_client: Redis client for storing auth state
-            redis_prefix: Prefix for Redis keys
-            task_id: Task ID for tracking auth status
-            scopes: OAuth scopes to request
-            client_name: Name for this client during registration
-            user_id: User ID for token storage
-            db: Database instance for token storage
-            additional_client_metadata: Extra fields for OAuthClientMetadata
-        """
-
-        self.redirect_uri = redirect_uri
-        self.redis_client = redis_client
-        self.redis_prefix = redis_prefix
-        self.task_id = task_id
-        self.user_id = user_id
-        self.db = db
-
-        parsed_url = urlparse(mcp_url)
-        self.server_base_url = f"{parsed_url.scheme}://{parsed_url.netloc}"
-
-        if isinstance(scopes, list):
-            scopes = " ".join(scopes)
-        client_metadata = OAuthClientMetadata(
-            client_name=client_name,
-            redirect_uris=[AnyHttpUrl(redirect_uri)],
-            grant_types=["authorization_code", "refresh_token"],
-            response_types=["code"],
-            scope=scopes,
-            **(additional_client_metadata or {}),
-        )
-
-        storage = DBTokenStorage(
-            server_url=self.server_base_url, user_id=self.user_id, db_client=self.db
-        )
-
-        super().__init__(
-            server_url=self.server_base_url,
-            client_metadata=client_metadata,
-            storage=storage,
-            redirect_handler=self.redirect_handler,
-            callback_handler=self.callback_handler,
-        )
-
-        self.auth_url = None
-        self.extracted_state = None
-
-    def _process_auth_url(self, authorization_url: str) -> tuple[str, str]:
-        """Process authorization URL to extract state"""
-        try:
-            parsed_url = urlparse(authorization_url)
-            query_params = parse_qs(parsed_url.query)
-
-            state_params = query_params.get("state", [])
-            if state_params:
-                state = state_params[0]
-            else:
-                raise ValueError("No state in auth URL")
-            return authorization_url, state
-        except Exception as e:
-            raise Exception(f"Failed to process auth URL: {e}")
-
-    async def redirect_handler(self, authorization_url: str) -> None:
-        """Store auth URL and state in Redis for frontend to use."""
-        auth_url, state = self._process_auth_url(authorization_url)
-        logging.info(
-            "[DocsGPTOAuth] Processed auth_url: %s, state: %s", auth_url, state
-        )
-        self.auth_url = auth_url
-        self.extracted_state = state
-
-        if self.redis_client and self.extracted_state:
-            key = f"{self.redis_prefix}auth_url:{self.extracted_state}"
-            self.redis_client.setex(key, 600, auth_url)
-            logging.info("[DocsGPTOAuth] Stored auth_url in Redis: %s", key)
-
-            if self.task_id:
-                status_key = f"mcp_oauth_status:{self.task_id}"
-                status_data = {
-                    "status": "requires_redirect",
-                    "message": "OAuth authorization required",
-                    "authorization_url": self.auth_url,
-                    "state": self.extracted_state,
-                    "requires_oauth": True,
-                    "task_id": self.task_id,
-                }
-                self.redis_client.setex(status_key, 600, json.dumps(status_data))
-
-    async def callback_handler(self) -> tuple[str, str | None]:
-        """Wait for auth code from Redis using the state value."""
-        if not self.redis_client or not self.extracted_state:
-            raise Exception("Redis client or state not configured for OAuth")
-        poll_interval = 1
-        max_wait_time = 300
-        code_key = f"{self.redis_prefix}code:{self.extracted_state}"
-
-        if self.task_id:
-            status_key = f"mcp_oauth_status:{self.task_id}"
-            status_data = {
-                "status": "awaiting_callback",
-                "message": "Waiting for OAuth callback...",
-                "authorization_url": self.auth_url,
-                "state": self.extracted_state,
-                "requires_oauth": True,
-                "task_id": self.task_id,
-            }
-            self.redis_client.setex(status_key, 600, json.dumps(status_data))
-        start_time = time.time()
-        while time.time() - start_time < max_wait_time:
-            code_data = self.redis_client.get(code_key)
-            if code_data:
-                code = code_data.decode()
-                returned_state = self.extracted_state
-
-                self.redis_client.delete(code_key)
-                self.redis_client.delete(
-                    f"{self.redis_prefix}auth_url:{self.extracted_state}"
-                )
-                self.redis_client.delete(
-                    f"{self.redis_prefix}state:{self.extracted_state}"
-                )
-
-                if self.task_id:
-                    status_data = {
-                        "status": "callback_received",
-                        "message": "OAuth callback received, completing authentication...",
-                        "task_id": self.task_id,
-                    }
-                    self.redis_client.setex(status_key, 600, json.dumps(status_data))
-                return code, returned_state
-            error_key = f"{self.redis_prefix}error:{self.extracted_state}"
-            error_data = self.redis_client.get(error_key)
-            if error_data:
-                error_msg = error_data.decode()
-                self.redis_client.delete(error_key)
-                self.redis_client.delete(
-                    f"{self.redis_prefix}auth_url:{self.extracted_state}"
-                )
-                self.redis_client.delete(
-                    f"{self.redis_prefix}state:{self.extracted_state}"
-                )
-                raise Exception(f"OAuth error: {error_msg}")
-            await asyncio.sleep(poll_interval)
-        self.redis_client.delete(f"{self.redis_prefix}auth_url:{self.extracted_state}")
-        self.redis_client.delete(f"{self.redis_prefix}state:{self.extracted_state}")
-        raise Exception("OAuth callback timeout: no code received within 5 minutes")
-
-
-class DBTokenStorage(TokenStorage):
-    def __init__(self, server_url: str, user_id: str, db_client):
-        self.server_url = server_url
-        self.user_id = user_id
-        self.db_client = db_client
-        self.collection = db_client["connector_sessions"]
-
-    @staticmethod
-    def get_base_url(url: str) -> str:
-        parsed = urlparse(url)
-        return f"{parsed.scheme}://{parsed.netloc}"
-
-    def get_db_key(self) -> dict:
-        return {
-            "server_url": self.get_base_url(self.server_url),
-            "user_id": self.user_id,
-        }
-
-    async def get_tokens(self) -> OAuthToken | None:
-        doc = await asyncio.to_thread(self.collection.find_one, self.get_db_key())
-        if not doc or "tokens" not in doc:
-            return None
-        try:
-            tokens = OAuthToken.model_validate(doc["tokens"])
-            return tokens
-        except ValidationError as e:
-            logging.error(f"Could not load tokens: {e}")
-            return None
-
-    async def set_tokens(self, tokens: OAuthToken) -> None:
-        await asyncio.to_thread(
-            self.collection.update_one,
-            self.get_db_key(),
-            {"$set": {"tokens": tokens.model_dump()}},
-            True,
-        )
-        logging.info(f"Saved tokens for {self.get_base_url(self.server_url)}")
-
-    async def get_client_info(self) -> OAuthClientInformationFull | None:
-        doc = await asyncio.to_thread(self.collection.find_one, self.get_db_key())
-        if not doc or "client_info" not in doc:
-            return None
-        try:
-            client_info = OAuthClientInformationFull.model_validate(doc["client_info"])
-            tokens = await self.get_tokens()
-            if tokens is None:
-                logging.debug(
-                    "No tokens found, clearing client info to force fresh registration."
-                )
-                await asyncio.to_thread(
-                    self.collection.update_one,
-                    self.get_db_key(),
-                    {"$unset": {"client_info": ""}},
-                )
-                return None
-            return client_info
-        except ValidationError as e:
-            logging.error(f"Could not load client info: {e}")
-            return None
-
-    def _serialize_client_info(self, info: dict) -> dict:
-        if "redirect_uris" in info and isinstance(info["redirect_uris"], list):
-            info["redirect_uris"] = [str(u) for u in info["redirect_uris"]]
-        return info
-
-    async def set_client_info(self, client_info: OAuthClientInformationFull) -> None:
-        serialized_info = self._serialize_client_info(client_info.model_dump())
-        await asyncio.to_thread(
-            self.collection.update_one,
-            self.get_db_key(),
-            {"$set": {"client_info": serialized_info}},
-            True,
-        )
-        logging.info(f"Saved client info for {self.get_base_url(self.server_url)}")
-
-    async def clear(self) -> None:
-        await asyncio.to_thread(self.collection.delete_one, self.get_db_key())
-        logging.info(f"Cleared OAuth cache for {self.get_base_url(self.server_url)}")
-
-    @classmethod
-    async def clear_all(cls, db_client) -> None:
-        collection = db_client["connector_sessions"]
-        await asyncio.to_thread(collection.delete_many, {})
-        logging.info("Cleared all OAuth client cache data.")
-
-
-class MCPOAuthManager:
-    """Manager for handling MCP OAuth callbacks."""
-
-    def __init__(self, redis_client: Redis | None, redis_prefix: str = "mcp_oauth:"):
-        self.redis_client = redis_client
-        self.redis_prefix = redis_prefix
-
-    def handle_oauth_callback(
-        self, state: str, code: str, error: Optional[str] = None
-    ) -> bool:
-        """
-        Handle OAuth callback from provider.
-
-        Args:
-            state: The state parameter from OAuth callback
-            code: The authorization code from OAuth callback
-            error: Error message if OAuth failed
-
-        Returns:
-            True if successful, False otherwise
-        """
-        try:
-            if not self.redis_client or not state:
-                raise Exception("Redis client or state not provided")
-            if error:
-                error_key = f"{self.redis_prefix}error:{state}"
-                self.redis_client.setex(error_key, 300, error)
-                raise Exception(f"OAuth error received: {error}")
-            code_key = f"{self.redis_prefix}code:{state}"
-            self.redis_client.setex(code_key, 300, code)
-
-            state_key = f"{self.redis_prefix}state:{state}"
-            self.redis_client.setex(state_key, 300, "completed")
-
-            return True
-        except Exception as e:
-            logging.error(f"Error handling OAuth callback: {e}")
-            return False
-
-    def get_oauth_status(self, task_id: str) -> Dict[str, Any]:
-        """Get current status of OAuth flow using provided task_id."""
-        if not task_id:
-            return {"status": "not_started", "message": "OAuth flow not started"}
-        return mcp_oauth_status_task(task_id)

application/agents/tools/memory.py

@@ -1,546 +0,0 @@
-from datetime import datetime
-from pathlib import Path
-from typing import Any, Dict, List, Optional
-import re
-import uuid
-
-from .base import Tool
-from application.core.mongo_db import MongoDB
-from application.core.settings import settings
-
-
-class MemoryTool(Tool):
-    """Memory
-
-    Stores and retrieves information across conversations through a memory file directory.
-    """
-
-    def __init__(self, tool_config: Optional[Dict[str, Any]] = None, user_id: Optional[str] = None) -> None:
-        """Initialize the tool.
-
-        Args:
-            tool_config: Optional tool configuration. Should include:
-                - tool_id: Unique identifier for this memory tool instance (from user_tools._id)
-                           This ensures each user's tool configuration has isolated memories
-            user_id: The authenticated user's id (should come from decoded_token["sub"]).
-        """
-        self.user_id: Optional[str] = user_id
-
-        # Get tool_id from configuration (passed from user_tools._id in production)
-        # In production, tool_id is the MongoDB ObjectId string from user_tools collection
-        if tool_config and "tool_id" in tool_config:
-            self.tool_id = tool_config["tool_id"]
-        elif user_id:
-            # Fallback for backward compatibility or testing
-            self.tool_id = f"default_{user_id}"
-        else:
-            # Last resort fallback (shouldn't happen in normal use)
-            self.tool_id = str(uuid.uuid4())
-
-        db = MongoDB.get_client()[settings.MONGO_DB_NAME]
-        self.collection = db["memories"]
-
-    # -----------------------------
-    # Action implementations
-    # -----------------------------
-    def execute_action(self, action_name: str, **kwargs: Any) -> str:
-        """Execute an action by name.
-
-        Args:
-            action_name: One of view, create, str_replace, insert, delete, rename.
-            **kwargs: Parameters for the action.
-
-        Returns:
-            A human-readable string result.
-        """
-        if not self.user_id:
-            return "Error: MemoryTool requires a valid user_id."
-
-        if action_name == "view":
-            return self._view(
-                kwargs.get("path", "/"),
-                kwargs.get("view_range")
-            )
-
-        if action_name == "create":
-            return self._create(
-                kwargs.get("path", ""),
-                kwargs.get("file_text", "")
-            )
-
-        if action_name == "str_replace":
-            return self._str_replace(
-                kwargs.get("path", ""),
-                kwargs.get("old_str", ""),
-                kwargs.get("new_str", "")
-            )
-
-        if action_name == "insert":
-            return self._insert(
-                kwargs.get("path", ""),
-                kwargs.get("insert_line", 1),
-                kwargs.get("insert_text", "")
-            )
-
-        if action_name == "delete":
-            return self._delete(kwargs.get("path", ""))
-
-        if action_name == "rename":
-            return self._rename(
-                kwargs.get("old_path", ""),
-                kwargs.get("new_path", "")
-            )
-
-        return f"Unknown action: {action_name}"
-
-    def get_actions_metadata(self) -> List[Dict[str, Any]]:
-        """Return JSON metadata describing supported actions for tool schemas."""
-        return [
-            {
-                "name": "view",
-                "description": "Shows directory contents or file contents with optional line ranges.",
-                "parameters": {
-                    "type": "object",
-                    "properties": {
-                        "path": {
-                            "type": "string",
-                            "description": "Path to file or directory (e.g., /notes.txt or /project/ or /)."
-                        },
-                        "view_range": {
-                            "type": "array",
-                            "items": {"type": "integer"},
-                            "description": "Optional [start_line, end_line] to view specific lines (1-indexed)."
-                        }
-                    },
-                    "required": ["path"]
-                },
-            },
-            {
-                "name": "create",
-                "description": "Create or overwrite a file.",
-                "parameters": {
-                    "type": "object",
-                    "properties": {
-                        "path": {
-                            "type": "string",
-                            "description": "File path to create (e.g., /notes.txt or /project/task.txt)."
-                        },
-                        "file_text": {
-                            "type": "string",
-                            "description": "Content to write to the file."
-                        }
-                    },
-                    "required": ["path", "file_text"]
-                },
-            },
-            {
-                "name": "str_replace",
-                "description": "Replace text in a file.",
-                "parameters": {
-                    "type": "object",
-                    "properties": {
-                        "path": {
-                            "type": "string",
-                            "description": "File path (e.g., /notes.txt)."
-                        },
-                        "old_str": {
-                            "type": "string",
-                            "description": "String to find."
-                        },
-                        "new_str": {
-                            "type": "string",
-                            "description": "String to replace with."
-                        }
-                    },
-                    "required": ["path", "old_str", "new_str"]
-                },
-            },
-            {
-                "name": "insert",
-                "description": "Insert text at a specific line in a file.",
-                "parameters": {
-                    "type": "object",
-                    "properties": {
-                        "path": {
-                            "type": "string",
-                            "description": "File path (e.g., /notes.txt)."
-                        },
-                        "insert_line": {
-                            "type": "integer",
-                            "description": "Line number to insert at (1-indexed)."
-                        },
-                        "insert_text": {
-                            "type": "string",
-                            "description": "Text to insert."
-                        }
-                    },
-                    "required": ["path", "insert_line", "insert_text"]
-                },
-            },
-            {
-                "name": "delete",
-                "description": "Delete a file or directory.",
-                "parameters": {
-                    "type": "object",
-                    "properties": {
-                        "path": {
-                            "type": "string",
-                            "description": "Path to delete (e.g., /notes.txt or /project/)."
-                        }
-                    },
-                    "required": ["path"]
-                },
-            },
-            {
-                "name": "rename",
-                "description": "Rename or move a file/directory.",
-                "parameters": {
-                    "type": "object",
-                    "properties": {
-                        "old_path": {
-                            "type": "string",
-                            "description": "Current path (e.g., /old.txt)."
-                        },
-                        "new_path": {
-                            "type": "string",
-                            "description": "New path (e.g., /new.txt)."
-                        }
-                    },
-                    "required": ["old_path", "new_path"]
-                },
-            },
-        ]
-
-    def get_config_requirements(self) -> Dict[str, Any]:
-        """Return configuration requirements."""
-        return {}
-
-    # -----------------------------
-    # Path validation
-    # -----------------------------
-    def _validate_path(self, path: str) -> Optional[str]:
-        """Validate and normalize path.
-
-        Args:
-            path: User-provided path.
-
-        Returns:
-            Normalized path or None if invalid.
-        """
-        if not path:
-            return None
-
-        # Remove any leading/trailing whitespace
-        path = path.strip()
-
-        # Preserve whether path ends with / (indicates directory)
-        is_directory = path.endswith("/")
-
-        # Ensure path starts with / for consistency
-        if not path.startswith("/"):
-            path = "/" + path
-
-        # Check for directory traversal patterns
-        if ".." in path or path.count("//") > 0:
-            return None
-
-        # Normalize the path
-        try:
-            # Convert to Path object and resolve to canonical form
-            normalized = str(Path(path).as_posix())
-
-            # Ensure it still starts with /
-            if not normalized.startswith("/"):
-                return None
-
-            # Preserve trailing slash for directories
-            if is_directory and not normalized.endswith("/") and normalized != "/":
-                normalized = normalized + "/"
-
-            return normalized
-        except Exception:
-            return None
-
-    # -----------------------------
-    # Internal helpers
-    # -----------------------------
-    def _view(self, path: str, view_range: Optional[List[int]] = None) -> str:
-        """View directory contents or file contents."""
-        validated_path = self._validate_path(path)
-        if not validated_path:
-            return "Error: Invalid path."
-
-        # Check if viewing directory (ends with / or is root)
-        if validated_path == "/" or validated_path.endswith("/"):
-            return self._view_directory(validated_path)
-
-        # Otherwise view file
-        return self._view_file(validated_path, view_range)
-
-    def _view_directory(self, path: str) -> str:
-        """List files in a directory."""
-        # Ensure path ends with / for proper prefix matching
-        search_path = path if path.endswith("/") else path + "/"
-
-        # Find all files that start with this directory path
-        query = {
-            "user_id": self.user_id,
-            "tool_id": self.tool_id,
-            "path": {"$regex": f"^{re.escape(search_path)}"}
-        }
-
-        docs = list(self.collection.find(query, {"path": 1}))
-
-        if not docs:
-            return f"Directory: {path}\n(empty)"
-
-        # Extract filenames relative to the directory
-        files = []
-        for doc in docs:
-            file_path = doc["path"]
-            # Remove the directory prefix
-            if file_path.startswith(search_path):
-                relative = file_path[len(search_path):]
-                if relative:
-                    files.append(relative)
-
-        files.sort()
-        file_list = "\n".join(f"- {f}" for f in files)
-        return f"Directory: {path}\n{file_list}"
-
-    def _view_file(self, path: str, view_range: Optional[List[int]] = None) -> str:
-        """View file contents with optional line range."""
-        doc = self.collection.find_one({"user_id": self.user_id, "tool_id": self.tool_id, "path": path})
-
-        if not doc or not doc.get("content"):
-            return f"Error: File not found: {path}"
-
-        content = str(doc["content"])
-
-        # Apply view_range if specified
-        if view_range and len(view_range) == 2:
-            lines = content.split("\n")
-            start, end = view_range
-            # Convert to 0-indexed
-            start_idx = max(0, start - 1)
-            end_idx = min(len(lines), end)
-
-            if start_idx >= len(lines):
-                return f"Error: Line range out of bounds. File has {len(lines)} lines."
-
-            selected_lines = lines[start_idx:end_idx]
-            # Add line numbers (enumerate with 1-based start)
-            numbered_lines = [f"{i}: {line}" for i, line in enumerate(selected_lines, start=start)]
-            return "\n".join(numbered_lines)
-
-        return content
-
-    def _create(self, path: str, file_text: str) -> str:
-        """Create or overwrite a file."""
-        validated_path = self._validate_path(path)
-        if not validated_path:
-            return "Error: Invalid path."
-
-        if validated_path == "/" or validated_path.endswith("/"):
-            return "Error: Cannot create a file at directory path."
-
-        self.collection.update_one(
-            {"user_id": self.user_id, "tool_id": self.tool_id, "path": validated_path},
-            {
-                "$set": {
-                    "content": file_text,
-                    "updated_at": datetime.now()
-                }
-            },
-            upsert=True
-        )
-
-        return f"File created: {validated_path}"
-
-    def _str_replace(self, path: str, old_str: str, new_str: str) -> str:
-        """Replace text in a file."""
-        validated_path = self._validate_path(path)
-        if not validated_path:
-            return "Error: Invalid path."
-
-        if not old_str:
-            return "Error: old_str is required."
-
-        doc = self.collection.find_one({"user_id": self.user_id, "tool_id": self.tool_id, "path": validated_path})
-
-        if not doc or not doc.get("content"):
-            return f"Error: File not found: {validated_path}"
-
-        current_content = str(doc["content"])
-
-        # Check if old_str exists (case-insensitive)
-        if old_str.lower() not in current_content.lower():
-            return f"Error: String '{old_str}' not found in file."
-
-        # Replace the string (case-insensitive)
-        import re as regex_module
-        updated_content = regex_module.sub(regex_module.escape(old_str), new_str, current_content, flags=regex_module.IGNORECASE)
-
-        self.collection.update_one(
-            {"user_id": self.user_id, "tool_id": self.tool_id, "path": validated_path},
-            {
-                "$set": {
-                    "content": updated_content,
-                    "updated_at": datetime.now()
-                }
-            }
-        )
-
-        return f"File updated: {validated_path}"
-
-    def _insert(self, path: str, insert_line: int, insert_text: str) -> str:
-        """Insert text at a specific line."""
-        validated_path = self._validate_path(path)
-        if not validated_path:
-            return "Error: Invalid path."
-
-        if not insert_text:
-            return "Error: insert_text is required."
-
-        doc = self.collection.find_one({"user_id": self.user_id, "tool_id": self.tool_id, "path": validated_path})
-
-        if not doc or not doc.get("content"):
-            return f"Error: File not found: {validated_path}"
-
-        current_content = str(doc["content"])
-        lines = current_content.split("\n")
-
-        # Convert to 0-indexed
-        index = insert_line - 1
-        if index < 0 or index > len(lines):
-            return f"Error: Invalid line number. File has {len(lines)} lines."
-
-        lines.insert(index, insert_text)
-        updated_content = "\n".join(lines)
-
-        self.collection.update_one(
-            {"user_id": self.user_id, "tool_id": self.tool_id, "path": validated_path},
-            {
-                "$set": {
-                    "content": updated_content,
-                    "updated_at": datetime.now()
-                }
-            }
-        )
-
-        return f"Text inserted at line {insert_line} in {validated_path}"
-
-    def _delete(self, path: str) -> str:
-        """Delete a file or directory."""
-        validated_path = self._validate_path(path)
-        if not validated_path:
-            return "Error: Invalid path."
-
-        if validated_path == "/":
-            # Delete all files for this user and tool
-            result = self.collection.delete_many({"user_id": self.user_id, "tool_id": self.tool_id})
-            return f"Deleted {result.deleted_count} file(s) from memory."
-
-        # Check if it's a directory (ends with /)
-        if validated_path.endswith("/"):
-            # Delete all files in directory
-            result = self.collection.delete_many({
-                "user_id": self.user_id,
-                "tool_id": self.tool_id,
-                "path": {"$regex": f"^{re.escape(validated_path)}"}
-            })
-            return f"Deleted directory and {result.deleted_count} file(s)."
-
-        # Try to delete as directory first (without trailing slash)
-        # Check if any files start with this path + /
-        search_path = validated_path + "/"
-        directory_result = self.collection.delete_many({
-            "user_id": self.user_id,
-            "tool_id": self.tool_id,
-            "path": {"$regex": f"^{re.escape(search_path)}"}
-        })
-
-        if directory_result.deleted_count > 0:
-            return f"Deleted directory and {directory_result.deleted_count} file(s)."
-
-        # Delete single file
-        result = self.collection.delete_one({
-            "user_id": self.user_id,
-            "tool_id": self.tool_id,
-            "path": validated_path
-        })
-
-        if result.deleted_count:
-            return f"Deleted: {validated_path}"
-        return f"Error: File not found: {validated_path}"
-
-    def _rename(self, old_path: str, new_path: str) -> str:
-        """Rename or move a file/directory."""
-        validated_old = self._validate_path(old_path)
-        validated_new = self._validate_path(new_path)
-
-        if not validated_old or not validated_new:
-            return "Error: Invalid path."
-
-        if validated_old == "/" or validated_new == "/":
-            return "Error: Cannot rename root directory."
-
-        # Check if renaming a directory
-        if validated_old.endswith("/"):
-            # Ensure validated_new also ends with / for proper path replacement
-            if not validated_new.endswith("/"):
-                validated_new = validated_new + "/"
-
-            # Find all files in the old directory
-            docs = list(self.collection.find({
-                "user_id": self.user_id,
-                "tool_id": self.tool_id,
-                "path": {"$regex": f"^{re.escape(validated_old)}"}
-            }))
-
-            if not docs:
-                return f"Error: Directory not found: {validated_old}"
-
-            # Update paths for all files
-            for doc in docs:
-                old_file_path = doc["path"]
-                new_file_path = old_file_path.replace(validated_old, validated_new, 1)
-
-                self.collection.update_one(
-                    {"_id": doc["_id"]},
-                    {"$set": {"path": new_file_path, "updated_at": datetime.now()}}
-                )
-
-            return f"Renamed directory: {validated_old} -> {validated_new} ({len(docs)} files)"
-
-        # Rename single file
-        doc = self.collection.find_one({
-            "user_id": self.user_id,
-            "tool_id": self.tool_id,
-            "path": validated_old
-        })
-
-        if not doc:
-            return f"Error: File not found: {validated_old}"
-
-        # Check if new path already exists
-        existing = self.collection.find_one({
-            "user_id": self.user_id,
-            "tool_id": self.tool_id,
-            "path": validated_new
-        })
-
-        if existing:
-            return f"Error: File already exists at {validated_new}"
-
-        # Delete the old document and create a new one with the new path
-        self.collection.delete_one({"user_id": self.user_id, "tool_id": self.tool_id, "path": validated_old})
-        self.collection.insert_one({
-            "user_id": self.user_id,
-            "tool_id": self.tool_id,
-            "path": validated_new,
-            "content": doc.get("content", ""),
-            "updated_at": datetime.now()
-        })
-
-        return f"Renamed: {validated_old} -> {validated_new}"

application/agents/tools/notes.py

@@ -1,199 +0,0 @@
-from datetime import datetime
-from typing import Any, Dict, List, Optional
-import uuid
-
-from .base import Tool
-from application.core.mongo_db import MongoDB
-from application.core.settings import settings
-
-
-class NotesTool(Tool):
-    """Notepad
-
-    Single note. Supports viewing, overwriting, string replacement.
-    """
-
-    def __init__(self, tool_config: Optional[Dict[str, Any]] = None, user_id: Optional[str] = None) -> None:
-        """Initialize the tool.
-
-        Args:
-            tool_config: Optional tool configuration. Should include:
-                - tool_id: Unique identifier for this notes tool instance (from user_tools._id)
-                           This ensures each user's tool configuration has isolated notes
-            user_id: The authenticated user's id (should come from decoded_token["sub"]).
-        """
-        self.user_id: Optional[str] = user_id
-
-        # Get tool_id from configuration (passed from user_tools._id in production)
-        # In production, tool_id is the MongoDB ObjectId string from user_tools collection
-        if tool_config and "tool_id" in tool_config:
-            self.tool_id = tool_config["tool_id"]
-        elif user_id:
-            # Fallback for backward compatibility or testing
-            self.tool_id = f"default_{user_id}"
-        else:
-            # Last resort fallback (shouldn't happen in normal use)
-            self.tool_id = str(uuid.uuid4())
-
-        db = MongoDB.get_client()[settings.MONGO_DB_NAME]
-        self.collection = db["notes"]
-
-    # -----------------------------
-    # Action implementations
-    # -----------------------------
-    def execute_action(self, action_name: str, **kwargs: Any) -> str:
-        """Execute an action by name.
-
-        Args:
-            action_name: One of view, overwrite, str_replace, insert, delete.
-            **kwargs: Parameters for the action.
-
-        Returns:
-            A human-readable string result.
-        """
-        if not self.user_id:
-             return "Error: NotesTool requires a valid user_id."
-
-        if action_name == "view":
-            return self._get_note()
-
-        if action_name == "overwrite":
-            return self._overwrite_note(kwargs.get("text", ""))
-
-        if action_name == "str_replace":
-            return self._str_replace(kwargs.get("old_str", ""), kwargs.get("new_str", ""))
-
-        if action_name == "insert":
-            return self._insert(kwargs.get("line_number", 1), kwargs.get("text", ""))
-
-        if action_name == "delete":
-            return self._delete_note()
-
-        return f"Unknown action: {action_name}"
-
-    def get_actions_metadata(self) -> List[Dict[str, Any]]:
-        """Return JSON metadata describing supported actions for tool schemas."""
-        return [
-            {
-                "name": "view",
-                "description": "Retrieve the user's note.",
-                "parameters": {"type": "object", "properties": {}},
-            },
-            {
-                "name": "overwrite",
-                "description": "Replace the entire note content (creates if doesn't exist).",
-                "parameters": {
-                    "type": "object",
-                    "properties": {
-                        "text": {"type": "string", "description": "New note content."}
-                    },
-                    "required": ["text"],
-                },
-            },
-            {
-                "name": "str_replace",
-                "description": "Replace occurrences of old_str with new_str in the note.",
-                "parameters": {
-                    "type": "object",
-                    "properties": {
-                        "old_str": {"type": "string", "description": "String to find."},
-                        "new_str": {"type": "string", "description": "String to replace with."}
-                    },
-                    "required": ["old_str", "new_str"],
-                },
-            },
-            {
-                "name": "insert",
-                "description": "Insert text at the specified line number (1-indexed).",
-                "parameters": {
-                    "type": "object",
-                    "properties": {
-                        "line_number": {"type": "integer", "description": "Line number to insert at (1-indexed)."},
-                        "text": {"type": "string", "description": "Text to insert."}
-                    },
-                    "required": ["line_number", "text"],
-                },
-            },
-            {
-                "name": "delete",
-                "description": "Delete the user's note.",
-                "parameters": {"type": "object", "properties": {}},
-            },
-        ]
-
-    def get_config_requirements(self) -> Dict[str, Any]:
-        """Return configuration requirements (none for now)."""
-        return {}
-
-    # -----------------------------
-    # Internal helpers (single-note)
-    # -----------------------------
-    def _get_note(self) -> str:
-        doc = self.collection.find_one({"user_id": self.user_id, "tool_id": self.tool_id})
-        if not doc or not doc.get("note"):
-            return "No note found."
-        return str(doc["note"])
-
-    def _overwrite_note(self, content: str) -> str:
-        content = (content or "").strip()
-        if not content:
-            return "Note content required."
-        self.collection.update_one(
-            {"user_id": self.user_id, "tool_id": self.tool_id},
-            {"$set": {"note": content, "updated_at": datetime.utcnow()}},
-            upsert=True,  # ✅ create if missing
-        )
-        return "Note saved."
-
-    def _str_replace(self, old_str: str, new_str: str) -> str:
-        if not old_str:
-            return "old_str is required."
-
-        doc = self.collection.find_one({"user_id": self.user_id, "tool_id": self.tool_id})
-        if not doc or not doc.get("note"):
-            return "No note found."
-
-        current_note = str(doc["note"])
-
-        # Case-insensitive search
-        if old_str.lower() not in current_note.lower():
-            return f"String '{old_str}' not found in note."
-
-        # Case-insensitive replacement
-        import re
-        updated_note = re.sub(re.escape(old_str), new_str, current_note, flags=re.IGNORECASE)
-
-        self.collection.update_one(
-            {"user_id": self.user_id, "tool_id": self.tool_id},
-            {"$set": {"note": updated_note, "updated_at": datetime.utcnow()}},
-        )
-        return "Note updated."
-
-    def _insert(self, line_number: int, text: str) -> str:
-        if not text:
-            return "Text is required."
-
-        doc = self.collection.find_one({"user_id": self.user_id, "tool_id": self.tool_id})
-        if not doc or not doc.get("note"):
-            return "No note found."
-
-        current_note = str(doc["note"])
-        lines = current_note.split("\n")
-
-        # Convert to 0-indexed and validate
-        index = line_number - 1
-        if index < 0 or index > len(lines):
-            return f"Invalid line number. Note has {len(lines)} lines."
-
-        lines.insert(index, text)
-        updated_note = "\n".join(lines)
-
-        self.collection.update_one(
-            {"user_id": self.user_id, "tool_id": self.tool_id},
-            {"$set": {"note": updated_note, "updated_at": datetime.utcnow()}},
-        )
-        return "Text inserted."
-
-    def _delete_note(self) -> str:
-        res = self.collection.delete_one({"user_id": self.user_id, "tool_id": self.tool_id})
-        return "Note deleted." if res.deleted_count else "No note found to delete."

application/agents/tools/todo_list.py

@@ -1,321 +0,0 @@
-from datetime import datetime
-from typing import Any, Dict, List, Optional
-import uuid
-
-from .base import Tool
-from application.core.mongo_db import MongoDB
-from application.core.settings import settings
-
-
-class TodoListTool(Tool):
-    """Todo List
-
-    Manages todo items for users. Supports creating, viewing, updating, and deleting todos.
-    """
-
-    def __init__(self, tool_config: Optional[Dict[str, Any]] = None, user_id: Optional[str] = None) -> None:
-        """Initialize the tool.
-
-        Args:
-            tool_config: Optional tool configuration. Should include:
-                - tool_id: Unique identifier for this todo list tool instance (from user_tools._id)
-                           This ensures each user's tool configuration has isolated todos
-            user_id: The authenticated user's id (should come from decoded_token["sub"]).
-        """
-        self.user_id: Optional[str] = user_id
-
-        # Get tool_id from configuration (passed from user_tools._id in production)
-        # In production, tool_id is the MongoDB ObjectId string from user_tools collection
-        if tool_config and "tool_id" in tool_config:
-            self.tool_id = tool_config["tool_id"]
-        elif user_id:
-            # Fallback for backward compatibility or testing
-            self.tool_id = f"default_{user_id}"
-        else:
-            # Last resort fallback (shouldn't happen in normal use)
-            self.tool_id = str(uuid.uuid4())
-
-        db = MongoDB.get_client()[settings.MONGO_DB_NAME]
-        self.collection = db["todos"]
-
-    # -----------------------------
-    # Action implementations
-    # -----------------------------
-    def execute_action(self, action_name: str, **kwargs: Any) -> str:
-        """Execute an action by name.
-
-        Args:
-            action_name: One of list, create, get, update, complete, delete.
-            **kwargs: Parameters for the action.
-
-        Returns:
-            A human-readable string result.
-        """
-        if not self.user_id:
-            return "Error: TodoListTool requires a valid user_id."
-
-        if action_name == "list":
-            return self._list()
-
-        if action_name == "create":
-            return self._create(kwargs.get("title", ""))
-
-        if action_name == "get":
-            return self._get(kwargs.get("todo_id"))
-
-        if action_name == "update":
-            return self._update(
-                kwargs.get("todo_id"),
-                kwargs.get("title", "")
-            )
-
-        if action_name == "complete":
-            return self._complete(kwargs.get("todo_id"))
-
-        if action_name == "delete":
-            return self._delete(kwargs.get("todo_id"))
-
-        return f"Unknown action: {action_name}"
-
-    def get_actions_metadata(self) -> List[Dict[str, Any]]:
-        """Return JSON metadata describing supported actions for tool schemas."""
-        return [
-            {
-                "name": "list",
-                "description": "List all todos for the user.",
-                "parameters": {"type": "object", "properties": {}},
-            },
-            {
-                "name": "create",
-                "description": "Create a new todo item.",
-                "parameters": {
-                    "type": "object",
-                    "properties": {
-                        "title": {
-                            "type": "string",
-                            "description": "Title of the todo item."
-                        }
-                    },
-                    "required": ["title"],
-                },
-            },
-            {
-                "name": "get",
-                "description": "Get a specific todo by ID.",
-                "parameters": {
-                    "type": "object",
-                    "properties": {
-                        "todo_id": {
-                            "type": "integer",
-                            "description": "The ID of the todo to retrieve."
-                        }
-                    },
-                    "required": ["todo_id"],
-                },
-            },
-            {
-                "name": "update",
-                "description": "Update a todo's title by ID.",
-                "parameters": {
-                    "type": "object",
-                    "properties": {
-                        "todo_id": {
-                            "type": "integer",
-                            "description": "The ID of the todo to update."
-                        },
-                        "title": {
-                            "type": "string",
-                            "description": "The new title for the todo."
-                        }
-                    },
-                    "required": ["todo_id", "title"],
-                },
-            },
-            {
-                "name": "complete",
-                "description": "Mark a todo as completed.",
-                "parameters": {
-                    "type": "object",
-                    "properties": {
-                        "todo_id": {
-                            "type": "integer",
-                            "description": "The ID of the todo to mark as completed."
-                        }
-                    },
-                    "required": ["todo_id"],
-                },
-            },
-            {
-                "name": "delete",
-                "description": "Delete a specific todo by ID.",
-                "parameters": {
-                    "type": "object",
-                    "properties": {
-                        "todo_id": {
-                            "type": "integer",
-                            "description": "The ID of the todo to delete."
-                        }
-                    },
-                    "required": ["todo_id"],
-                },
-            },
-        ]
-
-    def get_config_requirements(self) -> Dict[str, Any]:
-        """Return configuration requirements."""
-        return {}
-
-    # -----------------------------
-    # Internal helpers
-    # -----------------------------
-    def _coerce_todo_id(self, value: Optional[Any]) -> Optional[int]:
-        """Convert todo identifiers to sequential integers."""
-        if value is None:
-            return None
-
-        if isinstance(value, int):
-            return value if value > 0 else None
-
-        if isinstance(value, str):
-            stripped = value.strip()
-            if stripped.isdigit():
-                numeric_value = int(stripped)
-                return numeric_value if numeric_value > 0 else None
-
-        return None
-
-    def _get_next_todo_id(self) -> int:
-        """Get the next sequential todo_id for this user and tool.
-
-        Returns a simple integer (1, 2, 3, ...) scoped to this user/tool.
-        With 5-10 todos max, scanning is negligible.
-        """
-        # Find all todos for this user/tool and get their IDs
-        todos = list(self.collection.find(
-            {"user_id": self.user_id, "tool_id": self.tool_id},
-            {"todo_id": 1}
-        ))
-
-        # Find the maximum todo_id
-        max_id = 0
-        for todo in todos:
-            todo_id = self._coerce_todo_id(todo.get("todo_id"))
-            if todo_id is not None:
-                max_id = max(max_id, todo_id)
-
-        return max_id + 1
-
-    def _list(self) -> str:
-        """List all todos for the user."""
-        cursor = self.collection.find({"user_id": self.user_id, "tool_id": self.tool_id})
-        todos = list(cursor)
-
-        if not todos:
-            return "No todos found."
-
-        result_lines = ["Todos:"]
-        for doc in todos:
-            todo_id = doc.get("todo_id")
-            title = doc.get("title", "Untitled")
-            status = doc.get("status", "open")
-
-            line = f"[{todo_id}] {title} ({status})"
-            result_lines.append(line)
-
-        return "\n".join(result_lines)
-
-    def _create(self, title: str) -> str:
-        """Create a new todo item."""
-        title = (title or "").strip()
-        if not title:
-            return "Error: Title is required."
-
-        now = datetime.now()
-        todo_id = self._get_next_todo_id()
-
-        doc = {
-            "todo_id": todo_id,
-            "user_id": self.user_id,
-            "tool_id": self.tool_id,
-            "title": title,
-            "status": "open",
-            "created_at": now,
-            "updated_at": now,
-        }
-        self.collection.insert_one(doc)
-        return f"Todo created with ID {todo_id}: {title}"
-
-    def _get(self, todo_id: Optional[Any]) -> str:
-        """Get a specific todo by ID."""
-        parsed_todo_id = self._coerce_todo_id(todo_id)
-        if parsed_todo_id is None:
-            return "Error: todo_id must be a positive integer."
-
-        doc = self.collection.find_one({
-            "user_id": self.user_id,
-            "tool_id": self.tool_id,
-            "todo_id": parsed_todo_id
-        })
-
-        if not doc:
-            return f"Error: Todo with ID {parsed_todo_id} not found."
-
-        title = doc.get("title", "Untitled")
-        status = doc.get("status", "open")
-
-        result = f"Todo [{parsed_todo_id}]:\nTitle: {title}\nStatus: {status}"
-
-        return result
-
-    def _update(self, todo_id: Optional[Any], title: str) -> str:
-        """Update a todo's title by ID."""
-        parsed_todo_id = self._coerce_todo_id(todo_id)
-        if parsed_todo_id is None:
-            return "Error: todo_id must be a positive integer."
-
-        title = (title or "").strip()
-        if not title:
-            return "Error: Title is required."
-
-        result = self.collection.update_one(
-            {"user_id": self.user_id, "tool_id": self.tool_id, "todo_id": parsed_todo_id},
-            {"$set": {"title": title, "updated_at": datetime.now()}}
-        )
-
-        if result.matched_count == 0:
-            return f"Error: Todo with ID {parsed_todo_id} not found."
-
-        return f"Todo {parsed_todo_id} updated to: {title}"
-
-    def _complete(self, todo_id: Optional[Any]) -> str:
-        """Mark a todo as completed."""
-        parsed_todo_id = self._coerce_todo_id(todo_id)
-        if parsed_todo_id is None:
-            return "Error: todo_id must be a positive integer."
-
-        result = self.collection.update_one(
-            {"user_id": self.user_id, "tool_id": self.tool_id, "todo_id": parsed_todo_id},
-            {"$set": {"status": "completed", "updated_at": datetime.now()}}
-        )
-
-        if result.matched_count == 0:
-            return f"Error: Todo with ID {parsed_todo_id} not found."
-
-        return f"Todo {parsed_todo_id} marked as completed."
-
-    def _delete(self, todo_id: Optional[Any]) -> str:
-        """Delete a specific todo by ID."""
-        parsed_todo_id = self._coerce_todo_id(todo_id)
-        if parsed_todo_id is None:
-            return "Error: todo_id must be a positive integer."
-
-        result = self.collection.delete_one({
-            "user_id": self.user_id,
-            "tool_id": self.tool_id,
-            "todo_id": parsed_todo_id
-        })
-
-        if result.deleted_count == 0:
-            return f"Error: Todo with ID {parsed_todo_id} not found."
-
-        return f"Todo {parsed_todo_id} deleted."

application/agents/tools/tool_action_parser.py

@@ -20,24 +20,20 @@ class ToolActionParser:
         try:
             call_args = json.loads(call.arguments)
             tool_parts = call.name.split("_")
-
+            
             # If the tool name doesn't contain an underscore, it's likely a hallucinated tool
             if len(tool_parts) < 2:
-                logger.warning(
-                    f"Invalid tool name format: {call.name}. Expected format: action_name_tool_id"
-                )
+                logger.warning(f"Invalid tool name format: {call.name}. Expected format: action_name_tool_id")
                 return None, None, None
-
+                
             tool_id = tool_parts[-1]
             action_name = "_".join(tool_parts[:-1])
-
+            
             # Validate that tool_id looks like a numerical ID
             if not tool_id.isdigit():
-                logger.warning(
-                    f"Tool ID '{tool_id}' is not numerical. This might be a hallucinated tool call."
-                )
-
-        except (AttributeError, TypeError, json.JSONDecodeError) as e:
+                logger.warning(f"Tool ID '{tool_id}' is not numerical. This might be a hallucinated tool call.")
+                
+        except (AttributeError, TypeError) as e:
             logger.error(f"Error parsing OpenAI LLM call: {e}")
             return None, None, None
         return tool_id, action_name, call_args
@@ -46,23 +42,19 @@ class ToolActionParser:
         try:
             call_args = call.arguments
             tool_parts = call.name.split("_")
-
+            
             # If the tool name doesn't contain an underscore, it's likely a hallucinated tool
             if len(tool_parts) < 2:
-                logger.warning(
-                    f"Invalid tool name format: {call.name}. Expected format: action_name_tool_id"
-                )
+                logger.warning(f"Invalid tool name format: {call.name}. Expected format: action_name_tool_id")
                 return None, None, None
-
+                
             tool_id = tool_parts[-1]
             action_name = "_".join(tool_parts[:-1])
-
+            
             # Validate that tool_id looks like a numerical ID
             if not tool_id.isdigit():
-                logger.warning(
-                    f"Tool ID '{tool_id}' is not numerical. This might be a hallucinated tool call."
-                )
-
+                logger.warning(f"Tool ID '{tool_id}' is not numerical. This might be a hallucinated tool call.")
+                
         except (AttributeError, TypeError) as e:
             logger.error(f"Error parsing Google LLM call: {e}")
             return None, None, None

application/agents/tools/tool_manager.py

@@ -23,23 +23,16 @@ class ToolManager:
                     tool_config = self.config.get(name, {})
                     self.tools[name] = obj(tool_config)
 
-    def load_tool(self, tool_name, tool_config, user_id=None):
+    def load_tool(self, tool_name, tool_config):
         self.config[tool_name] = tool_config
         module = importlib.import_module(f"application.agents.tools.{tool_name}")
         for member_name, obj in inspect.getmembers(module, inspect.isclass):
             if issubclass(obj, Tool) and obj is not Tool:
-                if tool_name in {"mcp_tool", "notes", "memory", "todo_list"} and user_id:
-                    return obj(tool_config, user_id)
-                else:
-                    return obj(tool_config)
+                return obj(tool_config)
 
-    def execute_action(self, tool_name, action_name, user_id=None, **kwargs):
+    def execute_action(self, tool_name, action_name, **kwargs):
         if tool_name not in self.tools:
             raise ValueError(f"Tool '{tool_name}' not loaded")
-        if tool_name in {"mcp_tool", "memory", "todo_list"} and user_id:
-            tool_config = self.config.get(tool_name, {})
-            tool = self.load_tool(tool_name, tool_config, user_id)
-            return tool.execute_action(action_name, **kwargs)
         return self.tools[tool_name].execute_action(action_name, **kwargs)
 
     def get_all_actions_metadata(self):

application/api/answer/routes/answer.py

@@ -72,9 +72,6 @@ class AnswerResource(Resource, BaseAnswerResource):
             agent = processor.create_agent()
             retriever = processor.create_retriever()
 
-            if error := self.check_usage(processor.agent_config):
-                return error
-
             stream = self.complete_stream(
                 question=data["question"],
                 agent=agent,

application/api/answer/routes/base.py

@@ -3,7 +3,7 @@ import json
 import logging
 from typing import Any, Dict, Generator, List, Optional
 
-from flask import Response, make_response, jsonify
+from flask import Response
 from flask_restx import Namespace
 
 from application.api.answer.services.conversation_service import ConversationService
@@ -25,7 +25,6 @@ class BaseAnswerResource:
     def __init__(self):
         mongo = MongoDB.get_client()
         db = mongo[settings.MONGO_DB_NAME]
-        self.db = db
         self.user_logs_collection = db["user_logs"]
         self.gpt_model = get_gpt_model()
         self.conversation_service = ConversationService()
@@ -41,88 +40,6 @@ class BaseAnswerResource:
             return missing_fields
         return None
 
-    def check_usage(
-            self, agent_config: Dict
-    ) -> Optional[Response]:
-        """Check if there is a usage limit and if it is exceeded
-
-        Args:
-            agent_config: The config dict of agent instance
-
-        Returns:
-            None or Response if either of limits exceeded.
-        
-        """
-        api_key = agent_config.get("user_api_key")
-        if not api_key:
-            return None
-        
-        agents_collection = self.db["agents"]
-        agent = agents_collection.find_one({"key": api_key})
-
-        if not agent:
-            return make_response(
-                jsonify(
-                    {
-                        "success": False,
-                        "message": "Invalid API key."
-                    }
-                ),
-                401
-            )
-
-        limited_token_mode = agent.get("limited_token_mode", False)
-        limited_request_mode = agent.get("limited_request_mode", False)
-        token_limit = int(agent.get("token_limit", settings.DEFAULT_AGENT_LIMITS["token_limit"]))
-        request_limit = int(agent.get("request_limit", settings.DEFAULT_AGENT_LIMITS["request_limit"]))
-
-        token_usage_collection = self.db["token_usage"]
-
-        end_date = datetime.datetime.now()
-        start_date = end_date - datetime.timedelta(hours=24)
-
-        match_query = {
-            "timestamp": {"$gte": start_date, "$lte": end_date},
-            "api_key": api_key
-        }
-        
-        if limited_token_mode:
-            token_pipeline = [
-                {"$match": match_query},
-                {
-                    "$group": {
-                        "_id": None,
-                        "total_tokens": {"$sum": {"$add": ["$prompt_tokens", "$generated_tokens"]}}
-                    }
-                }
-            ]
-            token_result = list(token_usage_collection.aggregate(token_pipeline))
-            daily_token_usage = token_result[0]["total_tokens"] if token_result else 0
-        else:
-            daily_token_usage = 0
-
-        if limited_request_mode:
-            daily_request_usage = token_usage_collection.count_documents(match_query)
-        else:
-            daily_request_usage = 0
-
-        if not limited_token_mode and not limited_request_mode:
-            return None
-        elif limited_token_mode and token_limit > daily_token_usage:
-            return None
-        elif limited_request_mode and request_limit > daily_request_usage:
-            return None
-
-        return make_response(
-            jsonify(
-                {
-                    "success": False,
-                    "message": "Exceeding usage limit, please try again later."
-                }
-            ),
-            429, # too many requests
-        )
-
     def complete_stream(
         self,
         question: str,
@@ -193,8 +110,6 @@ class BaseAnswerResource:
                         yield f"data: {data}\n\n"
                 elif "tool_calls" in line:
                     tool_calls = line["tool_calls"]
-                    data = json.dumps({"type": "tool_calls", "tool_calls": tool_calls})
-                    yield f"data: {data}\n\n"
                 elif "thought" in line:
                     thought += line["thought"]
                     data = json.dumps({"type": "thought", "thought": line["thought"]})
@@ -276,43 +191,6 @@ class BaseAnswerResource:
 
             data = json.dumps({"type": "end"})
             yield f"data: {data}\n\n"
-        except GeneratorExit:
-            # Client aborted the connection
-            logger.info(
-                f"Stream aborted by client for question: {question[:50]}... "
-            )
-            # Save partial response to database before exiting
-            if should_save_conversation and response_full:
-                try:
-                    if isNoneDoc:
-                        for doc in source_log_docs:
-                            doc["source"] = "None"
-                    llm = LLMCreator.create_llm(
-                        settings.LLM_PROVIDER,
-                        api_key=settings.API_KEY,
-                        user_api_key=user_api_key,
-                        decoded_token=decoded_token,
-                    )
-                    self.conversation_service.save_conversation(
-                        conversation_id,
-                        question,
-                        response_full,
-                        thought,
-                        source_log_docs,
-                        tool_calls,
-                        llm,
-                        self.gpt_model,
-                        decoded_token,
-                        index=index,
-                        api_key=user_api_key,
-                        agent_id=agent_id,
-                        is_shared_usage=is_shared_usage,
-                        shared_token=shared_token,
-                        attachment_ids=attachment_ids,
-                    )
-                except Exception as e:
-                    logger.error(f"Error saving partial response: {str(e)}", exc_info=True)
-            raise
         except Exception as e:
             logger.error(f"Error in stream: {str(e)}", exc_info=True)
             data = json.dumps(

application/api/answer/routes/stream.py

@@ -76,9 +76,6 @@ class StreamResource(Resource, BaseAnswerResource):
             agent = processor.create_agent()
             retriever = processor.create_retriever()
 
-            if error := self.check_usage(processor.agent_config):
-                return error
-
             return Response(
                 self.complete_stream(
                     question=data["question"],

application/api/answer/services/stream_processor.py

@@ -69,8 +69,11 @@ class StreamProcessor:
             self.decoded_token.get("sub") if self.decoded_token is not None else None
         )
         self.conversation_id = self.data.get("conversation_id")
-        self.source = {}
-        self.all_sources = []
+        self.source = (
+            {"active_docs": self.data["active_docs"]}
+            if "active_docs" in self.data
+            else {}
+        )
         self.attachments = []
         self.history = []
         self.agent_config = {}
@@ -82,8 +85,6 @@ class StreamProcessor:
 
     def initialize(self):
         """Initialize all required components for processing"""
-        self._configure_agent()
-        self._configure_source()
         self._configure_retriever()
         self._configure_agent()
         self._load_conversation_history()
@@ -170,77 +171,13 @@ class StreamProcessor:
         source = data.get("source")
         if isinstance(source, DBRef):
             source_doc = self.db.dereference(source)
-            if source_doc:
-                data["source"] = str(source_doc["_id"])
-                data["retriever"] = source_doc.get("retriever", data.get("retriever"))
-                data["chunks"] = source_doc.get("chunks", data.get("chunks"))
-            else:
-                data["source"] = None
-        elif source == "default":
-            data["source"] = "default"
+            data["source"] = str(source_doc["_id"])
+            data["retriever"] = source_doc.get("retriever", data.get("retriever"))
+            data["chunks"] = source_doc.get("chunks", data.get("chunks"))
         else:
             data["source"] = None
-        # Handle multiple sources
-
-        sources = data.get("sources", [])
-        if sources and isinstance(sources, list):
-            sources_list = []
-            for i, source_ref in enumerate(sources):
-                if source_ref == "default":
-                    processed_source = {
-                        "id": "default",
-                        "retriever": "classic",
-                        "chunks": data.get("chunks", "2"),
-                    }
-                    sources_list.append(processed_source)
-                elif isinstance(source_ref, DBRef):
-                    source_doc = self.db.dereference(source_ref)
-                    if source_doc:
-                        processed_source = {
-                            "id": str(source_doc["_id"]),
-                            "retriever": source_doc.get("retriever", "classic"),
-                            "chunks": source_doc.get("chunks", data.get("chunks", "2")),
-                        }
-                        sources_list.append(processed_source)
-            data["sources"] = sources_list
-        else:
-            data["sources"] = []
         return data
 
-    def _configure_source(self):
-        """Configure the source based on agent data"""
-        api_key = self.data.get("api_key") or self.agent_key
-
-        if api_key:
-            agent_data = self._get_data_from_api_key(api_key)
-
-            if agent_data.get("sources") and len(agent_data["sources"]) > 0:
-                source_ids = [
-                    source["id"] for source in agent_data["sources"] if source.get("id")
-                ]
-                if source_ids:
-                    self.source = {"active_docs": source_ids}
-                else:
-                    self.source = {}
-                self.all_sources = agent_data["sources"]
-            elif agent_data.get("source"):
-                self.source = {"active_docs": agent_data["source"]}
-                self.all_sources = [
-                    {
-                        "id": agent_data["source"],
-                        "retriever": agent_data.get("retriever", "classic"),
-                    }
-                ]
-            else:
-                self.source = {}
-                self.all_sources = []
-            return
-        if "active_docs" in self.data:
-            self.source = {"active_docs": self.data["active_docs"]}
-            return
-        self.source = {}
-        self.all_sources = []
-
     def _configure_agent(self):
         """Configure the agent based on request data"""
         agent_id = self.data.get("agent_id")
@@ -266,13 +203,7 @@ class StreamProcessor:
             if data_key.get("retriever"):
                 self.retriever_config["retriever_name"] = data_key["retriever"]
             if data_key.get("chunks") is not None:
-                try:
-                    self.retriever_config["chunks"] = int(data_key["chunks"])
-                except (ValueError, TypeError):
-                    logger.warning(
-                        f"Invalid chunks value: {data_key['chunks']}, using default value 2"
-                    )
-                    self.retriever_config["chunks"] = 2
+                self.retriever_config["chunks"] = data_key["chunks"]
         elif self.agent_key:
             data_key = self._get_data_from_api_key(self.agent_key)
             self.agent_config.update(
@@ -293,13 +224,7 @@ class StreamProcessor:
             if data_key.get("retriever"):
                 self.retriever_config["retriever_name"] = data_key["retriever"]
             if data_key.get("chunks") is not None:
-                try:
-                    self.retriever_config["chunks"] = int(data_key["chunks"])
-                except (ValueError, TypeError):
-                    logger.warning(
-                        f"Invalid chunks value: {data_key['chunks']}, using default value 2"
-                    )
-                    self.retriever_config["chunks"] = 2
+                self.retriever_config["chunks"] = data_key["chunks"]
         else:
             self.agent_config.update(
                 {
@@ -318,8 +243,7 @@ class StreamProcessor:
             "token_limit": self.data.get("token_limit", settings.DEFAULT_MAX_HISTORY),
         }
 
-        api_key = self.data.get("api_key") or self.agent_key
-        if not api_key and "isNoneDoc" in self.data and self.data["isNoneDoc"]:
+        if "isNoneDoc" in self.data and self.data["isNoneDoc"]:
             self.retriever_config["chunks"] = 0
 
     def create_agent(self):

application/api/connector/routes.py

@@ -1,7 +1,6 @@
-import base64
 import datetime
 import json
-import uuid
+import logging
 
 
 from bson.objectid import ObjectId
@@ -15,6 +14,8 @@ from flask import (
 from flask_restx import fields, Namespace, Resource
 
 
+
+
 from application.api.user.tasks import (
     ingest_connector_task,
 )
@@ -23,9 +24,15 @@ from application.core.settings import settings
 from application.api import api
 
 
+from application.utils import (
+    check_required_fields
+)
+
+
 from application.parser.connectors.connector_creator import ConnectorCreator
 
 
+
 mongo = MongoDB.get_client()
 db = mongo[settings.MONGO_DB_NAME]
 sources_collection = db["sources"]
@@ -37,6 +44,185 @@ api.add_namespace(connectors_ns)
 
 
 
+@connectors_ns.route("/api/connectors/upload")
+class UploadConnector(Resource):
+    @api.expect(
+        api.model(
+            "ConnectorUploadModel",
+            {
+                "user": fields.String(required=True, description="User ID"),
+                "source": fields.String(
+                    required=True, description="Source type (google_drive, github, etc.)"
+                ),
+                "name": fields.String(required=True, description="Job name"),
+                "data": fields.String(required=True, description="Configuration data"),
+                "repo_url": fields.String(description="GitHub repository URL"),
+            },
+        )
+    )
+    @api.doc(
+        description="Uploads connector source for vectorization",
+    )
+    def post(self):
+        decoded_token = request.decoded_token
+        if not decoded_token:
+            return make_response(jsonify({"success": False}), 401)
+        data = request.form
+        required_fields = ["user", "source", "name", "data"]
+        missing_fields = check_required_fields(data, required_fields)
+        if missing_fields:
+            return missing_fields
+        try:
+            config = json.loads(data["data"])
+            source_data = None
+            sync_frequency = config.get("sync_frequency", "never")
+
+            if data["source"] == "github":
+                source_data = config.get("repo_url")
+            elif data["source"] in ["crawler", "url"]:
+                source_data = config.get("url")
+            elif data["source"] == "reddit":
+                source_data = config
+            elif data["source"] in ConnectorCreator.get_supported_connectors():
+                session_token = config.get("session_token")
+                if not session_token:
+                    return make_response(jsonify({
+                        "success": False,
+                        "error": f"Missing session_token in {data['source']} configuration"
+                    }), 400)
+
+                file_ids = config.get("file_ids", [])
+                if isinstance(file_ids, str):
+                    file_ids = [id.strip() for id in file_ids.split(',') if id.strip()]
+                elif not isinstance(file_ids, list):
+                    file_ids = []
+
+                folder_ids = config.get("folder_ids", [])
+                if isinstance(folder_ids, str):
+                    folder_ids = [id.strip() for id in folder_ids.split(',') if id.strip()]
+                elif not isinstance(folder_ids, list):
+                    folder_ids = []
+
+                config["file_ids"] = file_ids
+                config["folder_ids"] = folder_ids
+
+                task = ingest_connector_task.delay(
+                    job_name=data["name"],
+                    user=decoded_token.get("sub"),
+                    source_type=data["source"],
+                    session_token=session_token,
+                    file_ids=file_ids,
+                    folder_ids=folder_ids,
+                    recursive=config.get("recursive", False),
+                    retriever=config.get("retriever", "classic"),
+                    sync_frequency=sync_frequency
+                )
+                return make_response(jsonify({"success": True, "task_id": task.id}), 200)
+            task = ingest_connector_task.delay(
+                source_data=source_data,
+                job_name=data["name"],
+                user=decoded_token.get("sub"),
+                loader=data["source"],
+                sync_frequency=sync_frequency
+            )
+        except Exception as err:
+            current_app.logger.error(
+                f"Error uploading connector source: {err}", exc_info=True
+            )
+            return make_response(jsonify({"success": False}), 400)
+        return make_response(jsonify({"success": True, "task_id": task.id}), 200)
+
+
+@connectors_ns.route("/api/connectors/task_status")
+class ConnectorTaskStatus(Resource):
+    task_status_model = api.model(
+        "ConnectorTaskStatusModel",
+        {"task_id": fields.String(required=True, description="Task ID")},
+    )
+
+    @api.expect(task_status_model)
+    @api.doc(description="Get connector task status")
+    def get(self):
+        task_id = request.args.get("task_id")
+        if not task_id:
+            return make_response(
+                jsonify({"success": False, "message": "Task ID is required"}), 400
+            )
+        try:
+            from application.celery_init import celery
+
+            task = celery.AsyncResult(task_id)
+            task_meta = task.info
+            print(f"Task status: {task.status}")
+            if not isinstance(
+                task_meta, (dict, list, str, int, float, bool, type(None))
+            ):
+                task_meta = str(task_meta)
+        except Exception as err:
+            current_app.logger.error(f"Error getting task status: {err}", exc_info=True)
+            return make_response(jsonify({"success": False}), 400)
+        return make_response(jsonify({"status": task.status, "result": task_meta}), 200)
+
+
+@connectors_ns.route("/api/connectors/sources")
+class ConnectorSources(Resource):
+    @api.doc(description="Get connector sources")
+    def get(self):
+        decoded_token = request.decoded_token
+        if not decoded_token:
+            return make_response(jsonify({"success": False}), 401)
+        user = decoded_token.get("sub")
+        try:
+            sources = sources_collection.find({"user": user, "type": "connector"}).sort("date", -1)
+            connector_sources = []
+            for source in sources:
+                connector_sources.append({
+                    "id": str(source["_id"]),
+                    "name": source.get("name"),
+                    "date": source.get("date"),
+                    "type": source.get("type"),
+                    "source": source.get("source"),
+                    "tokens": source.get("tokens", ""),
+                    "retriever": source.get("retriever", "classic"),
+                    "syncFrequency": source.get("sync_frequency", ""),
+                })
+        except Exception as err:
+            current_app.logger.error(f"Error retrieving connector sources: {err}", exc_info=True)
+            return make_response(jsonify({"success": False}), 400)
+        return make_response(jsonify(connector_sources), 200)
+
+
+@connectors_ns.route("/api/connectors/delete")
+class DeleteConnectorSource(Resource):
+    @api.doc(
+        description="Delete a connector source",
+        params={"source_id": "The source ID to delete"},
+    )
+    def delete(self):
+        decoded_token = request.decoded_token
+        if not decoded_token:
+            return make_response(jsonify({"success": False}), 401)
+        source_id = request.args.get("source_id")
+        if not source_id:
+            return make_response(
+                jsonify({"success": False, "message": "source_id is required"}), 400
+            )
+        try:
+            result = sources_collection.delete_one(
+                {"_id": ObjectId(source_id), "user": decoded_token.get("sub")}
+            )
+            if result.deleted_count == 0:
+                return make_response(
+                    jsonify({"success": False, "message": "Source not found"}), 404
+                )
+        except Exception as err:
+            current_app.logger.error(
+                f"Error deleting connector source: {err}", exc_info=True
+            )
+            return make_response(jsonify({"success": False}), 400)
+        return make_response(jsonify({"success": True}), 200)
+
+
 @connectors_ns.route("/api/connectors/auth")
 class ConnectorAuth(Resource):
     @api.doc(description="Get connector OAuth authorization URL", params={"provider": "Connector provider (e.g., google_drive)"})
@@ -49,24 +235,8 @@ class ConnectorAuth(Resource):
             if not ConnectorCreator.is_supported(provider):
                 return make_response(jsonify({"success": False, "error": f"Unsupported provider: {provider}"}), 400)
 
-            decoded_token = request.decoded_token
-            if not decoded_token:
-                return make_response(jsonify({"success": False, "error": "Unauthorized"}), 401)
-            user_id = decoded_token.get('sub')
-
-            now = datetime.datetime.now(datetime.timezone.utc)
-            result = sessions_collection.insert_one({
-                "provider": provider,
-                "user": user_id,
-                "status": "pending",
-                "created_at": now
-            })
-            state_dict = {
-                "provider": provider,
-                "object_id": str(result.inserted_id)
-            }
-            state = base64.urlsafe_b64encode(json.dumps(state_dict).encode()).decode()
-
+            import uuid
+            state = str(uuid.uuid4())
             auth = ConnectorCreator.create_auth(provider)
             authorization_url = auth.get_authorization_url(state=state)
             return make_response(jsonify({
@@ -87,30 +257,25 @@ class ConnectorsCallback(Resource):
         try:
             from application.parser.connectors.connector_creator import ConnectorCreator
             from flask import request, redirect
+            import uuid
 
+            provider = request.args.get('provider', 'google_drive')
             authorization_code = request.args.get('code')
-            state = request.args.get('state')
+            _ = request.args.get('state')
             error = request.args.get('error')
 
-            state_dict = json.loads(base64.urlsafe_b64decode(state.encode()).decode())
-            provider = state_dict["provider"]
-            state_object_id = state_dict["object_id"]
-
             if error:
-                if error == "access_denied":
-                    return redirect(f"/api/connectors/callback-status?status=cancelled&message=Authentication+was+cancelled.+You+can+try+again+if+you'd+like+to+connect+your+account.&provider={provider}")
-                else:
-                    current_app.logger.warning(f"OAuth error in callback: {error}")
-                    return redirect(f"/api/connectors/callback-status?status=error&message=Authentication+failed.+Please+try+again+and+make+sure+to+grant+all+requested+permissions.&provider={provider}")
+                return redirect(f"/api/connectors/callback-status?status=error&message=OAuth+error:+{error}.+Please+try+again+and+make+sure+to+grant+all+requested+permissions,+including+offline+access.&provider={provider}")
 
             if not authorization_code:
-                return redirect(f"/api/connectors/callback-status?status=error&message=Authentication+failed.+Please+try+again+and+make+sure+to+grant+all+requested+permissions.&provider={provider}")
+                return redirect(f"/api/connectors/callback-status?status=error&message=Authorization+code+not+provided.+Please+complete+the+authorization+process+and+make+sure+to+grant+offline+access.&provider={provider}")
 
             try:
                 auth = ConnectorCreator.create_auth(provider)
                 token_info = auth.exchange_code_for_tokens(authorization_code)
 
                 session_token = str(uuid.uuid4())
+                
 
                 try:
                     credentials = auth.create_credentials_from_token_info(token_info)
@@ -125,44 +290,57 @@ class ConnectorsCallback(Resource):
                     "access_token": token_info.get("access_token"),
                     "refresh_token": token_info.get("refresh_token"),
                     "token_uri": token_info.get("token_uri"),
-                    "expiry": token_info.get("expiry")
+                    "expiry": token_info.get("expiry"),
+                    "scopes": token_info.get("scopes")
                 }
 
-                sessions_collection.find_one_and_update(
-                    {"_id": ObjectId(state_object_id), "provider": provider},
-                    {
-                        "$set": {
-                            "session_token": session_token,
-                            "token_info": sanitized_token_info,
-                            "user_email": user_email,
-                            "status": "authorized"
-                        }
-                    }
-                )
+                user_id = request.decoded_token.get("sub") if getattr(request, "decoded_token", None) else None
+                sessions_collection.insert_one({
+                    "session_token": session_token,
+                    "user": user_id,
+                    "token_info": sanitized_token_info,
+                    "created_at": datetime.datetime.now(datetime.timezone.utc),
+                    "user_email": user_email,
+                    "provider": provider
+                })
 
                 # Redirect to success page with session token and user email
                 return redirect(f"/api/connectors/callback-status?status=success&message=Authentication+successful&provider={provider}&session_token={session_token}&user_email={user_email}")
 
             except Exception as e:
                 current_app.logger.error(f"Error exchanging code for tokens: {str(e)}", exc_info=True)
-                return redirect(f"/api/connectors/callback-status?status=error&message=Authentication+failed.+Please+try+again+and+make+sure+to+grant+all+requested+permissions.&provider={provider}")
+                return redirect(f"/api/connectors/callback-status?status=error&message=Failed+to+exchange+authorization+code+for+tokens:+{str(e)}&provider={provider}")
 
         except Exception as e:
             current_app.logger.error(f"Error handling connector callback: {e}")
-            return redirect("/api/connectors/callback-status?status=error&message=Authentication+failed.+Please+try+again+and+make+sure+to+grant+all+requested+permissions.")
+            return redirect(f"/api/connectors/callback-status?status=error&message=Failed+to+complete+connector+authentication:+{str(e)}.+Please+try+again+and+make+sure+to+grant+all+requested+permissions,+including+offline+access.")
+
+
+@connectors_ns.route("/api/connectors/refresh")
+class ConnectorRefresh(Resource):
+    @api.expect(api.model("ConnectorRefreshModel", {"provider": fields.String(required=True), "refresh_token": fields.String(required=True)}))
+    @api.doc(description="Refresh connector access token")
+    def post(self):
+        try:
+            data = request.get_json()
+            provider = data.get('provider')
+            refresh_token = data.get('refresh_token')
+
+            if not provider or not refresh_token:
+                return make_response(jsonify({"success": False, "error": "provider and refresh_token are required"}), 400)
+
+            auth = ConnectorCreator.create_auth(provider)
+            token_info = auth.refresh_access_token(refresh_token)
+            return make_response(jsonify({"success": True, "token_info": token_info}), 200)
+        except Exception as e:
+            current_app.logger.error(f"Error refreshing token for connector: {e}")
+            return make_response(jsonify({"success": False, "error": str(e)}), 500)
 
 
 @connectors_ns.route("/api/connectors/files")
 class ConnectorFiles(Resource):
-    @api.expect(api.model("ConnectorFilesModel", {
-        "provider": fields.String(required=True), 
-        "session_token": fields.String(required=True), 
-        "folder_id": fields.String(required=False), 
-        "limit": fields.Integer(required=False), 
-        "page_token": fields.String(required=False),
-        "search_query": fields.String(required=False)
-    }))
-    @api.doc(description="List files from a connector provider (supports pagination and search)")
+    @api.expect(api.model("ConnectorFilesModel", {"provider": fields.String(required=True), "session_token": fields.String(required=True), "folder_id": fields.String(required=False), "limit": fields.Integer(required=False), "page_token": fields.String(required=False)}))
+    @api.doc(description="List files from a connector provider (supports pagination)")
     def post(self):
         try:
             data = request.get_json()
@@ -171,11 +349,10 @@ class ConnectorFiles(Resource):
             folder_id = data.get('folder_id')
             limit = data.get('limit', 10)
             page_token = data.get('page_token')
-            search_query = data.get('search_query')
-            
             if not provider or not session_token:
                 return make_response(jsonify({"success": False, "error": "provider and session_token are required"}), 400)
 
+
             decoded_token = request.decoded_token
             if not decoded_token:
                 return make_response(jsonify({"success": False, "error": "Unauthorized"}), 401)
@@ -185,17 +362,13 @@ class ConnectorFiles(Resource):
                 return make_response(jsonify({"success": False, "error": "Invalid or unauthorized session"}), 401)
 
             loader = ConnectorCreator.create_connector(provider, session_token)
-            input_config = {
+            documents = loader.load_data({
                 'limit': limit,
                 'list_only': True,
                 'session_token': session_token,
                 'folder_id': folder_id,
                 'page_token': page_token
-            }
-            if search_query:
-                input_config['search_query'] = search_query
-                
-            documents = loader.load_data(input_config)
+            })
 
             files = []
             for doc in documents[:limit]:
@@ -213,20 +386,13 @@ class ConnectorFiles(Resource):
                     'name': metadata.get('file_name', 'Unknown File'),
                     'type': metadata.get('mime_type', 'unknown'),
                     'size': metadata.get('size', None),
-                    'modifiedTime': formatted_time,
-                    'isFolder': metadata.get('is_folder', False)
+                    'modifiedTime': formatted_time
                 })
 
             next_token = getattr(loader, 'next_page_token', None)
             has_more = bool(next_token)
 
-            return make_response(jsonify({
-                "success": True, 
-                "files": files, 
-                "total": len(files), 
-                "next_page_token": next_token, 
-                "has_more": has_more
-            }), 200)
+            return make_response(jsonify({"success": True, "files": files, "total": len(files), "next_page_token": next_token, "has_more": has_more}), 200)
         except Exception as e:
             current_app.logger.error(f"Error loading connector files: {e}")
             return make_response(jsonify({"success": False, "error": f"Failed to load files: {str(e)}"}), 500)
@@ -235,7 +401,7 @@ class ConnectorFiles(Resource):
 @connectors_ns.route("/api/connectors/validate-session")
 class ConnectorValidateSession(Resource):
     @api.expect(api.model("ConnectorValidateSessionModel", {"provider": fields.String(required=True), "session_token": fields.String(required=True)}))
-    @api.doc(description="Validate connector session token and return user info and access token")
+    @api.doc(description="Validate connector session token and return user info")
     def post(self):
         try:
             data = request.get_json()
@@ -244,6 +410,7 @@ class ConnectorValidateSession(Resource):
             if not provider or not session_token:
                 return make_response(jsonify({"success": False, "error": "provider and session_token are required"}), 400)
 
+
             decoded_token = request.decoded_token
             if not decoded_token:
                 return make_response(jsonify({"success": False, "error": "Unauthorized"}), 401)
@@ -257,36 +424,10 @@ class ConnectorValidateSession(Resource):
             auth = ConnectorCreator.create_auth(provider)
             is_expired = auth.is_token_expired(token_info)
 
-            if is_expired and token_info.get('refresh_token'):
-                try:
-                    refreshed_token_info = auth.refresh_access_token(token_info.get('refresh_token'))
-                    sanitized_token_info = {
-                    "access_token": refreshed_token_info.get("access_token"),
-                    "refresh_token": refreshed_token_info.get("refresh_token"),
-                    "token_uri": refreshed_token_info.get("token_uri"),
-                    "expiry": refreshed_token_info.get("expiry")
-                }    
-                    sessions_collection.update_one(
-                        {"session_token": session_token},
-                        {"$set": {"token_info": sanitized_token_info}}
-                    )
-                    token_info = sanitized_token_info
-                    is_expired = False
-                except Exception as refresh_error:
-                    current_app.logger.error(f"Failed to refresh token: {refresh_error}")
-            
-            if is_expired:
-                return make_response(jsonify({
-                    "success": False,
-                    "expired": True,
-                    "error": "Session token has expired. Please reconnect."
-                }), 401)
-
             return make_response(jsonify({
                 "success": True,
-                "expired": False,
-                "user_email": session.get('user_email', 'Connected User'),
-                "access_token": token_info.get('access_token')
+                "expired": is_expired,
+                "user_email": session.get('user_email', 'Connected User')
             }), 200)
         except Exception as e:
             current_app.logger.error(f"Error validating connector session: {e}")
@@ -446,23 +587,20 @@ class ConnectorCallbackStatus(Resource):
                     .container {{ max-width: 600px; margin: 0 auto; }}
                     .success {{ color: #4CAF50; }}
                     .error {{ color: #F44336; }}
-                    .cancelled {{ color: #FF9800; }}
                 </style>
                 <script>
                     window.onload = function() {{
                         const status = "{status}";
                         const sessionToken = "{session_token}";
                         const userEmail = "{user_email}";
-
+                        
                         if (status === "success" && window.opener) {{
                             window.opener.postMessage({{
                                 type: '{provider}_auth_success',
                                 session_token: sessionToken,
                                 user_email: userEmail
                             }}, '*');
-
-                            setTimeout(() => window.close(), 3000);
-                        }} else if (status === "cancelled" || status === "error") {{
+                            
                             setTimeout(() => window.close(), 3000);
                         }}
                     }};
@@ -475,7 +613,7 @@ class ConnectorCallbackStatus(Resource):
                         <p>{message}</p>
                         {f'<p>Connected as: {user_email}</p>' if status == 'success' else ''}
                     </div>
-                    <p><small>You can close this window. {f"Your {provider.replace('_', ' ').title()} is now connected and ready to use." if status == 'success' else "Feel free to close this window."}</small></p>
+                    <p><small>You can close this window. {f"Your {provider.replace('_', ' ').title()} is now connected and ready to use." if status == 'success' else ''}</small></p>
                 </div>
             </body>
             </html>

application/api/user/__init__.py

@@ -1,5 +0,0 @@
-"""User API module - provides all user-related API endpoints"""
-
-from .routes import user
-
-__all__ = ["user"]

application/api/user/agents/__init__.py

@@ -1,7 +0,0 @@
-"""Agents module."""
-
-from .routes import agents_ns
-from .sharing import agents_sharing_ns
-from .webhooks import agents_webhooks_ns
-
-__all__ = ["agents_ns", "agents_sharing_ns", "agents_webhooks_ns"]

application/api/user/agents/sharing.py

@@ -1,263 +0,0 @@
-"""Agent management sharing functionality."""
-
-import datetime
-import secrets
-
-from bson import DBRef
-from bson.objectid import ObjectId
-from flask import current_app, jsonify, make_response, request
-from flask_restx import fields, Namespace, Resource
-
-from application.api import api
-from application.core.settings import settings
-from application.api.user.base import (
-    agents_collection,
-    db,
-    ensure_user_doc,
-    resolve_tool_details,
-    user_tools_collection,
-    users_collection,
-)
-from application.utils import generate_image_url
-
-agents_sharing_ns = Namespace(
-    "agents", description="Agent management operations", path="/api"
-)
-
-
-@agents_sharing_ns.route("/shared_agent")
-class SharedAgent(Resource):
-    @api.doc(
-        params={
-            "token": "Shared token of the agent",
-        },
-        description="Get a shared agent by token or ID",
-    )
-    def get(self):
-        shared_token = request.args.get("token")
-
-        if not shared_token:
-            return make_response(
-                jsonify({"success": False, "message": "Token or ID is required"}), 400
-            )
-        try:
-            query = {
-                "shared_publicly": True,
-                "shared_token": shared_token,
-            }
-            shared_agent = agents_collection.find_one(query)
-            if not shared_agent:
-                return make_response(
-                    jsonify({"success": False, "message": "Shared agent not found"}),
-                    404,
-                )
-            agent_id = str(shared_agent["_id"])
-            data = {
-                "id": agent_id,
-                "user": shared_agent.get("user", ""),
-                "name": shared_agent.get("name", ""),
-                "image": (
-                    generate_image_url(shared_agent["image"])
-                    if shared_agent.get("image")
-                    else ""
-                ),
-                "description": shared_agent.get("description", ""),
-                "source": (
-                    str(source_doc["_id"])
-                    if isinstance(shared_agent.get("source"), DBRef)
-                    and (source_doc := db.dereference(shared_agent.get("source")))
-                    else ""
-                ),
-                "chunks": shared_agent.get("chunks", "0"),
-                "retriever": shared_agent.get("retriever", "classic"),
-                "prompt_id": shared_agent.get("prompt_id", "default"),
-                "tools": shared_agent.get("tools", []),
-                "tool_details": resolve_tool_details(shared_agent.get("tools", [])),
-                "agent_type": shared_agent.get("agent_type", ""),
-                "status": shared_agent.get("status", ""),
-                "json_schema": shared_agent.get("json_schema"),
-                "limited_token_mode": shared_agent.get("limited_token_mode", False),
-                "token_limit": shared_agent.get("token_limit", settings.DEFAULT_AGENT_LIMITS["token_limit"]),
-                "limited_request_mode": shared_agent.get("limited_request_mode", False),
-                "request_limit": shared_agent.get("request_limit", settings.DEFAULT_AGENT_LIMITS["request_limit"]),
-                "created_at": shared_agent.get("createdAt", ""),
-                "updated_at": shared_agent.get("updatedAt", ""),
-                "shared": shared_agent.get("shared_publicly", False),
-                "shared_token": shared_agent.get("shared_token", ""),
-                "shared_metadata": shared_agent.get("shared_metadata", {}),
-            }
-
-            if data["tools"]:
-                enriched_tools = []
-                for tool in data["tools"]:
-                    tool_data = user_tools_collection.find_one({"_id": ObjectId(tool)})
-                    if tool_data:
-                        enriched_tools.append(tool_data.get("name", ""))
-                data["tools"] = enriched_tools
-            decoded_token = getattr(request, "decoded_token", None)
-            if decoded_token:
-                user_id = decoded_token.get("sub")
-                owner_id = shared_agent.get("user")
-
-                if user_id != owner_id:
-                    ensure_user_doc(user_id)
-                    users_collection.update_one(
-                        {"user_id": user_id},
-                        {"$addToSet": {"agent_preferences.shared_with_me": agent_id}},
-                    )
-            return make_response(jsonify(data), 200)
-        except Exception as err:
-            current_app.logger.error(f"Error retrieving shared agent: {err}")
-            return make_response(jsonify({"success": False}), 400)
-
-
-@agents_sharing_ns.route("/shared_agents")
-class SharedAgents(Resource):
-    @api.doc(description="Get shared agents explicitly shared with the user")
-    def get(self):
-        try:
-            decoded_token = request.decoded_token
-            if not decoded_token:
-                return make_response(jsonify({"success": False}), 401)
-            user_id = decoded_token.get("sub")
-
-            user_doc = ensure_user_doc(user_id)
-            shared_with_ids = user_doc.get("agent_preferences", {}).get(
-                "shared_with_me", []
-            )
-            shared_object_ids = [ObjectId(id) for id in shared_with_ids]
-
-            shared_agents_cursor = agents_collection.find(
-                {"_id": {"$in": shared_object_ids}, "shared_publicly": True}
-            )
-            shared_agents = list(shared_agents_cursor)
-
-            found_ids_set = {str(agent["_id"]) for agent in shared_agents}
-            stale_ids = [id for id in shared_with_ids if id not in found_ids_set]
-            if stale_ids:
-                users_collection.update_one(
-                    {"user_id": user_id},
-                    {"$pullAll": {"agent_preferences.shared_with_me": stale_ids}},
-                )
-            pinned_ids = set(user_doc.get("agent_preferences", {}).get("pinned", []))
-
-            list_shared_agents = [
-                {
-                    "id": str(agent["_id"]),
-                    "name": agent.get("name", ""),
-                    "description": agent.get("description", ""),
-                    "image": (
-                        generate_image_url(agent["image"]) if agent.get("image") else ""
-                    ),
-                    "tools": agent.get("tools", []),
-                    "tool_details": resolve_tool_details(agent.get("tools", [])),
-                    "agent_type": agent.get("agent_type", ""),
-                    "status": agent.get("status", ""),
-                    "json_schema": agent.get("json_schema"),
-                    "limited_token_mode": agent.get("limited_token_mode", False),
-                    "token_limit": agent.get("token_limit", settings.DEFAULT_AGENT_LIMITS["token_limit"]),
-                    "limited_request_mode": agent.get("limited_request_mode", False),
-                    "request_limit": agent.get("request_limit", settings.DEFAULT_AGENT_LIMITS["request_limit"]),
-                    "created_at": agent.get("createdAt", ""),
-                    "updated_at": agent.get("updatedAt", ""),
-                    "pinned": str(agent["_id"]) in pinned_ids,
-                    "shared": agent.get("shared_publicly", False),
-                    "shared_token": agent.get("shared_token", ""),
-                    "shared_metadata": agent.get("shared_metadata", {}),
-                }
-                for agent in shared_agents
-            ]
-
-            return make_response(jsonify(list_shared_agents), 200)
-        except Exception as err:
-            current_app.logger.error(f"Error retrieving shared agents: {err}")
-            return make_response(jsonify({"success": False}), 400)
-
-
-@agents_sharing_ns.route("/share_agent")
-class ShareAgent(Resource):
-    @api.expect(
-        api.model(
-            "ShareAgentModel",
-            {
-                "id": fields.String(required=True, description="ID of the agent"),
-                "shared": fields.Boolean(
-                    required=True, description="Share or unshare the agent"
-                ),
-                "username": fields.String(
-                    required=False, description="Name of the user"
-                ),
-            },
-        )
-    )
-    @api.doc(description="Share or unshare an agent")
-    def put(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-
-        data = request.get_json()
-        if not data:
-            return make_response(
-                jsonify({"success": False, "message": "Missing JSON body"}), 400
-            )
-        agent_id = data.get("id")
-        shared = data.get("shared")
-        username = data.get("username", "")
-
-        if not agent_id:
-            return make_response(
-                jsonify({"success": False, "message": "ID is required"}), 400
-            )
-        if shared is None:
-            return make_response(
-                jsonify(
-                    {
-                        "success": False,
-                        "message": "Shared parameter is required and must be true or false",
-                    }
-                ),
-                400,
-            )
-        try:
-            try:
-                agent_oid = ObjectId(agent_id)
-            except Exception:
-                return make_response(
-                    jsonify({"success": False, "message": "Invalid agent ID"}), 400
-                )
-            agent = agents_collection.find_one({"_id": agent_oid, "user": user})
-            if not agent:
-                return make_response(
-                    jsonify({"success": False, "message": "Agent not found"}), 404
-                )
-            if shared:
-                shared_metadata = {
-                    "shared_by": username,
-                    "shared_at": datetime.datetime.now(datetime.timezone.utc),
-                }
-                shared_token = secrets.token_urlsafe(32)
-                agents_collection.update_one(
-                    {"_id": agent_oid, "user": user},
-                    {
-                        "$set": {
-                            "shared_publicly": shared,
-                            "shared_metadata": shared_metadata,
-                            "shared_token": shared_token,
-                        }
-                    },
-                )
-            else:
-                agents_collection.update_one(
-                    {"_id": agent_oid, "user": user},
-                    {"$set": {"shared_publicly": shared, "shared_token": None}},
-                    {"$unset": {"shared_metadata": ""}},
-                )
-        except Exception as err:
-            current_app.logger.error(f"Error sharing/unsharing agent: {err}")
-            return make_response(jsonify({"success": False, "error": str(err)}), 400)
-        shared_token = shared_token if shared else None
-        return make_response(
-            jsonify({"success": True, "shared_token": shared_token}), 200
-        )

application/api/user/agents/webhooks.py

@@ -1,119 +0,0 @@
-"""Agent management webhook handlers."""
-
-import secrets
-
-from bson.objectid import ObjectId
-from flask import current_app, jsonify, make_response, request
-from flask_restx import Namespace, Resource
-
-from application.api import api
-from application.api.user.base import agents_collection, require_agent
-from application.api.user.tasks import process_agent_webhook
-from application.core.settings import settings
-
-
-agents_webhooks_ns = Namespace(
-    "agents", description="Agent management operations", path="/api"
-)
-
-
-@agents_webhooks_ns.route("/agent_webhook")
-class AgentWebhook(Resource):
-    @api.doc(
-        params={"id": "ID of the agent"},
-        description="Generate webhook URL for the agent",
-    )
-    def get(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        agent_id = request.args.get("id")
-        if not agent_id:
-            return make_response(
-                jsonify({"success": False, "message": "ID is required"}), 400
-            )
-        try:
-            agent = agents_collection.find_one(
-                {"_id": ObjectId(agent_id), "user": user}
-            )
-            if not agent:
-                return make_response(
-                    jsonify({"success": False, "message": "Agent not found"}), 404
-                )
-            webhook_token = agent.get("incoming_webhook_token")
-            if not webhook_token:
-                webhook_token = secrets.token_urlsafe(32)
-                agents_collection.update_one(
-                    {"_id": ObjectId(agent_id), "user": user},
-                    {"$set": {"incoming_webhook_token": webhook_token}},
-                )
-            base_url = settings.API_URL.rstrip("/")
-            full_webhook_url = f"{base_url}/api/webhooks/agents/{webhook_token}"
-        except Exception as err:
-            current_app.logger.error(
-                f"Error generating webhook URL: {err}", exc_info=True
-            )
-            return make_response(
-                jsonify({"success": False, "message": "Error generating webhook URL"}),
-                400,
-            )
-        return make_response(
-            jsonify({"success": True, "webhook_url": full_webhook_url}), 200
-        )
-
-
-@agents_webhooks_ns.route("/webhooks/agents/<string:webhook_token>")
-class AgentWebhookListener(Resource):
-    method_decorators = [require_agent]
-
-    def _enqueue_webhook_task(self, agent_id_str, payload, source_method):
-        if not payload:
-            current_app.logger.warning(
-                f"Webhook ({source_method}) received for agent {agent_id_str} with empty payload."
-            )
-        current_app.logger.info(
-            f"Incoming {source_method} webhook for agent {agent_id_str}. Enqueuing task with payload: {payload}"
-        )
-
-        try:
-            task = process_agent_webhook.delay(
-                agent_id=agent_id_str,
-                payload=payload,
-            )
-            current_app.logger.info(
-                f"Task {task.id} enqueued for agent {agent_id_str} ({source_method})."
-            )
-            return make_response(jsonify({"success": True, "task_id": task.id}), 200)
-        except Exception as err:
-            current_app.logger.error(
-                f"Error enqueuing webhook task ({source_method}) for agent {agent_id_str}: {err}",
-                exc_info=True,
-            )
-            return make_response(
-                jsonify({"success": False, "message": "Error processing webhook"}), 500
-            )
-
-    @api.doc(
-        description="Webhook listener for agent events (POST). Expects JSON payload, which is used to trigger processing.",
-    )
-    def post(self, webhook_token, agent, agent_id_str):
-        payload = request.get_json()
-        if payload is None:
-            return make_response(
-                jsonify(
-                    {
-                        "success": False,
-                        "message": "Invalid or missing JSON data in request body",
-                    }
-                ),
-                400,
-            )
-        return self._enqueue_webhook_task(agent_id_str, payload, source_method="POST")
-
-    @api.doc(
-        description="Webhook listener for agent events (GET). Uses URL query parameters as payload to trigger processing.",
-    )
-    def get(self, webhook_token, agent, agent_id_str):
-        payload = request.args.to_dict(flat=True)
-        return self._enqueue_webhook_task(agent_id_str, payload, source_method="GET")

application/api/user/analytics/__init__.py

@@ -1,5 +0,0 @@
-"""Analytics module."""
-
-from .routes import analytics_ns
-
-__all__ = ["analytics_ns"]

application/api/user/analytics/routes.py

@@ -1,540 +0,0 @@
-"""Analytics and reporting routes."""
-
-import datetime
-
-from bson.objectid import ObjectId
-from flask import current_app, jsonify, make_response, request
-from flask_restx import fields, Namespace, Resource
-
-from application.api import api
-from application.api.user.base import (
-    agents_collection,
-    conversations_collection,
-    generate_date_range,
-    generate_hourly_range,
-    generate_minute_range,
-    token_usage_collection,
-    user_logs_collection,
-)
-
-analytics_ns = Namespace(
-    "analytics", description="Analytics and reporting operations", path="/api"
-)
-
-
-@analytics_ns.route("/get_message_analytics")
-class GetMessageAnalytics(Resource):
-    get_message_analytics_model = api.model(
-        "GetMessageAnalyticsModel",
-        {
-            "api_key_id": fields.String(required=False, description="API Key ID"),
-            "filter_option": fields.String(
-                required=False,
-                description="Filter option for analytics",
-                default="last_30_days",
-                enum=[
-                    "last_hour",
-                    "last_24_hour",
-                    "last_7_days",
-                    "last_15_days",
-                    "last_30_days",
-                ],
-            ),
-        },
-    )
-
-    @api.expect(get_message_analytics_model)
-    @api.doc(description="Get message analytics based on filter option")
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-        api_key_id = data.get("api_key_id")
-        filter_option = data.get("filter_option", "last_30_days")
-
-        try:
-            api_key = (
-                agents_collection.find_one({"_id": ObjectId(api_key_id), "user": user})[
-                    "key"
-                ]
-                if api_key_id
-                else None
-            )
-        except Exception as err:
-            current_app.logger.error(f"Error getting API key: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)
-        end_date = datetime.datetime.now(datetime.timezone.utc)
-
-        if filter_option == "last_hour":
-            start_date = end_date - datetime.timedelta(hours=1)
-            group_format = "%Y-%m-%d %H:%M:00"
-        elif filter_option == "last_24_hour":
-            start_date = end_date - datetime.timedelta(hours=24)
-            group_format = "%Y-%m-%d %H:00"
-        else:
-            if filter_option in ["last_7_days", "last_15_days", "last_30_days"]:
-                filter_days = (
-                    6
-                    if filter_option == "last_7_days"
-                    else 14 if filter_option == "last_15_days" else 29
-                )
-            else:
-                return make_response(
-                    jsonify({"success": False, "message": "Invalid option"}), 400
-                )
-            start_date = end_date - datetime.timedelta(days=filter_days)
-            start_date = start_date.replace(hour=0, minute=0, second=0, microsecond=0)
-            end_date = end_date.replace(
-                hour=23, minute=59, second=59, microsecond=999999
-            )
-            group_format = "%Y-%m-%d"
-        try:
-            match_stage = {
-                "$match": {
-                    "user": user,
-                }
-            }
-            if api_key:
-                match_stage["$match"]["api_key"] = api_key
-            pipeline = [
-                match_stage,
-                {"$unwind": "$queries"},
-                {
-                    "$match": {
-                        "queries.timestamp": {"$gte": start_date, "$lte": end_date}
-                    }
-                },
-                {
-                    "$group": {
-                        "_id": {
-                            "$dateToString": {
-                                "format": group_format,
-                                "date": "$queries.timestamp",
-                            }
-                        },
-                        "count": {"$sum": 1},
-                    }
-                },
-                {"$sort": {"_id": 1}},
-            ]
-
-            message_data = conversations_collection.aggregate(pipeline)
-
-            if filter_option == "last_hour":
-                intervals = generate_minute_range(start_date, end_date)
-            elif filter_option == "last_24_hour":
-                intervals = generate_hourly_range(start_date, end_date)
-            else:
-                intervals = generate_date_range(start_date, end_date)
-            daily_messages = {interval: 0 for interval in intervals}
-
-            for entry in message_data:
-                daily_messages[entry["_id"]] = entry["count"]
-        except Exception as err:
-            current_app.logger.error(
-                f"Error getting message analytics: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(
-            jsonify({"success": True, "messages": daily_messages}), 200
-        )
-
-
-@analytics_ns.route("/get_token_analytics")
-class GetTokenAnalytics(Resource):
-    get_token_analytics_model = api.model(
-        "GetTokenAnalyticsModel",
-        {
-            "api_key_id": fields.String(required=False, description="API Key ID"),
-            "filter_option": fields.String(
-                required=False,
-                description="Filter option for analytics",
-                default="last_30_days",
-                enum=[
-                    "last_hour",
-                    "last_24_hour",
-                    "last_7_days",
-                    "last_15_days",
-                    "last_30_days",
-                ],
-            ),
-        },
-    )
-
-    @api.expect(get_token_analytics_model)
-    @api.doc(description="Get token analytics data")
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-        api_key_id = data.get("api_key_id")
-        filter_option = data.get("filter_option", "last_30_days")
-
-        try:
-            api_key = (
-                agents_collection.find_one({"_id": ObjectId(api_key_id), "user": user})[
-                    "key"
-                ]
-                if api_key_id
-                else None
-            )
-        except Exception as err:
-            current_app.logger.error(f"Error getting API key: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)
-        end_date = datetime.datetime.now(datetime.timezone.utc)
-
-        if filter_option == "last_hour":
-            start_date = end_date - datetime.timedelta(hours=1)
-            group_format = "%Y-%m-%d %H:%M:00"
-            group_stage = {
-                "$group": {
-                    "_id": {
-                        "minute": {
-                            "$dateToString": {
-                                "format": group_format,
-                                "date": "$timestamp",
-                            }
-                        }
-                    },
-                    "total_tokens": {
-                        "$sum": {"$add": ["$prompt_tokens", "$generated_tokens"]}
-                    },
-                }
-            }
-        elif filter_option == "last_24_hour":
-            start_date = end_date - datetime.timedelta(hours=24)
-            group_format = "%Y-%m-%d %H:00"
-            group_stage = {
-                "$group": {
-                    "_id": {
-                        "hour": {
-                            "$dateToString": {
-                                "format": group_format,
-                                "date": "$timestamp",
-                            }
-                        }
-                    },
-                    "total_tokens": {
-                        "$sum": {"$add": ["$prompt_tokens", "$generated_tokens"]}
-                    },
-                }
-            }
-        else:
-            if filter_option in ["last_7_days", "last_15_days", "last_30_days"]:
-                filter_days = (
-                    6
-                    if filter_option == "last_7_days"
-                    else (14 if filter_option == "last_15_days" else 29)
-                )
-            else:
-                return make_response(
-                    jsonify({"success": False, "message": "Invalid option"}), 400
-                )
-            start_date = end_date - datetime.timedelta(days=filter_days)
-            start_date = start_date.replace(hour=0, minute=0, second=0, microsecond=0)
-            end_date = end_date.replace(
-                hour=23, minute=59, second=59, microsecond=999999
-            )
-            group_format = "%Y-%m-%d"
-            group_stage = {
-                "$group": {
-                    "_id": {
-                        "day": {
-                            "$dateToString": {
-                                "format": group_format,
-                                "date": "$timestamp",
-                            }
-                        }
-                    },
-                    "total_tokens": {
-                        "$sum": {"$add": ["$prompt_tokens", "$generated_tokens"]}
-                    },
-                }
-            }
-        try:
-            match_stage = {
-                "$match": {
-                    "user_id": user,
-                    "timestamp": {"$gte": start_date, "$lte": end_date},
-                }
-            }
-            if api_key:
-                match_stage["$match"]["api_key"] = api_key
-            token_usage_data = token_usage_collection.aggregate(
-                [
-                    match_stage,
-                    group_stage,
-                    {"$sort": {"_id": 1}},
-                ]
-            )
-
-            if filter_option == "last_hour":
-                intervals = generate_minute_range(start_date, end_date)
-            elif filter_option == "last_24_hour":
-                intervals = generate_hourly_range(start_date, end_date)
-            else:
-                intervals = generate_date_range(start_date, end_date)
-            daily_token_usage = {interval: 0 for interval in intervals}
-
-            for entry in token_usage_data:
-                if filter_option == "last_hour":
-                    daily_token_usage[entry["_id"]["minute"]] = entry["total_tokens"]
-                elif filter_option == "last_24_hour":
-                    daily_token_usage[entry["_id"]["hour"]] = entry["total_tokens"]
-                else:
-                    daily_token_usage[entry["_id"]["day"]] = entry["total_tokens"]
-        except Exception as err:
-            current_app.logger.error(
-                f"Error getting token analytics: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(
-            jsonify({"success": True, "token_usage": daily_token_usage}), 200
-        )
-
-
-@analytics_ns.route("/get_feedback_analytics")
-class GetFeedbackAnalytics(Resource):
-    get_feedback_analytics_model = api.model(
-        "GetFeedbackAnalyticsModel",
-        {
-            "api_key_id": fields.String(required=False, description="API Key ID"),
-            "filter_option": fields.String(
-                required=False,
-                description="Filter option for analytics",
-                default="last_30_days",
-                enum=[
-                    "last_hour",
-                    "last_24_hour",
-                    "last_7_days",
-                    "last_15_days",
-                    "last_30_days",
-                ],
-            ),
-        },
-    )
-
-    @api.expect(get_feedback_analytics_model)
-    @api.doc(description="Get feedback analytics data")
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-        api_key_id = data.get("api_key_id")
-        filter_option = data.get("filter_option", "last_30_days")
-
-        try:
-            api_key = (
-                agents_collection.find_one({"_id": ObjectId(api_key_id), "user": user})[
-                    "key"
-                ]
-                if api_key_id
-                else None
-            )
-        except Exception as err:
-            current_app.logger.error(f"Error getting API key: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)
-        end_date = datetime.datetime.now(datetime.timezone.utc)
-
-        if filter_option == "last_hour":
-            start_date = end_date - datetime.timedelta(hours=1)
-            group_format = "%Y-%m-%d %H:%M:00"
-            date_field = {
-                "$dateToString": {
-                    "format": group_format,
-                    "date": "$queries.feedback_timestamp",
-                }
-            }
-        elif filter_option == "last_24_hour":
-            start_date = end_date - datetime.timedelta(hours=24)
-            group_format = "%Y-%m-%d %H:00"
-            date_field = {
-                "$dateToString": {
-                    "format": group_format,
-                    "date": "$queries.feedback_timestamp",
-                }
-            }
-        else:
-            if filter_option in ["last_7_days", "last_15_days", "last_30_days"]:
-                filter_days = (
-                    6
-                    if filter_option == "last_7_days"
-                    else (14 if filter_option == "last_15_days" else 29)
-                )
-            else:
-                return make_response(
-                    jsonify({"success": False, "message": "Invalid option"}), 400
-                )
-            start_date = end_date - datetime.timedelta(days=filter_days)
-            start_date = start_date.replace(hour=0, minute=0, second=0, microsecond=0)
-            end_date = end_date.replace(
-                hour=23, minute=59, second=59, microsecond=999999
-            )
-            group_format = "%Y-%m-%d"
-            date_field = {
-                "$dateToString": {
-                    "format": group_format,
-                    "date": "$queries.feedback_timestamp",
-                }
-            }
-        try:
-            match_stage = {
-                "$match": {
-                    "queries.feedback_timestamp": {
-                        "$gte": start_date,
-                        "$lte": end_date,
-                    },
-                    "queries.feedback": {"$exists": True},
-                }
-            }
-            if api_key:
-                match_stage["$match"]["api_key"] = api_key
-            pipeline = [
-                match_stage,
-                {"$unwind": "$queries"},
-                {"$match": {"queries.feedback": {"$exists": True}}},
-                {
-                    "$group": {
-                        "_id": {"time": date_field, "feedback": "$queries.feedback"},
-                        "count": {"$sum": 1},
-                    }
-                },
-                {
-                    "$group": {
-                        "_id": "$_id.time",
-                        "positive": {
-                            "$sum": {
-                                "$cond": [
-                                    {"$eq": ["$_id.feedback", "LIKE"]},
-                                    "$count",
-                                    0,
-                                ]
-                            }
-                        },
-                        "negative": {
-                            "$sum": {
-                                "$cond": [
-                                    {"$eq": ["$_id.feedback", "DISLIKE"]},
-                                    "$count",
-                                    0,
-                                ]
-                            }
-                        },
-                    }
-                },
-                {"$sort": {"_id": 1}},
-            ]
-
-            feedback_data = conversations_collection.aggregate(pipeline)
-
-            if filter_option == "last_hour":
-                intervals = generate_minute_range(start_date, end_date)
-            elif filter_option == "last_24_hour":
-                intervals = generate_hourly_range(start_date, end_date)
-            else:
-                intervals = generate_date_range(start_date, end_date)
-            daily_feedback = {
-                interval: {"positive": 0, "negative": 0} for interval in intervals
-            }
-
-            for entry in feedback_data:
-                daily_feedback[entry["_id"]] = {
-                    "positive": entry["positive"],
-                    "negative": entry["negative"],
-                }
-        except Exception as err:
-            current_app.logger.error(
-                f"Error getting feedback analytics: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(
-            jsonify({"success": True, "feedback": daily_feedback}), 200
-        )
-
-
-@analytics_ns.route("/get_user_logs")
-class GetUserLogs(Resource):
-    get_user_logs_model = api.model(
-        "GetUserLogsModel",
-        {
-            "page": fields.Integer(
-                required=False,
-                description="Page number for pagination",
-                default=1,
-            ),
-            "api_key_id": fields.String(required=False, description="API Key ID"),
-            "page_size": fields.Integer(
-                required=False,
-                description="Number of logs per page",
-                default=10,
-            ),
-        },
-    )
-
-    @api.expect(get_user_logs_model)
-    @api.doc(description="Get user logs with pagination")
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-        page = int(data.get("page", 1))
-        api_key_id = data.get("api_key_id")
-        page_size = int(data.get("page_size", 10))
-        skip = (page - 1) * page_size
-
-        try:
-            api_key = (
-                agents_collection.find_one({"_id": ObjectId(api_key_id)})["key"]
-                if api_key_id
-                else None
-            )
-        except Exception as err:
-            current_app.logger.error(f"Error getting API key: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)
-        query = {"user": user}
-        if api_key:
-            query = {"api_key": api_key}
-        items_cursor = (
-            user_logs_collection.find(query)
-            .sort("timestamp", -1)
-            .skip(skip)
-            .limit(page_size + 1)
-        )
-        items = list(items_cursor)
-
-        results = [
-            {
-                "id": str(item.get("_id")),
-                "action": item.get("action"),
-                "level": item.get("level"),
-                "user": item.get("user"),
-                "question": item.get("question"),
-                "sources": item.get("sources"),
-                "retriever_params": item.get("retriever_params"),
-                "timestamp": item.get("timestamp"),
-            }
-            for item in items[:page_size]
-        ]
-
-        has_more = len(items) > page_size
-
-        return make_response(
-            jsonify(
-                {
-                    "success": True,
-                    "logs": results,
-                    "page": page,
-                    "page_size": page_size,
-                    "has_more": has_more,
-                }
-            ),
-            200,
-        )

application/api/user/attachments/__init__.py

@@ -1,5 +0,0 @@
-"""Attachments module."""
-
-from .routes import attachments_ns
-
-__all__ = ["attachments_ns"]

application/api/user/attachments/routes.py

@@ -1,150 +0,0 @@
-"""File attachments and media routes."""
-
-import os
-
-from bson.objectid import ObjectId
-from flask import current_app, jsonify, make_response, request
-from flask_restx import fields, Namespace, Resource
-
-from application.api import api
-from application.api.user.base import agents_collection, storage
-from application.api.user.tasks import store_attachment
-from application.core.settings import settings
-from application.tts.tts_creator import TTSCreator
-from application.utils import safe_filename
-
-
-attachments_ns = Namespace(
-    "attachments", description="File attachments and media operations", path="/api"
-)
-
-
-@attachments_ns.route("/store_attachment")
-class StoreAttachment(Resource):
-    @api.expect(
-        api.model(
-            "AttachmentModel",
-            {
-                "file": fields.Raw(required=True, description="File to upload"),
-                "api_key": fields.String(
-                    required=False, description="API key (optional)"
-                ),
-            },
-        )
-    )
-    @api.doc(
-        description="Stores a single attachment without vectorization or training. Supports user or API key authentication."
-    )
-    def post(self):
-        decoded_token = getattr(request, "decoded_token", None)
-        api_key = request.form.get("api_key") or request.args.get("api_key")
-        file = request.files.get("file")
-
-        if not file or file.filename == "":
-            return make_response(
-                jsonify({"status": "error", "message": "Missing file"}),
-                400,
-            )
-        user = None
-        if decoded_token:
-            user = safe_filename(decoded_token.get("sub"))
-        elif api_key:
-            agent = agents_collection.find_one({"key": api_key})
-            if not agent:
-                return make_response(
-                    jsonify({"success": False, "message": "Invalid API key"}), 401
-                )
-            user = safe_filename(agent.get("user"))
-        else:
-            return make_response(
-                jsonify({"success": False, "message": "Authentication required"}), 401
-            )
-        try:
-            attachment_id = ObjectId()
-            original_filename = safe_filename(os.path.basename(file.filename))
-            relative_path = f"{settings.UPLOAD_FOLDER}/{user}/attachments/{str(attachment_id)}/{original_filename}"
-
-            metadata = storage.save_file(file, relative_path)
-
-            file_info = {
-                "filename": original_filename,
-                "attachment_id": str(attachment_id),
-                "path": relative_path,
-                "metadata": metadata,
-            }
-
-            task = store_attachment.delay(file_info, user)
-
-            return make_response(
-                jsonify(
-                    {
-                        "success": True,
-                        "task_id": task.id,
-                        "message": "File uploaded successfully. Processing started.",
-                    }
-                ),
-                200,
-            )
-        except Exception as err:
-            current_app.logger.error(f"Error storing attachment: {err}", exc_info=True)
-            return make_response(jsonify({"success": False, "error": str(err)}), 400)
-
-
-@attachments_ns.route("/images/<path:image_path>")
-class ServeImage(Resource):
-    @api.doc(description="Serve an image from storage")
-    def get(self, image_path):
-        try:
-            file_obj = storage.get_file(image_path)
-            extension = image_path.split(".")[-1].lower()
-            content_type = f"image/{extension}"
-            if extension == "jpg":
-                content_type = "image/jpeg"
-            response = make_response(file_obj.read())
-            response.headers.set("Content-Type", content_type)
-            response.headers.set("Cache-Control", "max-age=86400")
-
-            return response
-        except FileNotFoundError:
-            return make_response(
-                jsonify({"success": False, "message": "Image not found"}), 404
-            )
-        except Exception as e:
-            current_app.logger.error(f"Error serving image: {e}")
-            return make_response(
-                jsonify({"success": False, "message": "Error retrieving image"}), 500
-            )
-
-
-@attachments_ns.route("/tts")
-class TextToSpeech(Resource):
-    tts_model = api.model(
-        "TextToSpeechModel",
-        {
-            "text": fields.String(
-                required=True, description="Text to be synthesized as audio"
-            ),
-        },
-    )
-
-    @api.expect(tts_model)
-    @api.doc(description="Synthesize audio speech from text")
-    def post(self):
-        data = request.get_json()
-        text = data["text"]
-        try:
-            tts_instance = TTSCreator.create_tts(settings.TTS_PROVIDER)
-            audio_base64, detected_language = tts_instance.text_to_speech(text)
-            return make_response(
-                jsonify(
-                    {
-                        "success": True,
-                        "audio_base64": audio_base64,
-                        "lang": detected_language,
-                    }
-                ),
-                200,
-            )
-        except Exception as err:
-            current_app.logger.error(f"Error synthesizing audio: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)

application/api/user/base.py

@@ -1,222 +0,0 @@
-"""
-Shared utilities, database connections, and helper functions for user API routes.
-"""
-
-import datetime
-import os
-import uuid
-from functools import wraps
-from typing import Optional, Tuple
-
-from bson.objectid import ObjectId
-from flask import current_app, jsonify, make_response, Response
-from pymongo import ReturnDocument
-from werkzeug.utils import secure_filename
-
-from application.core.mongo_db import MongoDB
-from application.core.settings import settings
-from application.storage.storage_creator import StorageCreator
-from application.vectorstore.vector_creator import VectorCreator
-
-
-storage = StorageCreator.get_storage()
-
-
-mongo = MongoDB.get_client()
-db = mongo[settings.MONGO_DB_NAME]
-
-
-conversations_collection = db["conversations"]
-sources_collection = db["sources"]
-prompts_collection = db["prompts"]
-feedback_collection = db["feedback"]
-agents_collection = db["agents"]
-token_usage_collection = db["token_usage"]
-shared_conversations_collections = db["shared_conversations"]
-users_collection = db["users"]
-user_logs_collection = db["user_logs"]
-user_tools_collection = db["user_tools"]
-attachments_collection = db["attachments"]
-
-
-try:
-    agents_collection.create_index(
-        [("shared", 1)],
-        name="shared_index",
-        background=True,
-    )
-    users_collection.create_index("user_id", unique=True)
-except Exception as e:
-    print("Error creating indexes:", e)
-current_dir = os.path.dirname(
-    os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
-)
-
-
-def generate_minute_range(start_date, end_date):
-    """Generate a dictionary with minute-level time ranges."""
-    return {
-        (start_date + datetime.timedelta(minutes=i)).strftime("%Y-%m-%d %H:%M:00"): 0
-        for i in range(int((end_date - start_date).total_seconds() // 60) + 1)
-    }
-
-
-def generate_hourly_range(start_date, end_date):
-    """Generate a dictionary with hourly time ranges."""
-    return {
-        (start_date + datetime.timedelta(hours=i)).strftime("%Y-%m-%d %H:00"): 0
-        for i in range(int((end_date - start_date).total_seconds() // 3600) + 1)
-    }
-
-
-def generate_date_range(start_date, end_date):
-    """Generate a dictionary with daily date ranges."""
-    return {
-        (start_date + datetime.timedelta(days=i)).strftime("%Y-%m-%d"): 0
-        for i in range((end_date - start_date).days + 1)
-    }
-
-
-def ensure_user_doc(user_id):
-    """
-    Ensure user document exists with proper agent preferences structure.
-
-    Args:
-        user_id: The user ID to ensure
-
-    Returns:
-        The user document
-    """
-    default_prefs = {
-        "pinned": [],
-        "shared_with_me": [],
-    }
-
-    user_doc = users_collection.find_one_and_update(
-        {"user_id": user_id},
-        {"$setOnInsert": {"agent_preferences": default_prefs}},
-        upsert=True,
-        return_document=ReturnDocument.AFTER,
-    )
-
-    prefs = user_doc.get("agent_preferences", {})
-    updates = {}
-    if "pinned" not in prefs:
-        updates["agent_preferences.pinned"] = []
-    if "shared_with_me" not in prefs:
-        updates["agent_preferences.shared_with_me"] = []
-    if updates:
-        users_collection.update_one({"user_id": user_id}, {"$set": updates})
-        user_doc = users_collection.find_one({"user_id": user_id})
-    return user_doc
-
-
-def resolve_tool_details(tool_ids):
-    """
-    Resolve tool IDs to their details.
-
-    Args:
-        tool_ids: List of tool IDs
-
-    Returns:
-        List of tool details with id, name, and display_name
-    """
-    tools = user_tools_collection.find(
-        {"_id": {"$in": [ObjectId(tid) for tid in tool_ids]}}
-    )
-    return [
-        {
-            "id": str(tool["_id"]),
-            "name": tool.get("name", ""),
-            "display_name": tool.get("displayName", tool.get("name", "")),
-        }
-        for tool in tools
-    ]
-
-
-def get_vector_store(source_id):
-    """
-    Get the Vector Store for a given source ID.
-
-    Args:
-        source_id (str): source id of the document
-
-    Returns:
-        Vector store instance
-    """
-    store = VectorCreator.create_vectorstore(
-        settings.VECTOR_STORE,
-        source_id=source_id,
-        embeddings_key=os.getenv("EMBEDDINGS_KEY"),
-    )
-    return store
-
-
-def handle_image_upload(
-    request, existing_url: str, user: str, storage, base_path: str = "attachments/"
-) -> Tuple[str, Optional[Response]]:
-    """
-    Handle image file upload from request.
-
-    Args:
-        request: Flask request object
-        existing_url: Existing image URL (fallback)
-        user: User ID
-        storage: Storage instance
-        base_path: Base path for upload
-
-    Returns:
-        Tuple of (image_url, error_response)
-    """
-    image_url = existing_url
-
-    if "image" in request.files:
-        file = request.files["image"]
-        if file.filename != "":
-            filename = secure_filename(file.filename)
-            upload_path = f"{settings.UPLOAD_FOLDER.rstrip('/')}/{user}/{base_path.rstrip('/')}/{uuid.uuid4()}_{filename}"
-            try:
-                storage.save_file(file, upload_path, storage_class="STANDARD")
-                image_url = upload_path
-            except Exception as e:
-                current_app.logger.error(f"Error uploading image: {e}")
-                return None, make_response(
-                    jsonify({"success": False, "message": "Image upload failed"}),
-                    400,
-                )
-    return image_url, None
-
-
-def require_agent(func):
-    """
-    Decorator to require valid agent webhook token.
-
-    Args:
-        func: Function to decorate
-
-    Returns:
-        Wrapped function
-    """
-
-    @wraps(func)
-    def wrapper(*args, **kwargs):
-        webhook_token = kwargs.get("webhook_token")
-        if not webhook_token:
-            return make_response(
-                jsonify({"success": False, "message": "Webhook token missing"}), 400
-            )
-        agent = agents_collection.find_one(
-            {"incoming_webhook_token": webhook_token}, {"_id": 1}
-        )
-        if not agent:
-            current_app.logger.warning(
-                f"Webhook attempt with invalid token: {webhook_token}"
-            )
-            return make_response(
-                jsonify({"success": False, "message": "Agent not found"}), 404
-            )
-        kwargs["agent"] = agent
-        kwargs["agent_id_str"] = str(agent["_id"])
-        return func(*args, **kwargs)
-
-    return wrapper

application/api/user/conversations/__init__.py

@@ -1,5 +0,0 @@
-"""Conversation management module."""
-
-from .routes import conversations_ns
-
-__all__ = ["conversations_ns"]

application/api/user/conversations/routes.py

@@ -1,280 +0,0 @@
-"""Conversation management routes."""
-
-import datetime
-
-from bson.objectid import ObjectId
-from flask import current_app, jsonify, make_response, request
-from flask_restx import fields, Namespace, Resource
-
-from application.api import api
-from application.api.user.base import attachments_collection, conversations_collection
-from application.utils import check_required_fields
-
-conversations_ns = Namespace(
-    "conversations", description="Conversation management operations", path="/api"
-)
-
-
-@conversations_ns.route("/delete_conversation")
-class DeleteConversation(Resource):
-    @api.doc(
-        description="Deletes a conversation by ID",
-        params={"id": "The ID of the conversation to delete"},
-    )
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        conversation_id = request.args.get("id")
-        if not conversation_id:
-            return make_response(
-                jsonify({"success": False, "message": "ID is required"}), 400
-            )
-        try:
-            conversations_collection.delete_one(
-                {"_id": ObjectId(conversation_id), "user": decoded_token["sub"]}
-            )
-        except Exception as err:
-            current_app.logger.error(
-                f"Error deleting conversation: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"success": True}), 200)
-
-
-@conversations_ns.route("/delete_all_conversations")
-class DeleteAllConversations(Resource):
-    @api.doc(
-        description="Deletes all conversations for a specific user",
-    )
-    def get(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user_id = decoded_token.get("sub")
-        try:
-            conversations_collection.delete_many({"user": user_id})
-        except Exception as err:
-            current_app.logger.error(
-                f"Error deleting all conversations: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"success": True}), 200)
-
-
-@conversations_ns.route("/get_conversations")
-class GetConversations(Resource):
-    @api.doc(
-        description="Retrieve a list of the latest 30 conversations (excluding API key conversations)",
-    )
-    def get(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        try:
-            conversations = (
-                conversations_collection.find(
-                    {
-                        "$or": [
-                            {"api_key": {"$exists": False}},
-                            {"agent_id": {"$exists": True}},
-                        ],
-                        "user": decoded_token.get("sub"),
-                    }
-                )
-                .sort("date", -1)
-                .limit(30)
-            )
-
-            list_conversations = [
-                {
-                    "id": str(conversation["_id"]),
-                    "name": conversation["name"],
-                    "agent_id": conversation.get("agent_id", None),
-                    "is_shared_usage": conversation.get("is_shared_usage", False),
-                    "shared_token": conversation.get("shared_token", None),
-                }
-                for conversation in conversations
-            ]
-        except Exception as err:
-            current_app.logger.error(
-                f"Error retrieving conversations: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify(list_conversations), 200)
-
-
-@conversations_ns.route("/get_single_conversation")
-class GetSingleConversation(Resource):
-    @api.doc(
-        description="Retrieve a single conversation by ID",
-        params={"id": "The conversation ID"},
-    )
-    def get(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        conversation_id = request.args.get("id")
-        if not conversation_id:
-            return make_response(
-                jsonify({"success": False, "message": "ID is required"}), 400
-            )
-        try:
-            conversation = conversations_collection.find_one(
-                {"_id": ObjectId(conversation_id), "user": decoded_token.get("sub")}
-            )
-            if not conversation:
-                return make_response(jsonify({"status": "not found"}), 404)
-            # Process queries to include attachment names
-
-            queries = conversation["queries"]
-            for query in queries:
-                if "attachments" in query and query["attachments"]:
-                    attachment_details = []
-                    for attachment_id in query["attachments"]:
-                        try:
-                            attachment = attachments_collection.find_one(
-                                {"_id": ObjectId(attachment_id)}
-                            )
-                            if attachment:
-                                attachment_details.append(
-                                    {
-                                        "id": str(attachment["_id"]),
-                                        "fileName": attachment.get(
-                                            "filename", "Unknown file"
-                                        ),
-                                    }
-                                )
-                        except Exception as e:
-                            current_app.logger.error(
-                                f"Error retrieving attachment {attachment_id}: {e}",
-                                exc_info=True,
-                            )
-                    query["attachments"] = attachment_details
-        except Exception as err:
-            current_app.logger.error(
-                f"Error retrieving conversation: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-        data = {
-            "queries": queries,
-            "agent_id": conversation.get("agent_id"),
-            "is_shared_usage": conversation.get("is_shared_usage", False),
-            "shared_token": conversation.get("shared_token", None),
-        }
-        return make_response(jsonify(data), 200)
-
-
-@conversations_ns.route("/update_conversation_name")
-class UpdateConversationName(Resource):
-    @api.expect(
-        api.model(
-            "UpdateConversationModel",
-            {
-                "id": fields.String(required=True, description="Conversation ID"),
-                "name": fields.String(
-                    required=True, description="New name of the conversation"
-                ),
-            },
-        )
-    )
-    @api.doc(
-        description="Updates the name of a conversation",
-    )
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        data = request.get_json()
-        required_fields = ["id", "name"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        try:
-            conversations_collection.update_one(
-                {"_id": ObjectId(data["id"]), "user": decoded_token.get("sub")},
-                {"$set": {"name": data["name"]}},
-            )
-        except Exception as err:
-            current_app.logger.error(
-                f"Error updating conversation name: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"success": True}), 200)
-
-
-@conversations_ns.route("/feedback")
-class SubmitFeedback(Resource):
-    @api.expect(
-        api.model(
-            "FeedbackModel",
-            {
-                "question": fields.String(
-                    required=False, description="The user question"
-                ),
-                "answer": fields.String(required=False, description="The AI answer"),
-                "feedback": fields.String(required=True, description="User feedback"),
-                "question_index": fields.Integer(
-                    required=True,
-                    description="The question number in that particular conversation",
-                ),
-                "conversation_id": fields.String(
-                    required=True, description="id of the particular conversation"
-                ),
-                "api_key": fields.String(description="Optional API key"),
-            },
-        )
-    )
-    @api.doc(
-        description="Submit feedback for a conversation",
-    )
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        data = request.get_json()
-        required_fields = ["feedback", "conversation_id", "question_index"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        try:
-            if data["feedback"] is None:
-                # Remove feedback and feedback_timestamp if feedback is null
-
-                conversations_collection.update_one(
-                    {
-                        "_id": ObjectId(data["conversation_id"]),
-                        "user": decoded_token.get("sub"),
-                        f"queries.{data['question_index']}": {"$exists": True},
-                    },
-                    {
-                        "$unset": {
-                            f"queries.{data['question_index']}.feedback": "",
-                            f"queries.{data['question_index']}.feedback_timestamp": "",
-                        }
-                    },
-                )
-            else:
-                # Set feedback and feedback_timestamp if feedback has a value
-
-                conversations_collection.update_one(
-                    {
-                        "_id": ObjectId(data["conversation_id"]),
-                        "user": decoded_token.get("sub"),
-                        f"queries.{data['question_index']}": {"$exists": True},
-                    },
-                    {
-                        "$set": {
-                            f"queries.{data['question_index']}.feedback": data[
-                                "feedback"
-                            ],
-                            f"queries.{data['question_index']}.feedback_timestamp": datetime.datetime.now(
-                                datetime.timezone.utc
-                            ),
-                        }
-                    },
-                )
-        except Exception as err:
-            current_app.logger.error(f"Error submitting feedback: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"success": True}), 200)

application/api/user/prompts/__init__.py

@@ -1,5 +0,0 @@
-"""Prompts module."""
-
-from .routes import prompts_ns
-
-__all__ = ["prompts_ns"]

application/api/user/prompts/routes.py

@@ -1,191 +0,0 @@
-"""Prompt management routes."""
-
-import os
-
-from bson.objectid import ObjectId
-from flask import current_app, jsonify, make_response, request
-from flask_restx import fields, Namespace, Resource
-
-from application.api import api
-from application.api.user.base import current_dir, prompts_collection
-from application.utils import check_required_fields
-
-prompts_ns = Namespace(
-    "prompts", description="Prompt management operations", path="/api"
-)
-
-
-@prompts_ns.route("/create_prompt")
-class CreatePrompt(Resource):
-    create_prompt_model = api.model(
-        "CreatePromptModel",
-        {
-            "content": fields.String(
-                required=True, description="Content of the prompt"
-            ),
-            "name": fields.String(required=True, description="Name of the prompt"),
-        },
-    )
-
-    @api.expect(create_prompt_model)
-    @api.doc(description="Create a new prompt")
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        data = request.get_json()
-        required_fields = ["content", "name"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        user = decoded_token.get("sub")
-        try:
-
-            resp = prompts_collection.insert_one(
-                {
-                    "name": data["name"],
-                    "content": data["content"],
-                    "user": user,
-                }
-            )
-            new_id = str(resp.inserted_id)
-        except Exception as err:
-            current_app.logger.error(f"Error creating prompt: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"id": new_id}), 200)
-
-
-@prompts_ns.route("/get_prompts")
-class GetPrompts(Resource):
-    @api.doc(description="Get all prompts for the user")
-    def get(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        try:
-            prompts = prompts_collection.find({"user": user})
-            list_prompts = [
-                {"id": "default", "name": "default", "type": "public"},
-                {"id": "creative", "name": "creative", "type": "public"},
-                {"id": "strict", "name": "strict", "type": "public"},
-            ]
-
-            for prompt in prompts:
-                list_prompts.append(
-                    {
-                        "id": str(prompt["_id"]),
-                        "name": prompt["name"],
-                        "type": "private",
-                    }
-                )
-        except Exception as err:
-            current_app.logger.error(f"Error retrieving prompts: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify(list_prompts), 200)
-
-
-@prompts_ns.route("/get_single_prompt")
-class GetSinglePrompt(Resource):
-    @api.doc(params={"id": "ID of the prompt"}, description="Get a single prompt by ID")
-    def get(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        prompt_id = request.args.get("id")
-        if not prompt_id:
-            return make_response(
-                jsonify({"success": False, "message": "ID is required"}), 400
-            )
-        try:
-            if prompt_id == "default":
-                with open(
-                    os.path.join(current_dir, "prompts", "chat_combine_default.txt"),
-                    "r",
-                ) as f:
-                    chat_combine_template = f.read()
-                return make_response(jsonify({"content": chat_combine_template}), 200)
-            elif prompt_id == "creative":
-                with open(
-                    os.path.join(current_dir, "prompts", "chat_combine_creative.txt"),
-                    "r",
-                ) as f:
-                    chat_reduce_creative = f.read()
-                return make_response(jsonify({"content": chat_reduce_creative}), 200)
-            elif prompt_id == "strict":
-                with open(
-                    os.path.join(current_dir, "prompts", "chat_combine_strict.txt"), "r"
-                ) as f:
-                    chat_reduce_strict = f.read()
-                return make_response(jsonify({"content": chat_reduce_strict}), 200)
-            prompt = prompts_collection.find_one(
-                {"_id": ObjectId(prompt_id), "user": user}
-            )
-        except Exception as err:
-            current_app.logger.error(f"Error retrieving prompt: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"content": prompt["content"]}), 200)
-
-
-@prompts_ns.route("/delete_prompt")
-class DeletePrompt(Resource):
-    delete_prompt_model = api.model(
-        "DeletePromptModel",
-        {"id": fields.String(required=True, description="Prompt ID to delete")},
-    )
-
-    @api.expect(delete_prompt_model)
-    @api.doc(description="Delete a prompt by ID")
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-        required_fields = ["id"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        try:
-            prompts_collection.delete_one({"_id": ObjectId(data["id"]), "user": user})
-        except Exception as err:
-            current_app.logger.error(f"Error deleting prompt: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"success": True}), 200)
-
-
-@prompts_ns.route("/update_prompt")
-class UpdatePrompt(Resource):
-    update_prompt_model = api.model(
-        "UpdatePromptModel",
-        {
-            "id": fields.String(required=True, description="Prompt ID to update"),
-            "name": fields.String(required=True, description="New name of the prompt"),
-            "content": fields.String(
-                required=True, description="New content of the prompt"
-            ),
-        },
-    )
-
-    @api.expect(update_prompt_model)
-    @api.doc(description="Update an existing prompt")
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-        required_fields = ["id", "name", "content"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        try:
-            prompts_collection.update_one(
-                {"_id": ObjectId(data["id"]), "user": user},
-                {"$set": {"name": data["name"], "content": data["content"]}},
-            )
-        except Exception as err:
-            current_app.logger.error(f"Error updating prompt: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"success": True}), 200)

application/api/user/sharing/__init__.py

@@ -1,5 +0,0 @@
-"""Sharing module."""
-
-from .routes import sharing_ns
-
-__all__ = ["sharing_ns"]

application/api/user/sharing/routes.py

@@ -1,301 +0,0 @@
-"""Conversation sharing routes."""
-
-import uuid
-
-from bson.binary import Binary, UuidRepresentation
-from bson.dbref import DBRef
-from bson.objectid import ObjectId
-from flask import current_app, jsonify, make_response, request
-from flask_restx import fields, inputs, Namespace, Resource
-
-from application.api import api
-from application.api.user.base import (
-    agents_collection,
-    attachments_collection,
-    conversations_collection,
-    db,
-    shared_conversations_collections,
-)
-from application.utils import check_required_fields
-
-sharing_ns = Namespace(
-    "sharing", description="Conversation sharing operations", path="/api"
-)
-
-
-@sharing_ns.route("/share")
-class ShareConversation(Resource):
-    share_conversation_model = api.model(
-        "ShareConversationModel",
-        {
-            "conversation_id": fields.String(
-                required=True, description="Conversation ID"
-            ),
-            "user": fields.String(description="User ID (optional)"),
-            "prompt_id": fields.String(description="Prompt ID (optional)"),
-            "chunks": fields.Integer(description="Chunks count (optional)"),
-        },
-    )
-
-    @api.expect(share_conversation_model)
-    @api.doc(description="Share a conversation")
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-        required_fields = ["conversation_id"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        is_promptable = request.args.get("isPromptable", type=inputs.boolean)
-        if is_promptable is None:
-            return make_response(
-                jsonify({"success": False, "message": "isPromptable is required"}), 400
-            )
-        conversation_id = data["conversation_id"]
-
-        try:
-            conversation = conversations_collection.find_one(
-                {"_id": ObjectId(conversation_id)}
-            )
-            if conversation is None:
-                return make_response(
-                    jsonify(
-                        {
-                            "status": "error",
-                            "message": "Conversation does not exist",
-                        }
-                    ),
-                    404,
-                )
-            current_n_queries = len(conversation["queries"])
-            explicit_binary = Binary.from_uuid(
-                uuid.uuid4(), UuidRepresentation.STANDARD
-            )
-
-            if is_promptable:
-                prompt_id = data.get("prompt_id", "default")
-                chunks = data.get("chunks", "2")
-
-                name = conversation["name"] + "(shared)"
-                new_api_key_data = {
-                    "prompt_id": prompt_id,
-                    "chunks": chunks,
-                    "user": user,
-                }
-
-                if "source" in data and ObjectId.is_valid(data["source"]):
-                    new_api_key_data["source"] = DBRef(
-                        "sources", ObjectId(data["source"])
-                    )
-                if "retriever" in data:
-                    new_api_key_data["retriever"] = data["retriever"]
-                pre_existing_api_document = agents_collection.find_one(new_api_key_data)
-                if pre_existing_api_document:
-                    api_uuid = pre_existing_api_document["key"]
-                    pre_existing = shared_conversations_collections.find_one(
-                        {
-                            "conversation_id": DBRef(
-                                "conversations", ObjectId(conversation_id)
-                            ),
-                            "isPromptable": is_promptable,
-                            "first_n_queries": current_n_queries,
-                            "user": user,
-                            "api_key": api_uuid,
-                        }
-                    )
-                    if pre_existing is not None:
-                        return make_response(
-                            jsonify(
-                                {
-                                    "success": True,
-                                    "identifier": str(pre_existing["uuid"].as_uuid()),
-                                }
-                            ),
-                            200,
-                        )
-                    else:
-                        shared_conversations_collections.insert_one(
-                            {
-                                "uuid": explicit_binary,
-                                "conversation_id": {
-                                    "$ref": "conversations",
-                                    "$id": ObjectId(conversation_id),
-                                },
-                                "isPromptable": is_promptable,
-                                "first_n_queries": current_n_queries,
-                                "user": user,
-                                "api_key": api_uuid,
-                            }
-                        )
-                        return make_response(
-                            jsonify(
-                                {
-                                    "success": True,
-                                    "identifier": str(explicit_binary.as_uuid()),
-                                }
-                            ),
-                            201,
-                        )
-                else:
-                    api_uuid = str(uuid.uuid4())
-                    new_api_key_data["key"] = api_uuid
-                    new_api_key_data["name"] = name
-
-                    if "source" in data and ObjectId.is_valid(data["source"]):
-                        new_api_key_data["source"] = DBRef(
-                            "sources", ObjectId(data["source"])
-                        )
-                    if "retriever" in data:
-                        new_api_key_data["retriever"] = data["retriever"]
-                    agents_collection.insert_one(new_api_key_data)
-                    shared_conversations_collections.insert_one(
-                        {
-                            "uuid": explicit_binary,
-                            "conversation_id": {
-                                "$ref": "conversations",
-                                "$id": ObjectId(conversation_id),
-                            },
-                            "isPromptable": is_promptable,
-                            "first_n_queries": current_n_queries,
-                            "user": user,
-                            "api_key": api_uuid,
-                        }
-                    )
-                    return make_response(
-                        jsonify(
-                            {
-                                "success": True,
-                                "identifier": str(explicit_binary.as_uuid()),
-                            }
-                        ),
-                        201,
-                    )
-            pre_existing = shared_conversations_collections.find_one(
-                {
-                    "conversation_id": DBRef(
-                        "conversations", ObjectId(conversation_id)
-                    ),
-                    "isPromptable": is_promptable,
-                    "first_n_queries": current_n_queries,
-                    "user": user,
-                }
-            )
-            if pre_existing is not None:
-                return make_response(
-                    jsonify(
-                        {
-                            "success": True,
-                            "identifier": str(pre_existing["uuid"].as_uuid()),
-                        }
-                    ),
-                    200,
-                )
-            else:
-                shared_conversations_collections.insert_one(
-                    {
-                        "uuid": explicit_binary,
-                        "conversation_id": {
-                            "$ref": "conversations",
-                            "$id": ObjectId(conversation_id),
-                        },
-                        "isPromptable": is_promptable,
-                        "first_n_queries": current_n_queries,
-                        "user": user,
-                    }
-                )
-                return make_response(
-                    jsonify(
-                        {"success": True, "identifier": str(explicit_binary.as_uuid())}
-                    ),
-                    201,
-                )
-        except Exception as err:
-            current_app.logger.error(
-                f"Error sharing conversation: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-
-
-@sharing_ns.route("/shared_conversation/<string:identifier>")
-class GetPubliclySharedConversations(Resource):
-    @api.doc(description="Get publicly shared conversations by identifier")
-    def get(self, identifier: str):
-        try:
-            query_uuid = Binary.from_uuid(
-                uuid.UUID(identifier), UuidRepresentation.STANDARD
-            )
-            shared = shared_conversations_collections.find_one({"uuid": query_uuid})
-            conversation_queries = []
-
-            if (
-                shared
-                and "conversation_id" in shared
-                and isinstance(shared["conversation_id"], DBRef)
-            ):
-                conversation_ref = shared["conversation_id"]
-                conversation = db.dereference(conversation_ref)
-                if conversation is None:
-                    return make_response(
-                        jsonify(
-                            {
-                                "success": False,
-                                "error": "might have broken url or the conversation does not exist",
-                            }
-                        ),
-                        404,
-                    )
-                conversation_queries = conversation["queries"][
-                    : (shared["first_n_queries"])
-                ]
-
-                for query in conversation_queries:
-                    if "attachments" in query and query["attachments"]:
-                        attachment_details = []
-                        for attachment_id in query["attachments"]:
-                            try:
-                                attachment = attachments_collection.find_one(
-                                    {"_id": ObjectId(attachment_id)}
-                                )
-                                if attachment:
-                                    attachment_details.append(
-                                        {
-                                            "id": str(attachment["_id"]),
-                                            "fileName": attachment.get(
-                                                "filename", "Unknown file"
-                                            ),
-                                        }
-                                    )
-                            except Exception as e:
-                                current_app.logger.error(
-                                    f"Error retrieving attachment {attachment_id}: {e}",
-                                    exc_info=True,
-                                )
-                        query["attachments"] = attachment_details
-            else:
-                return make_response(
-                    jsonify(
-                        {
-                            "success": False,
-                            "error": "might have broken url or the conversation does not exist",
-                        }
-                    ),
-                    404,
-                )
-            date = conversation["_id"].generation_time.isoformat()
-            res = {
-                "success": True,
-                "queries": conversation_queries,
-                "title": conversation["name"],
-                "timestamp": date,
-            }
-            if shared["isPromptable"] and "api_key" in shared:
-                res["api_key"] = shared["api_key"]
-            return make_response(jsonify(res), 200)
-        except Exception as err:
-            current_app.logger.error(
-                f"Error getting shared conversation: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)

application/api/user/sources/__init__.py

@@ -1,7 +0,0 @@
-"""Sources module."""
-
-from .chunks import sources_chunks_ns
-from .routes import sources_ns
-from .upload import sources_upload_ns
-
-__all__ = ["sources_ns", "sources_chunks_ns", "sources_upload_ns"]

application/api/user/sources/chunks.py

@@ -1,278 +0,0 @@
-"""Source document management chunk management."""
-
-from bson.objectid import ObjectId
-from flask import current_app, jsonify, make_response, request
-from flask_restx import fields, Namespace, Resource
-
-from application.api import api
-from application.api.user.base import get_vector_store, sources_collection
-from application.utils import check_required_fields, num_tokens_from_string
-
-sources_chunks_ns = Namespace(
-    "sources", description="Source document management operations", path="/api"
-)
-
-
-@sources_chunks_ns.route("/get_chunks")
-class GetChunks(Resource):
-    @api.doc(
-        description="Retrieves chunks from a document, optionally filtered by file path and search term",
-        params={
-            "id": "The document ID",
-            "page": "Page number for pagination",
-            "per_page": "Number of chunks per page",
-            "path": "Optional: Filter chunks by relative file path",
-            "search": "Optional: Search term to filter chunks by title or content",
-        },
-    )
-    def get(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        doc_id = request.args.get("id")
-        page = int(request.args.get("page", 1))
-        per_page = int(request.args.get("per_page", 10))
-        path = request.args.get("path")
-        search_term = request.args.get("search", "").strip().lower()
-
-        if not ObjectId.is_valid(doc_id):
-            return make_response(jsonify({"error": "Invalid doc_id"}), 400)
-        doc = sources_collection.find_one({"_id": ObjectId(doc_id), "user": user})
-        if not doc:
-            return make_response(
-                jsonify({"error": "Document not found or access denied"}), 404
-            )
-        try:
-            store = get_vector_store(doc_id)
-            chunks = store.get_chunks()
-
-            filtered_chunks = []
-            for chunk in chunks:
-                metadata = chunk.get("metadata", {})
-
-                # Filter by path if provided
-
-                if path:
-                    chunk_source = metadata.get("source", "")
-                    # Check if the chunk's source matches the requested path
-
-                    if not chunk_source or not chunk_source.endswith(path):
-                        continue
-                # Filter by search term if provided
-
-                if search_term:
-                    text_match = search_term in chunk.get("text", "").lower()
-                    title_match = search_term in metadata.get("title", "").lower()
-
-                    if not (text_match or title_match):
-                        continue
-                filtered_chunks.append(chunk)
-            chunks = filtered_chunks
-
-            total_chunks = len(chunks)
-            start = (page - 1) * per_page
-            end = start + per_page
-            paginated_chunks = chunks[start:end]
-
-            return make_response(
-                jsonify(
-                    {
-                        "page": page,
-                        "per_page": per_page,
-                        "total": total_chunks,
-                        "chunks": paginated_chunks,
-                        "path": path if path else None,
-                        "search": search_term if search_term else None,
-                    }
-                ),
-                200,
-            )
-        except Exception as e:
-            current_app.logger.error(f"Error getting chunks: {e}", exc_info=True)
-            return make_response(jsonify({"success": False}), 500)
-
-
-@sources_chunks_ns.route("/add_chunk")
-class AddChunk(Resource):
-    @api.expect(
-        api.model(
-            "AddChunkModel",
-            {
-                "id": fields.String(required=True, description="Document ID"),
-                "text": fields.String(required=True, description="Text of the chunk"),
-                "metadata": fields.Raw(
-                    required=False,
-                    description="Metadata associated with the chunk",
-                ),
-            },
-        )
-    )
-    @api.doc(
-        description="Adds a new chunk to the document",
-    )
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-        required_fields = ["id", "text"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        doc_id = data.get("id")
-        text = data.get("text")
-        metadata = data.get("metadata", {})
-        token_count = num_tokens_from_string(text)
-        metadata["token_count"] = token_count
-
-        if not ObjectId.is_valid(doc_id):
-            return make_response(jsonify({"error": "Invalid doc_id"}), 400)
-        doc = sources_collection.find_one({"_id": ObjectId(doc_id), "user": user})
-        if not doc:
-            return make_response(
-                jsonify({"error": "Document not found or access denied"}), 404
-            )
-        try:
-            store = get_vector_store(doc_id)
-            chunk_id = store.add_chunk(text, metadata)
-            return make_response(
-                jsonify({"message": "Chunk added successfully", "chunk_id": chunk_id}),
-                201,
-            )
-        except Exception as e:
-            current_app.logger.error(f"Error adding chunk: {e}", exc_info=True)
-            return make_response(jsonify({"success": False}), 500)
-
-
-@sources_chunks_ns.route("/delete_chunk")
-class DeleteChunk(Resource):
-    @api.doc(
-        description="Deletes a specific chunk from the document.",
-        params={"id": "The document ID", "chunk_id": "The ID of the chunk to delete"},
-    )
-    def delete(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        doc_id = request.args.get("id")
-        chunk_id = request.args.get("chunk_id")
-
-        if not ObjectId.is_valid(doc_id):
-            return make_response(jsonify({"error": "Invalid doc_id"}), 400)
-        doc = sources_collection.find_one({"_id": ObjectId(doc_id), "user": user})
-        if not doc:
-            return make_response(
-                jsonify({"error": "Document not found or access denied"}), 404
-            )
-        try:
-            store = get_vector_store(doc_id)
-            deleted = store.delete_chunk(chunk_id)
-            if deleted:
-                return make_response(
-                    jsonify({"message": "Chunk deleted successfully"}), 200
-                )
-            else:
-                return make_response(
-                    jsonify({"message": "Chunk not found or could not be deleted"}),
-                    404,
-                )
-        except Exception as e:
-            current_app.logger.error(f"Error deleting chunk: {e}", exc_info=True)
-            return make_response(jsonify({"success": False}), 500)
-
-
-@sources_chunks_ns.route("/update_chunk")
-class UpdateChunk(Resource):
-    @api.expect(
-        api.model(
-            "UpdateChunkModel",
-            {
-                "id": fields.String(required=True, description="Document ID"),
-                "chunk_id": fields.String(
-                    required=True, description="Chunk ID to update"
-                ),
-                "text": fields.String(
-                    required=False, description="New text of the chunk"
-                ),
-                "metadata": fields.Raw(
-                    required=False,
-                    description="Updated metadata associated with the chunk",
-                ),
-            },
-        )
-    )
-    @api.doc(
-        description="Updates an existing chunk in the document.",
-    )
-    def put(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-        required_fields = ["id", "chunk_id"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        doc_id = data.get("id")
-        chunk_id = data.get("chunk_id")
-        text = data.get("text")
-        metadata = data.get("metadata")
-
-        if text is not None:
-            token_count = num_tokens_from_string(text)
-            if metadata is None:
-                metadata = {}
-            metadata["token_count"] = token_count
-        if not ObjectId.is_valid(doc_id):
-            return make_response(jsonify({"error": "Invalid doc_id"}), 400)
-        doc = sources_collection.find_one({"_id": ObjectId(doc_id), "user": user})
-        if not doc:
-            return make_response(
-                jsonify({"error": "Document not found or access denied"}), 404
-            )
-        try:
-            store = get_vector_store(doc_id)
-
-            chunks = store.get_chunks()
-            existing_chunk = next((c for c in chunks if c["doc_id"] == chunk_id), None)
-            if not existing_chunk:
-                return make_response(jsonify({"error": "Chunk not found"}), 404)
-            new_text = text if text is not None else existing_chunk["text"]
-
-            if metadata is not None:
-                new_metadata = existing_chunk["metadata"].copy()
-                new_metadata.update(metadata)
-            else:
-                new_metadata = existing_chunk["metadata"].copy()
-            if text is not None:
-                new_metadata["token_count"] = num_tokens_from_string(new_text)
-            try:
-                new_chunk_id = store.add_chunk(new_text, new_metadata)
-
-                deleted = store.delete_chunk(chunk_id)
-                if not deleted:
-                    current_app.logger.warning(
-                        f"Failed to delete old chunk {chunk_id}, but new chunk {new_chunk_id} was created"
-                    )
-                return make_response(
-                    jsonify(
-                        {
-                            "message": "Chunk updated successfully",
-                            "chunk_id": new_chunk_id,
-                            "original_chunk_id": chunk_id,
-                        }
-                    ),
-                    200,
-                )
-            except Exception as add_error:
-                current_app.logger.error(f"Failed to add updated chunk: {add_error}")
-                return make_response(
-                    jsonify({"error": "Failed to update chunk - addition failed"}), 500
-                )
-        except Exception as e:
-            current_app.logger.error(f"Error updating chunk: {e}", exc_info=True)
-            return make_response(jsonify({"success": False}), 500)

application/api/user/sources/routes.py

@@ -1,323 +0,0 @@
-"""Source document management routes."""
-
-import json
-import math
-
-from bson.objectid import ObjectId
-from flask import current_app, jsonify, make_response, redirect, request
-from flask_restx import fields, Namespace, Resource
-
-from application.api import api
-from application.api.user.base import sources_collection
-from application.core.settings import settings
-from application.storage.storage_creator import StorageCreator
-from application.utils import check_required_fields
-from application.vectorstore.vector_creator import VectorCreator
-
-
-sources_ns = Namespace(
-    "sources", description="Source document management operations", path="/api"
-)
-
-
-@sources_ns.route("/sources")
-class CombinedJson(Resource):
-    @api.doc(description="Provide JSON file with combined available indexes")
-    def get(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = [
-            {
-                "name": "Default",
-                "date": "default",
-                "model": settings.EMBEDDINGS_NAME,
-                "location": "remote",
-                "tokens": "",
-                "retriever": "classic",
-            }
-        ]
-
-        try:
-            for index in sources_collection.find({"user": user}).sort("date", -1):
-                data.append(
-                    {
-                        "id": str(index["_id"]),
-                        "name": index.get("name"),
-                        "date": index.get("date"),
-                        "model": settings.EMBEDDINGS_NAME,
-                        "location": "local",
-                        "tokens": index.get("tokens", ""),
-                        "retriever": index.get("retriever", "classic"),
-                        "syncFrequency": index.get("sync_frequency", ""),
-                        "is_nested": bool(index.get("directory_structure")),
-                        "type": index.get(
-                            "type", "file"
-                        ),  # Add type field with default "file"
-                    }
-                )
-        except Exception as err:
-            current_app.logger.error(f"Error retrieving sources: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify(data), 200)
-
-
-@sources_ns.route("/sources/paginated")
-class PaginatedSources(Resource):
-    @api.doc(description="Get document with pagination, sorting and filtering")
-    def get(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        sort_field = request.args.get("sort", "date")  # Default to 'date'
-        sort_order = request.args.get("order", "desc")  # Default to 'desc'
-        page = int(request.args.get("page", 1))  # Default to 1
-        rows_per_page = int(request.args.get("rows", 10))  # Default to 10
-        # add .strip() to remove leading and trailing whitespaces
-
-        search_term = request.args.get(
-            "search", ""
-        ).strip()  # add search for filter documents
-
-        # Prepare query for filtering
-
-        query = {"user": user}
-        if search_term:
-            query["name"] = {
-                "$regex": search_term,
-                "$options": "i",  # using case-insensitive search
-            }
-        total_documents = sources_collection.count_documents(query)
-        total_pages = max(1, math.ceil(total_documents / rows_per_page))
-        page = min(
-            max(1, page), total_pages
-        )  # add this to make sure page inbound is within the range
-        sort_order = 1 if sort_order == "asc" else -1
-        skip = (page - 1) * rows_per_page
-
-        try:
-            documents = (
-                sources_collection.find(query)
-                .sort(sort_field, sort_order)
-                .skip(skip)
-                .limit(rows_per_page)
-            )
-
-            paginated_docs = []
-            for doc in documents:
-                doc_data = {
-                    "id": str(doc["_id"]),
-                    "name": doc.get("name", ""),
-                    "date": doc.get("date", ""),
-                    "model": settings.EMBEDDINGS_NAME,
-                    "location": "local",
-                    "tokens": doc.get("tokens", ""),
-                    "retriever": doc.get("retriever", "classic"),
-                    "syncFrequency": doc.get("sync_frequency", ""),
-                    "isNested": bool(doc.get("directory_structure")),
-                    "type": doc.get("type", "file"),
-                }
-                paginated_docs.append(doc_data)
-            response = {
-                "total": total_documents,
-                "totalPages": total_pages,
-                "currentPage": page,
-                "paginated": paginated_docs,
-            }
-            return make_response(jsonify(response), 200)
-        except Exception as err:
-            current_app.logger.error(
-                f"Error retrieving paginated sources: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-
-
-@sources_ns.route("/delete_by_ids")
-class DeleteByIds(Resource):
-    @api.doc(
-        description="Deletes documents from the vector store by IDs",
-        params={"path": "Comma-separated list of IDs"},
-    )
-    def get(self):
-        ids = request.args.get("path")
-        if not ids:
-            return make_response(
-                jsonify({"success": False, "message": "Missing required fields"}), 400
-            )
-        try:
-            result = sources_collection.delete_index(ids=ids)
-            if result:
-                return make_response(jsonify({"success": True}), 200)
-        except Exception as err:
-            current_app.logger.error(f"Error deleting indexes: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"success": False}), 400)
-
-
-@sources_ns.route("/delete_old")
-class DeleteOldIndexes(Resource):
-    @api.doc(
-        description="Deletes old indexes and associated files",
-        params={"source_id": "The source ID to delete"},
-    )
-    def get(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        source_id = request.args.get("source_id")
-        if not source_id:
-            return make_response(
-                jsonify({"success": False, "message": "Missing required fields"}), 400
-            )
-        doc = sources_collection.find_one(
-            {"_id": ObjectId(source_id), "user": decoded_token.get("sub")}
-        )
-        if not doc:
-            return make_response(jsonify({"status": "not found"}), 404)
-        storage = StorageCreator.get_storage()
-
-        try:
-            # Delete vector index
-
-            if settings.VECTOR_STORE == "faiss":
-                index_path = f"indexes/{str(doc['_id'])}"
-                if storage.file_exists(f"{index_path}/index.faiss"):
-                    storage.delete_file(f"{index_path}/index.faiss")
-                if storage.file_exists(f"{index_path}/index.pkl"):
-                    storage.delete_file(f"{index_path}/index.pkl")
-            else:
-                vectorstore = VectorCreator.create_vectorstore(
-                    settings.VECTOR_STORE, source_id=str(doc["_id"])
-                )
-                vectorstore.delete_index()
-            if "file_path" in doc and doc["file_path"]:
-                file_path = doc["file_path"]
-                if storage.is_directory(file_path):
-                    files = storage.list_files(file_path)
-                    for f in files:
-                        storage.delete_file(f)
-                else:
-                    storage.delete_file(file_path)
-        except FileNotFoundError:
-            pass
-        except Exception as err:
-            current_app.logger.error(
-                f"Error deleting files and indexes: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-        sources_collection.delete_one({"_id": ObjectId(source_id)})
-        return make_response(jsonify({"success": True}), 200)
-
-
-@sources_ns.route("/combine")
-class RedirectToSources(Resource):
-    @api.doc(
-        description="Redirects /api/combine to /api/sources for backward compatibility"
-    )
-    def get(self):
-        return redirect("/api/sources", code=301)
-
-
-@sources_ns.route("/manage_sync")
-class ManageSync(Resource):
-    manage_sync_model = api.model(
-        "ManageSyncModel",
-        {
-            "source_id": fields.String(required=True, description="Source ID"),
-            "sync_frequency": fields.String(
-                required=True,
-                description="Sync frequency (never, daily, weekly, monthly)",
-            ),
-        },
-    )
-
-    @api.expect(manage_sync_model)
-    @api.doc(description="Manage sync frequency for sources")
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-        required_fields = ["source_id", "sync_frequency"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        source_id = data["source_id"]
-        sync_frequency = data["sync_frequency"]
-
-        if sync_frequency not in ["never", "daily", "weekly", "monthly"]:
-            return make_response(
-                jsonify({"success": False, "message": "Invalid frequency"}), 400
-            )
-        update_data = {"$set": {"sync_frequency": sync_frequency}}
-        try:
-            sources_collection.update_one(
-                {
-                    "_id": ObjectId(source_id),
-                    "user": user,
-                },
-                update_data,
-            )
-        except Exception as err:
-            current_app.logger.error(
-                f"Error updating sync frequency: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"success": True}), 200)
-
-
-@sources_ns.route("/directory_structure")
-class DirectoryStructure(Resource):
-    @api.doc(
-        description="Get the directory structure for a document",
-        params={"id": "The document ID"},
-    )
-    def get(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        doc_id = request.args.get("id")
-
-        if not doc_id:
-            return make_response(jsonify({"error": "Document ID is required"}), 400)
-        if not ObjectId.is_valid(doc_id):
-            return make_response(jsonify({"error": "Invalid document ID"}), 400)
-        try:
-            doc = sources_collection.find_one({"_id": ObjectId(doc_id), "user": user})
-            if not doc:
-                return make_response(
-                    jsonify({"error": "Document not found or access denied"}), 404
-                )
-            directory_structure = doc.get("directory_structure", {})
-            base_path = doc.get("file_path", "")
-
-            provider = None
-            remote_data = doc.get("remote_data")
-            try:
-                if isinstance(remote_data, str) and remote_data:
-                    remote_data_obj = json.loads(remote_data)
-                    provider = remote_data_obj.get("provider")
-            except Exception as e:
-                current_app.logger.warning(
-                    f"Failed to parse remote_data for doc {doc_id}: {e}"
-                )
-            return make_response(
-                jsonify(
-                    {
-                        "success": True,
-                        "directory_structure": directory_structure,
-                        "base_path": base_path,
-                        "provider": provider,
-                    }
-                ),
-                200,
-            )
-        except Exception as e:
-            current_app.logger.error(
-                f"Error retrieving directory structure: {e}", exc_info=True
-            )
-            return make_response(jsonify({"success": False, "error": str(e)}), 500)

application/api/user/sources/upload.py

@@ -1,583 +0,0 @@
-"""Source document management upload functionality."""
-
-import json
-import os
-import tempfile
-import zipfile
-
-from bson.objectid import ObjectId
-from flask import current_app, jsonify, make_response, request
-from flask_restx import fields, Namespace, Resource
-
-from application.api import api
-from application.api.user.base import sources_collection
-from application.api.user.tasks import ingest, ingest_connector_task, ingest_remote
-from application.core.settings import settings
-from application.parser.connectors.connector_creator import ConnectorCreator
-from application.storage.storage_creator import StorageCreator
-from application.utils import check_required_fields, safe_filename
-
-
-sources_upload_ns = Namespace(
-    "sources", description="Source document management operations", path="/api"
-)
-
-
-@sources_upload_ns.route("/upload")
-class UploadFile(Resource):
-    @api.expect(
-        api.model(
-            "UploadModel",
-            {
-                "user": fields.String(required=True, description="User ID"),
-                "name": fields.String(required=True, description="Job name"),
-                "file": fields.Raw(required=True, description="File(s) to upload"),
-            },
-        )
-    )
-    @api.doc(
-        description="Uploads a file to be vectorized and indexed",
-    )
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        data = request.form
-        files = request.files.getlist("file")
-        required_fields = ["user", "name"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields or not files or all(file.filename == "" for file in files):
-            return make_response(
-                jsonify(
-                    {
-                        "status": "error",
-                        "message": "Missing required fields or files",
-                    }
-                ),
-                400,
-            )
-        user = decoded_token.get("sub")
-        job_name = request.form["name"]
-
-        # Create safe versions for filesystem operations
-
-        safe_user = safe_filename(user)
-        dir_name = safe_filename(job_name)
-        base_path = f"{settings.UPLOAD_FOLDER}/{safe_user}/{dir_name}"
-
-        try:
-            storage = StorageCreator.get_storage()
-
-            for file in files:
-                original_filename = file.filename
-                safe_file = safe_filename(original_filename)
-
-                with tempfile.TemporaryDirectory() as temp_dir:
-                    temp_file_path = os.path.join(temp_dir, safe_file)
-                    file.save(temp_file_path)
-
-                    if zipfile.is_zipfile(temp_file_path):
-                        try:
-                            with zipfile.ZipFile(temp_file_path, "r") as zip_ref:
-                                zip_ref.extractall(path=temp_dir)
-
-                                # Walk through extracted files and upload them
-
-                                for root, _, files in os.walk(temp_dir):
-                                    for extracted_file in files:
-                                        if (
-                                            os.path.join(root, extracted_file)
-                                            == temp_file_path
-                                        ):
-                                            continue
-                                        rel_path = os.path.relpath(
-                                            os.path.join(root, extracted_file), temp_dir
-                                        )
-                                        storage_path = f"{base_path}/{rel_path}"
-
-                                        with open(
-                                            os.path.join(root, extracted_file), "rb"
-                                        ) as f:
-                                            storage.save_file(f, storage_path)
-                        except Exception as e:
-                            current_app.logger.error(
-                                f"Error extracting zip: {e}", exc_info=True
-                            )
-                            # If zip extraction fails, save the original zip file
-
-                            file_path = f"{base_path}/{safe_file}"
-                            with open(temp_file_path, "rb") as f:
-                                storage.save_file(f, file_path)
-                    else:
-                        # For non-zip files, save directly
-
-                        file_path = f"{base_path}/{safe_file}"
-                        with open(temp_file_path, "rb") as f:
-                            storage.save_file(f, file_path)
-            task = ingest.delay(
-                settings.UPLOAD_FOLDER,
-                [
-                    ".rst",
-                    ".md",
-                    ".pdf",
-                    ".txt",
-                    ".docx",
-                    ".csv",
-                    ".epub",
-                    ".html",
-                    ".mdx",
-                    ".json",
-                    ".xlsx",
-                    ".pptx",
-                    ".png",
-                    ".jpg",
-                    ".jpeg",
-                ],
-                job_name,
-                user,
-                file_path=base_path,
-                filename=dir_name,
-            )
-        except Exception as err:
-            current_app.logger.error(f"Error uploading file: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"success": True, "task_id": task.id}), 200)
-
-
-@sources_upload_ns.route("/remote")
-class UploadRemote(Resource):
-    @api.expect(
-        api.model(
-            "RemoteUploadModel",
-            {
-                "user": fields.String(required=True, description="User ID"),
-                "source": fields.String(
-                    required=True, description="Source of the data"
-                ),
-                "name": fields.String(required=True, description="Job name"),
-                "data": fields.String(required=True, description="Data to process"),
-                "repo_url": fields.String(description="GitHub repository URL"),
-            },
-        )
-    )
-    @api.doc(
-        description="Uploads remote source for vectorization",
-    )
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        data = request.form
-        required_fields = ["user", "source", "name", "data"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        try:
-            config = json.loads(data["data"])
-            source_data = None
-
-            if data["source"] == "github":
-                source_data = config.get("repo_url")
-            elif data["source"] in ["crawler", "url"]:
-                source_data = config.get("url")
-            elif data["source"] == "reddit":
-                source_data = config
-            elif data["source"] in ConnectorCreator.get_supported_connectors():
-                session_token = config.get("session_token")
-                if not session_token:
-                    return make_response(
-                        jsonify(
-                            {
-                                "success": False,
-                                "error": f"Missing session_token in {data['source']} configuration",
-                            }
-                        ),
-                        400,
-                    )
-                # Process file_ids
-
-                file_ids = config.get("file_ids", [])
-                if isinstance(file_ids, str):
-                    file_ids = [id.strip() for id in file_ids.split(",") if id.strip()]
-                elif not isinstance(file_ids, list):
-                    file_ids = []
-                # Process folder_ids
-
-                folder_ids = config.get("folder_ids", [])
-                if isinstance(folder_ids, str):
-                    folder_ids = [
-                        id.strip() for id in folder_ids.split(",") if id.strip()
-                    ]
-                elif not isinstance(folder_ids, list):
-                    folder_ids = []
-                config["file_ids"] = file_ids
-                config["folder_ids"] = folder_ids
-
-                task = ingest_connector_task.delay(
-                    job_name=data["name"],
-                    user=decoded_token.get("sub"),
-                    source_type=data["source"],
-                    session_token=session_token,
-                    file_ids=file_ids,
-                    folder_ids=folder_ids,
-                    recursive=config.get("recursive", False),
-                    retriever=config.get("retriever", "classic"),
-                )
-                return make_response(
-                    jsonify({"success": True, "task_id": task.id}), 200
-                )
-            task = ingest_remote.delay(
-                source_data=source_data,
-                job_name=data["name"],
-                user=decoded_token.get("sub"),
-                loader=data["source"],
-            )
-        except Exception as err:
-            current_app.logger.error(
-                f"Error uploading remote source: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"success": True, "task_id": task.id}), 200)
-
-
-@sources_upload_ns.route("/manage_source_files")
-class ManageSourceFiles(Resource):
-    @api.expect(
-        api.model(
-            "ManageSourceFilesModel",
-            {
-                "source_id": fields.String(
-                    required=True, description="Source ID to modify"
-                ),
-                "operation": fields.String(
-                    required=True,
-                    description="Operation: 'add', 'remove', or 'remove_directory'",
-                ),
-                "file_paths": fields.List(
-                    fields.String,
-                    required=False,
-                    description="File paths to remove (for remove operation)",
-                ),
-                "directory_path": fields.String(
-                    required=False,
-                    description="Directory path to remove (for remove_directory operation)",
-                ),
-                "file": fields.Raw(
-                    required=False, description="Files to add (for add operation)"
-                ),
-                "parent_dir": fields.String(
-                    required=False,
-                    description="Parent directory path relative to source root",
-                ),
-            },
-        )
-    )
-    @api.doc(
-        description="Add files, remove files, or remove directories from an existing source",
-    )
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(
-                jsonify({"success": False, "message": "Unauthorized"}), 401
-            )
-        user = decoded_token.get("sub")
-        source_id = request.form.get("source_id")
-        operation = request.form.get("operation")
-
-        if not source_id or not operation:
-            return make_response(
-                jsonify(
-                    {
-                        "success": False,
-                        "message": "source_id and operation are required",
-                    }
-                ),
-                400,
-            )
-        if operation not in ["add", "remove", "remove_directory"]:
-            return make_response(
-                jsonify(
-                    {
-                        "success": False,
-                        "message": "operation must be 'add', 'remove', or 'remove_directory'",
-                    }
-                ),
-                400,
-            )
-        try:
-            ObjectId(source_id)
-        except Exception:
-            return make_response(
-                jsonify({"success": False, "message": "Invalid source ID format"}), 400
-            )
-        try:
-            source = sources_collection.find_one(
-                {"_id": ObjectId(source_id), "user": user}
-            )
-            if not source:
-                return make_response(
-                    jsonify(
-                        {
-                            "success": False,
-                            "message": "Source not found or access denied",
-                        }
-                    ),
-                    404,
-                )
-        except Exception as err:
-            current_app.logger.error(f"Error finding source: {err}", exc_info=True)
-            return make_response(
-                jsonify({"success": False, "message": "Database error"}), 500
-            )
-        try:
-            storage = StorageCreator.get_storage()
-            source_file_path = source.get("file_path", "")
-            parent_dir = request.form.get("parent_dir", "")
-
-            if parent_dir and (parent_dir.startswith("/") or ".." in parent_dir):
-                return make_response(
-                    jsonify(
-                        {"success": False, "message": "Invalid parent directory path"}
-                    ),
-                    400,
-                )
-            if operation == "add":
-                files = request.files.getlist("file")
-                if not files or all(file.filename == "" for file in files):
-                    return make_response(
-                        jsonify(
-                            {
-                                "success": False,
-                                "message": "No files provided for add operation",
-                            }
-                        ),
-                        400,
-                    )
-                added_files = []
-
-                target_dir = source_file_path
-                if parent_dir:
-                    target_dir = f"{source_file_path}/{parent_dir}"
-                for file in files:
-                    if file.filename:
-                        safe_filename_str = safe_filename(file.filename)
-                        file_path = f"{target_dir}/{safe_filename_str}"
-
-                        # Save file to storage
-
-                        storage.save_file(file, file_path)
-                        added_files.append(safe_filename_str)
-                # Trigger re-ingestion pipeline
-
-                from application.api.user.tasks import reingest_source_task
-
-                task = reingest_source_task.delay(source_id=source_id, user=user)
-
-                return make_response(
-                    jsonify(
-                        {
-                            "success": True,
-                            "message": f"Added {len(added_files)} files",
-                            "added_files": added_files,
-                            "parent_dir": parent_dir,
-                            "reingest_task_id": task.id,
-                        }
-                    ),
-                    200,
-                )
-            elif operation == "remove":
-                file_paths_str = request.form.get("file_paths")
-                if not file_paths_str:
-                    return make_response(
-                        jsonify(
-                            {
-                                "success": False,
-                                "message": "file_paths required for remove operation",
-                            }
-                        ),
-                        400,
-                    )
-                try:
-                    file_paths = (
-                        json.loads(file_paths_str)
-                        if isinstance(file_paths_str, str)
-                        else file_paths_str
-                    )
-                except Exception:
-                    return make_response(
-                        jsonify(
-                            {"success": False, "message": "Invalid file_paths format"}
-                        ),
-                        400,
-                    )
-                # Remove files from storage and directory structure
-
-                removed_files = []
-                for file_path in file_paths:
-                    full_path = f"{source_file_path}/{file_path}"
-
-                    # Remove from storage
-
-                    if storage.file_exists(full_path):
-                        storage.delete_file(full_path)
-                        removed_files.append(file_path)
-                # Trigger re-ingestion pipeline
-
-                from application.api.user.tasks import reingest_source_task
-
-                task = reingest_source_task.delay(source_id=source_id, user=user)
-
-                return make_response(
-                    jsonify(
-                        {
-                            "success": True,
-                            "message": f"Removed {len(removed_files)} files",
-                            "removed_files": removed_files,
-                            "reingest_task_id": task.id,
-                        }
-                    ),
-                    200,
-                )
-            elif operation == "remove_directory":
-                directory_path = request.form.get("directory_path")
-                if not directory_path:
-                    return make_response(
-                        jsonify(
-                            {
-                                "success": False,
-                                "message": "directory_path required for remove_directory operation",
-                            }
-                        ),
-                        400,
-                    )
-                # Validate directory path (prevent path traversal)
-
-                if directory_path.startswith("/") or ".." in directory_path:
-                    current_app.logger.warning(
-                        f"Invalid directory path attempted for removal. "
-                        f"User: {user}, Source ID: {source_id}, Directory path: {directory_path}"
-                    )
-                    return make_response(
-                        jsonify(
-                            {"success": False, "message": "Invalid directory path"}
-                        ),
-                        400,
-                    )
-                full_directory_path = (
-                    f"{source_file_path}/{directory_path}"
-                    if directory_path
-                    else source_file_path
-                )
-
-                if not storage.is_directory(full_directory_path):
-                    current_app.logger.warning(
-                        f"Directory not found or is not a directory for removal. "
-                        f"User: {user}, Source ID: {source_id}, Directory path: {directory_path}, "
-                        f"Full path: {full_directory_path}"
-                    )
-                    return make_response(
-                        jsonify(
-                            {
-                                "success": False,
-                                "message": "Directory not found or is not a directory",
-                            }
-                        ),
-                        404,
-                    )
-                success = storage.remove_directory(full_directory_path)
-
-                if not success:
-                    current_app.logger.error(
-                        f"Failed to remove directory from storage. "
-                        f"User: {user}, Source ID: {source_id}, Directory path: {directory_path}, "
-                        f"Full path: {full_directory_path}"
-                    )
-                    return make_response(
-                        jsonify(
-                            {"success": False, "message": "Failed to remove directory"}
-                        ),
-                        500,
-                    )
-                current_app.logger.info(
-                    f"Successfully removed directory. "
-                    f"User: {user}, Source ID: {source_id}, Directory path: {directory_path}, "
-                    f"Full path: {full_directory_path}"
-                )
-
-                # Trigger re-ingestion pipeline
-
-                from application.api.user.tasks import reingest_source_task
-
-                task = reingest_source_task.delay(source_id=source_id, user=user)
-
-                return make_response(
-                    jsonify(
-                        {
-                            "success": True,
-                            "message": f"Successfully removed directory: {directory_path}",
-                            "removed_directory": directory_path,
-                            "reingest_task_id": task.id,
-                        }
-                    ),
-                    200,
-                )
-        except Exception as err:
-            error_context = f"operation={operation}, user={user}, source_id={source_id}"
-            if operation == "remove_directory":
-                directory_path = request.form.get("directory_path", "")
-                error_context += f", directory_path={directory_path}"
-            elif operation == "remove":
-                file_paths_str = request.form.get("file_paths", "")
-                error_context += f", file_paths={file_paths_str}"
-            elif operation == "add":
-                parent_dir = request.form.get("parent_dir", "")
-                error_context += f", parent_dir={parent_dir}"
-            current_app.logger.error(
-                f"Error managing source files: {err} ({error_context})", exc_info=True
-            )
-            return make_response(
-                jsonify({"success": False, "message": "Operation failed"}), 500
-            )
-
-
-@sources_upload_ns.route("/task_status")
-class TaskStatus(Resource):
-    task_status_model = api.model(
-        "TaskStatusModel",
-        {"task_id": fields.String(required=True, description="Task ID")},
-    )
-
-    @api.expect(task_status_model)
-    @api.doc(description="Get celery job status")
-    def get(self):
-        task_id = request.args.get("task_id")
-        if not task_id:
-            return make_response(
-                jsonify({"success": False, "message": "Task ID is required"}), 400
-            )
-        try:
-            from application.celery_init import celery
-
-            task = celery.AsyncResult(task_id)
-            task_meta = task.info
-            print(f"Task status: {task.status}")
-
-            if task.status == "PENDING":
-                inspect = celery.control.inspect()
-                active_workers = inspect.ping()
-                if not active_workers:
-                    raise ConnectionError("Service unavailable")
-
-            if not isinstance(
-                task_meta, (dict, list, str, int, float, bool, type(None))
-            ):
-                task_meta = str(task_meta)  # Convert to a string representation
-        except ConnectionError as err:
-            return make_response(
-                jsonify({"success": False, "message": str(err)}), 503
-            )
-        except Exception as err:
-            current_app.logger.error(f"Error getting task status: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"status": task.status, "result": task_meta}), 200)

application/api/user/tasks.py

@@ -5,8 +5,6 @@ from application.worker import (
     agent_webhook_worker,
     attachment_worker,
     ingest_worker,
-    mcp_oauth,
-    mcp_oauth_status,
     remote_worker,
     sync_worker,
 )
@@ -27,7 +25,6 @@ def ingest_remote(self, source_data, job_name, user, loader):
 @celery.task(bind=True)
 def reingest_source_task(self, source_id, user):
     from application.worker import reingest_source_worker
-
     resp = reingest_source_worker(self, source_id, user)
     return resp
 
@@ -63,10 +60,9 @@ def ingest_connector_task(
     retriever="classic",
     operation_mode="upload",
     doc_id=None,
-    sync_frequency="never",
+    sync_frequency="never"
 ):
     from application.worker import ingest_connector
-
     resp = ingest_connector(
         self,
         job_name,
@@ -79,7 +75,7 @@ def ingest_connector_task(
         retriever=retriever,
         operation_mode=operation_mode,
         doc_id=doc_id,
-        sync_frequency=sync_frequency,
+        sync_frequency=sync_frequency
     )
     return resp
 
@@ -98,15 +94,3 @@ def setup_periodic_tasks(sender, **kwargs):
         timedelta(days=30),
         schedule_syncs.s("monthly"),
     )
-
-
-@celery.task(bind=True)
-def mcp_oauth_task(self, config, user):
-    resp = mcp_oauth(self, config, user)
-    return resp
-
-
-@celery.task(bind=True)
-def mcp_oauth_status_task(self, task_id):
-    resp = mcp_oauth_status(self, task_id)
-    return resp

application/api/user/tools/__init__.py

@@ -1,6 +0,0 @@
-"""Tools module."""
-
-from .mcp import tools_mcp_ns
-from .routes import tools_ns
-
-__all__ = ["tools_ns", "tools_mcp_ns"]

application/api/user/tools/mcp.py

@@ -1,333 +0,0 @@
-"""Tool management MCP server integration."""
-
-import json
-from email.quoprimime import unquote
-
-from bson.objectid import ObjectId
-from flask import current_app, jsonify, make_response, redirect, request
-from flask_restx import fields, Namespace, Resource
-
-from application.agents.tools.mcp_tool import MCPOAuthManager, MCPTool
-from application.api import api
-from application.api.user.base import user_tools_collection
-from application.cache import get_redis_instance
-from application.security.encryption import encrypt_credentials
-from application.utils import check_required_fields
-
-tools_mcp_ns = Namespace("tools", description="Tool management operations", path="/api")
-
-
-@tools_mcp_ns.route("/mcp_server/test")
-class TestMCPServerConfig(Resource):
-    @api.expect(
-        api.model(
-            "MCPServerTestModel",
-            {
-                "config": fields.Raw(
-                    required=True, description="MCP server configuration to test"
-                ),
-            },
-        )
-    )
-    @api.doc(description="Test MCP server connection with provided configuration")
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-
-        required_fields = ["config"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        try:
-            config = data["config"]
-
-            auth_credentials = {}
-            auth_type = config.get("auth_type", "none")
-
-            if auth_type == "api_key" and "api_key" in config:
-                auth_credentials["api_key"] = config["api_key"]
-                if "api_key_header" in config:
-                    auth_credentials["api_key_header"] = config["api_key_header"]
-            elif auth_type == "bearer" and "bearer_token" in config:
-                auth_credentials["bearer_token"] = config["bearer_token"]
-            elif auth_type == "basic":
-                if "username" in config:
-                    auth_credentials["username"] = config["username"]
-                if "password" in config:
-                    auth_credentials["password"] = config["password"]
-            test_config = config.copy()
-            test_config["auth_credentials"] = auth_credentials
-
-            mcp_tool = MCPTool(config=test_config, user_id=user)
-            result = mcp_tool.test_connection()
-
-            return make_response(jsonify(result), 200)
-        except Exception as e:
-            current_app.logger.error(f"Error testing MCP server: {e}", exc_info=True)
-            return make_response(
-                jsonify(
-                    {"success": False, "error": f"Connection test failed: {str(e)}"}
-                ),
-                500,
-            )
-
-
-@tools_mcp_ns.route("/mcp_server/save")
-class MCPServerSave(Resource):
-    @api.expect(
-        api.model(
-            "MCPServerSaveModel",
-            {
-                "id": fields.String(
-                    required=False, description="Tool ID for updates (optional)"
-                ),
-                "displayName": fields.String(
-                    required=True, description="Display name for the MCP server"
-                ),
-                "config": fields.Raw(
-                    required=True, description="MCP server configuration"
-                ),
-                "status": fields.Boolean(
-                    required=False, default=True, description="Tool status"
-                ),
-            },
-        )
-    )
-    @api.doc(description="Create or update MCP server with automatic tool discovery")
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-
-        required_fields = ["displayName", "config"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        try:
-            config = data["config"]
-
-            auth_credentials = {}
-            auth_type = config.get("auth_type", "none")
-            if auth_type == "api_key":
-                if "api_key" in config and config["api_key"]:
-                    auth_credentials["api_key"] = config["api_key"]
-                if "api_key_header" in config:
-                    auth_credentials["api_key_header"] = config["api_key_header"]
-            elif auth_type == "bearer":
-                if "bearer_token" in config and config["bearer_token"]:
-                    auth_credentials["bearer_token"] = config["bearer_token"]
-            elif auth_type == "basic":
-                if "username" in config and config["username"]:
-                    auth_credentials["username"] = config["username"]
-                if "password" in config and config["password"]:
-                    auth_credentials["password"] = config["password"]
-            mcp_config = config.copy()
-            mcp_config["auth_credentials"] = auth_credentials
-
-            if auth_type == "oauth":
-                if not config.get("oauth_task_id"):
-                    return make_response(
-                        jsonify(
-                            {
-                                "success": False,
-                                "error": "Connection not authorized. Please complete the OAuth authorization first.",
-                            }
-                        ),
-                        400,
-                    )
-                redis_client = get_redis_instance()
-                manager = MCPOAuthManager(redis_client)
-                result = manager.get_oauth_status(config["oauth_task_id"])
-                if not result.get("status") == "completed":
-                    return make_response(
-                        jsonify(
-                            {
-                                "success": False,
-                                "error": "OAuth failed or not completed. Please try authorizing again.",
-                            }
-                        ),
-                        400,
-                    )
-                actions_metadata = result.get("tools", [])
-            elif auth_type == "none" or auth_credentials:
-                mcp_tool = MCPTool(config=mcp_config, user_id=user)
-                mcp_tool.discover_tools()
-                actions_metadata = mcp_tool.get_actions_metadata()
-            else:
-                raise Exception(
-                    "No valid credentials provided for the selected authentication type"
-                )
-            storage_config = config.copy()
-            if auth_credentials:
-                encrypted_credentials_string = encrypt_credentials(
-                    auth_credentials, user
-                )
-                storage_config["encrypted_credentials"] = encrypted_credentials_string
-            for field in [
-                "api_key",
-                "bearer_token",
-                "username",
-                "password",
-                "api_key_header",
-            ]:
-                storage_config.pop(field, None)
-            transformed_actions = []
-            for action in actions_metadata:
-                action["active"] = True
-                if "parameters" in action:
-                    if "properties" in action["parameters"]:
-                        for param_name, param_details in action["parameters"][
-                            "properties"
-                        ].items():
-                            param_details["filled_by_llm"] = True
-                            param_details["value"] = ""
-                transformed_actions.append(action)
-            tool_data = {
-                "name": "mcp_tool",
-                "displayName": data["displayName"],
-                "customName": data["displayName"],
-                "description": f"MCP Server: {storage_config.get('server_url', 'Unknown')}",
-                "config": storage_config,
-                "actions": transformed_actions,
-                "status": data.get("status", True),
-                "user": user,
-            }
-
-            tool_id = data.get("id")
-            if tool_id:
-                result = user_tools_collection.update_one(
-                    {"_id": ObjectId(tool_id), "user": user, "name": "mcp_tool"},
-                    {"$set": {k: v for k, v in tool_data.items() if k != "user"}},
-                )
-                if result.matched_count == 0:
-                    return make_response(
-                        jsonify(
-                            {
-                                "success": False,
-                                "error": "Tool not found or access denied",
-                            }
-                        ),
-                        404,
-                    )
-                response_data = {
-                    "success": True,
-                    "id": tool_id,
-                    "message": f"MCP server updated successfully! Discovered {len(transformed_actions)} tools.",
-                    "tools_count": len(transformed_actions),
-                }
-            else:
-                result = user_tools_collection.insert_one(tool_data)
-                tool_id = str(result.inserted_id)
-                response_data = {
-                    "success": True,
-                    "id": tool_id,
-                    "message": f"MCP server created successfully! Discovered {len(transformed_actions)} tools.",
-                    "tools_count": len(transformed_actions),
-                }
-            return make_response(jsonify(response_data), 200)
-        except Exception as e:
-            current_app.logger.error(f"Error saving MCP server: {e}", exc_info=True)
-            return make_response(
-                jsonify(
-                    {"success": False, "error": f"Failed to save MCP server: {str(e)}"}
-                ),
-                500,
-            )
-
-
-@tools_mcp_ns.route("/mcp_server/callback")
-class MCPOAuthCallback(Resource):
-    @api.expect(
-        api.model(
-            "MCPServerCallbackModel",
-            {
-                "code": fields.String(required=True, description="Authorization code"),
-                "state": fields.String(required=True, description="State parameter"),
-                "error": fields.String(
-                    required=False, description="Error message (if any)"
-                ),
-            },
-        )
-    )
-    @api.doc(
-        description="Handle OAuth callback by providing the authorization code and state"
-    )
-    def get(self):
-        code = request.args.get("code")
-        state = request.args.get("state")
-        error = request.args.get("error")
-
-        if error:
-            return redirect(
-                f"/api/connectors/callback-status?status=error&message=OAuth+error:+{error}.+Please+try+again+and+make+sure+to+grant+all+requested+permissions,+including+offline+access.&provider=mcp_tool"
-            )
-        if not code or not state:
-            return redirect(
-                "/api/connectors/callback-status?status=error&message=Authorization+code+or+state+not+provided.+Please+complete+the+authorization+process+and+make+sure+to+grant+offline+access.&provider=mcp_tool"
-            )
-        try:
-            redis_client = get_redis_instance()
-            if not redis_client:
-                return redirect(
-                    "/api/connectors/callback-status?status=error&message=Internal+server+error:+Redis+not+available.&provider=mcp_tool"
-                )
-            code = unquote(code)
-            manager = MCPOAuthManager(redis_client)
-            success = manager.handle_oauth_callback(state, code, error)
-            if success:
-                return redirect(
-                    "/api/connectors/callback-status?status=success&message=Authorization+code+received+successfully.+You+can+close+this+window.&provider=mcp_tool"
-                )
-            else:
-                return redirect(
-                    "/api/connectors/callback-status?status=error&message=OAuth+callback+failed.&provider=mcp_tool"
-                )
-        except Exception as e:
-            current_app.logger.error(
-                f"Error handling MCP OAuth callback: {str(e)}", exc_info=True
-            )
-            return redirect(
-                f"/api/connectors/callback-status?status=error&message=Internal+server+error:+{str(e)}.&provider=mcp_tool"
-            )
-
-
-@tools_mcp_ns.route("/mcp_server/oauth_status/<string:task_id>")
-class MCPOAuthStatus(Resource):
-    def get(self, task_id):
-        """
-        Get current status of OAuth flow.
-        Frontend should poll this endpoint periodically.
-        """
-        try:
-            redis_client = get_redis_instance()
-            status_key = f"mcp_oauth_status:{task_id}"
-            status_data = redis_client.get(status_key)
-
-            if status_data:
-                status = json.loads(status_data)
-                return make_response(
-                    jsonify({"success": True, "task_id": task_id, **status})
-                )
-            else:
-                return make_response(
-                    jsonify(
-                        {
-                            "success": False,
-                            "error": "Task not found or expired",
-                            "task_id": task_id,
-                        }
-                    ),
-                    404,
-                )
-        except Exception as e:
-            current_app.logger.error(
-                f"Error getting OAuth status for task {task_id}: {str(e)}"
-            )
-            return make_response(
-                jsonify({"success": False, "error": str(e), "task_id": task_id}), 500
-            )

application/api/user/tools/routes.py

@@ -1,415 +0,0 @@
-"""Tool management routes."""
-
-from bson.objectid import ObjectId
-from flask import current_app, jsonify, make_response, request
-from flask_restx import fields, Namespace, Resource
-
-from application.agents.tools.tool_manager import ToolManager
-from application.api import api
-from application.api.user.base import user_tools_collection
-from application.security.encryption import decrypt_credentials, encrypt_credentials
-from application.utils import check_required_fields, validate_function_name
-
-tool_config = {}
-tool_manager = ToolManager(config=tool_config)
-
-
-tools_ns = Namespace("tools", description="Tool management operations", path="/api")
-
-
-@tools_ns.route("/available_tools")
-class AvailableTools(Resource):
-    @api.doc(description="Get available tools for a user")
-    def get(self):
-        try:
-            tools_metadata = []
-            for tool_name, tool_instance in tool_manager.tools.items():
-                doc = tool_instance.__doc__.strip()
-                lines = doc.split("\n", 1)
-                name = lines[0].strip()
-                description = lines[1].strip() if len(lines) > 1 else ""
-                tools_metadata.append(
-                    {
-                        "name": tool_name,
-                        "displayName": name,
-                        "description": description,
-                        "configRequirements": tool_instance.get_config_requirements(),
-                    }
-                )
-        except Exception as err:
-            current_app.logger.error(
-                f"Error getting available tools: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"success": True, "data": tools_metadata}), 200)
-
-
-@tools_ns.route("/get_tools")
-class GetTools(Resource):
-    @api.doc(description="Get tools created by a user")
-    def get(self):
-        try:
-            decoded_token = request.decoded_token
-            if not decoded_token:
-                return make_response(jsonify({"success": False}), 401)
-            user = decoded_token.get("sub")
-            tools = user_tools_collection.find({"user": user})
-            user_tools = []
-            for tool in tools:
-                tool["id"] = str(tool["_id"])
-                tool.pop("_id")
-                user_tools.append(tool)
-        except Exception as err:
-            current_app.logger.error(f"Error getting user tools: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"success": True, "tools": user_tools}), 200)
-
-
-@tools_ns.route("/create_tool")
-class CreateTool(Resource):
-    @api.expect(
-        api.model(
-            "CreateToolModel",
-            {
-                "name": fields.String(required=True, description="Name of the tool"),
-                "displayName": fields.String(
-                    required=True, description="Display name for the tool"
-                ),
-                "description": fields.String(
-                    required=True, description="Tool description"
-                ),
-                "config": fields.Raw(
-                    required=True, description="Configuration of the tool"
-                ),
-                "customName": fields.String(
-                    required=False, description="Custom name for the tool"
-                ),
-                "status": fields.Boolean(
-                    required=True, description="Status of the tool"
-                ),
-            },
-        )
-    )
-    @api.doc(description="Create a new tool")
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-        required_fields = [
-            "name",
-            "displayName",
-            "description",
-            "config",
-            "status",
-        ]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        try:
-            tool_instance = tool_manager.tools.get(data["name"])
-            if not tool_instance:
-                return make_response(
-                    jsonify({"success": False, "message": "Tool not found"}), 404
-                )
-            actions_metadata = tool_instance.get_actions_metadata()
-            transformed_actions = []
-            for action in actions_metadata:
-                action["active"] = True
-                if "parameters" in action:
-                    if "properties" in action["parameters"]:
-                        for param_name, param_details in action["parameters"][
-                            "properties"
-                        ].items():
-                            param_details["filled_by_llm"] = True
-                            param_details["value"] = ""
-                transformed_actions.append(action)
-        except Exception as err:
-            current_app.logger.error(
-                f"Error getting tool actions: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-        try:
-            new_tool = {
-                "user": user,
-                "name": data["name"],
-                "displayName": data["displayName"],
-                "description": data["description"],
-                "customName": data.get("customName", ""),
-                "actions": transformed_actions,
-                "config": data["config"],
-                "status": data["status"],
-            }
-            resp = user_tools_collection.insert_one(new_tool)
-            new_id = str(resp.inserted_id)
-        except Exception as err:
-            current_app.logger.error(f"Error creating tool: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"id": new_id}), 200)
-
-
-@tools_ns.route("/update_tool")
-class UpdateTool(Resource):
-    @api.expect(
-        api.model(
-            "UpdateToolModel",
-            {
-                "id": fields.String(required=True, description="Tool ID"),
-                "name": fields.String(description="Name of the tool"),
-                "displayName": fields.String(description="Display name for the tool"),
-                "customName": fields.String(description="Custom name for the tool"),
-                "description": fields.String(description="Tool description"),
-                "config": fields.Raw(description="Configuration of the tool"),
-                "actions": fields.List(
-                    fields.Raw, description="Actions the tool can perform"
-                ),
-                "status": fields.Boolean(description="Status of the tool"),
-            },
-        )
-    )
-    @api.doc(description="Update a tool by ID")
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-        required_fields = ["id"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        try:
-            update_data = {}
-            if "name" in data:
-                update_data["name"] = data["name"]
-            if "displayName" in data:
-                update_data["displayName"] = data["displayName"]
-            if "customName" in data:
-                update_data["customName"] = data["customName"]
-            if "description" in data:
-                update_data["description"] = data["description"]
-            if "actions" in data:
-                update_data["actions"] = data["actions"]
-            if "config" in data:
-                if "actions" in data["config"]:
-                    for action_name in list(data["config"]["actions"].keys()):
-                        if not validate_function_name(action_name):
-                            return make_response(
-                                jsonify(
-                                    {
-                                        "success": False,
-                                        "message": f"Invalid function name '{action_name}'. Function names must match pattern '^[a-zA-Z0-9_-]+$'.",
-                                        "param": "tools[].function.name",
-                                    }
-                                ),
-                                400,
-                            )
-                tool_doc = user_tools_collection.find_one(
-                    {"_id": ObjectId(data["id"]), "user": user}
-                )
-                if tool_doc and tool_doc.get("name") == "mcp_tool":
-                    config = data["config"]
-                    existing_config = tool_doc.get("config", {})
-                    storage_config = existing_config.copy()
-
-                    storage_config.update(config)
-                    existing_credentials = {}
-                    if "encrypted_credentials" in existing_config:
-                        existing_credentials = decrypt_credentials(
-                            existing_config["encrypted_credentials"], user
-                        )
-                    auth_credentials = existing_credentials.copy()
-                    auth_type = storage_config.get("auth_type", "none")
-                    if auth_type == "api_key":
-                        if "api_key" in config and config["api_key"]:
-                            auth_credentials["api_key"] = config["api_key"]
-                        if "api_key_header" in config:
-                            auth_credentials["api_key_header"] = config[
-                                "api_key_header"
-                            ]
-                    elif auth_type == "bearer":
-                        if "bearer_token" in config and config["bearer_token"]:
-                            auth_credentials["bearer_token"] = config["bearer_token"]
-                        elif "encrypted_token" in config and config["encrypted_token"]:
-                            auth_credentials["bearer_token"] = config["encrypted_token"]
-                    elif auth_type == "basic":
-                        if "username" in config and config["username"]:
-                            auth_credentials["username"] = config["username"]
-                        if "password" in config and config["password"]:
-                            auth_credentials["password"] = config["password"]
-                    if auth_type != "none" and auth_credentials:
-                        encrypted_credentials_string = encrypt_credentials(
-                            auth_credentials, user
-                        )
-                        storage_config["encrypted_credentials"] = (
-                            encrypted_credentials_string
-                        )
-                    elif auth_type == "none":
-                        storage_config.pop("encrypted_credentials", None)
-                    for field in [
-                        "api_key",
-                        "bearer_token",
-                        "encrypted_token",
-                        "username",
-                        "password",
-                        "api_key_header",
-                    ]:
-                        storage_config.pop(field, None)
-                    update_data["config"] = storage_config
-                else:
-                    update_data["config"] = data["config"]
-            if "status" in data:
-                update_data["status"] = data["status"]
-            user_tools_collection.update_one(
-                {"_id": ObjectId(data["id"]), "user": user},
-                {"$set": update_data},
-            )
-        except Exception as err:
-            current_app.logger.error(f"Error updating tool: {err}", exc_info=True)
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"success": True}), 200)
-
-
-@tools_ns.route("/update_tool_config")
-class UpdateToolConfig(Resource):
-    @api.expect(
-        api.model(
-            "UpdateToolConfigModel",
-            {
-                "id": fields.String(required=True, description="Tool ID"),
-                "config": fields.Raw(
-                    required=True, description="Configuration of the tool"
-                ),
-            },
-        )
-    )
-    @api.doc(description="Update the configuration of a tool")
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-        required_fields = ["id", "config"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        try:
-            user_tools_collection.update_one(
-                {"_id": ObjectId(data["id"]), "user": user},
-                {"$set": {"config": data["config"]}},
-            )
-        except Exception as err:
-            current_app.logger.error(
-                f"Error updating tool config: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"success": True}), 200)
-
-
-@tools_ns.route("/update_tool_actions")
-class UpdateToolActions(Resource):
-    @api.expect(
-        api.model(
-            "UpdateToolActionsModel",
-            {
-                "id": fields.String(required=True, description="Tool ID"),
-                "actions": fields.List(
-                    fields.Raw,
-                    required=True,
-                    description="Actions the tool can perform",
-                ),
-            },
-        )
-    )
-    @api.doc(description="Update the actions of a tool")
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-        required_fields = ["id", "actions"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        try:
-            user_tools_collection.update_one(
-                {"_id": ObjectId(data["id"]), "user": user},
-                {"$set": {"actions": data["actions"]}},
-            )
-        except Exception as err:
-            current_app.logger.error(
-                f"Error updating tool actions: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"success": True}), 200)
-
-
-@tools_ns.route("/update_tool_status")
-class UpdateToolStatus(Resource):
-    @api.expect(
-        api.model(
-            "UpdateToolStatusModel",
-            {
-                "id": fields.String(required=True, description="Tool ID"),
-                "status": fields.Boolean(
-                    required=True, description="Status of the tool"
-                ),
-            },
-        )
-    )
-    @api.doc(description="Update the status of a tool")
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-        required_fields = ["id", "status"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        try:
-            user_tools_collection.update_one(
-                {"_id": ObjectId(data["id"]), "user": user},
-                {"$set": {"status": data["status"]}},
-            )
-        except Exception as err:
-            current_app.logger.error(
-                f"Error updating tool status: {err}", exc_info=True
-            )
-            return make_response(jsonify({"success": False}), 400)
-        return make_response(jsonify({"success": True}), 200)
-
-
-@tools_ns.route("/delete_tool")
-class DeleteTool(Resource):
-    @api.expect(
-        api.model(
-            "DeleteToolModel",
-            {"id": fields.String(required=True, description="Tool ID")},
-        )
-    )
-    @api.doc(description="Delete a tool by ID")
-    def post(self):
-        decoded_token = request.decoded_token
-        if not decoded_token:
-            return make_response(jsonify({"success": False}), 401)
-        user = decoded_token.get("sub")
-        data = request.get_json()
-        required_fields = ["id"]
-        missing_fields = check_required_fields(data, required_fields)
-        if missing_fields:
-            return missing_fields
-        try:
-            result = user_tools_collection.delete_one(
-                {"_id": ObjectId(data["id"]), "user": user}
-            )
-            if result.deleted_count == 0:
-                return {"success": False, "message": "Tool not found"}, 404
-        except Exception as err:
-            current_app.logger.error(f"Error deleting tool: {err}", exc_info=True)
-            return {"success": False}, 400
-        return {"success": True}, 200

application/core/settings.py

@@ -26,11 +26,7 @@ class Settings(BaseSettings):
         "gpt-4o-mini": 128000,
         "gpt-3.5-turbo": 4096,
         "claude-2": 1e5,
-        "gemini-2.5-flash": 1e6,
-    }
-    DEFAULT_AGENT_LIMITS: dict = {
-        "token_limit": 50000,
-        "request_limit": 500,
+        "gemini-2.0-flash-exp": 1e6,
     }
     UPLOAD_FOLDER: str = "inputs"
     PARSE_PDF_AS_IMAGE: bool = False
@@ -45,18 +41,11 @@ class Settings(BaseSettings):
     FALLBACK_LLM_API_KEY: Optional[str] = None  # api key for fallback llm
 
     # Google Drive integration
-    GOOGLE_CLIENT_ID: Optional[str] = (
-        None  # Replace with your actual Google OAuth client ID
-    )
-    GOOGLE_CLIENT_SECRET: Optional[str] = (
-        None  # Replace with your actual Google OAuth client secret
-    )
-    CONNECTOR_REDIRECT_BASE_URI: Optional[str] = (
-        "http://127.0.0.1:7091/api/connectors/callback"  ##add redirect url as it is to your provider's console(gcp)
-    )
+    GOOGLE_CLIENT_ID: Optional[str] = None # Replace with your actual Google OAuth client ID
+    GOOGLE_CLIENT_SECRET: Optional[str] = None# Replace with your actual Google OAuth client secret
+    CONNECTOR_REDIRECT_BASE_URI: Optional[str] = "http://127.0.0.1:7091/api/connectors/callback" 
+    ##append ?provider={provider_name} in your Provider console like http://127.0.0.1:7091/api/connectors/callback?provider=google_drive
 
-    # GitHub source
-    GITHUB_ACCESS_TOKEN: Optional[str] = None # PAT token with read repo access
 
     # LLM Cache
     CACHE_REDIS_URL: str = "redis://localhost:6379/2"
@@ -107,7 +96,7 @@ class Settings(BaseSettings):
     QDRANT_HOST: Optional[str] = None
     QDRANT_PATH: Optional[str] = None
     QDRANT_DISTANCE_FUNC: str = "Cosine"
-
+    
     # PGVector vectorstore config
     PGVECTOR_CONNECTION_STRING: Optional[str] = None
     # Milvus vectorstore config
@@ -127,11 +116,6 @@ class Settings(BaseSettings):
 
     JWT_SECRET_KEY: str = ""
 
-    # Encryption settings
-    ENCRYPTION_SECRET_KEY: str = "default-docsgpt-encryption-key"
-
-    TTS_PROVIDER: str = "google_tts" # google_tts or elevenlabs
-    ELEVENLABS_API_KEY: Optional[str] = None
 
 path = Path(__file__).parent.parent.absolute()
 settings = Settings(_env_file=path.joinpath(".env"), _env_file_encoding="utf-8")

application/llm/anthropic.py

@@ -46,9 +46,5 @@ class AnthropicLLM(BaseLLM):
             stream=True,
         )
 
-        try:
-            for completion in stream_response:
-                yield completion.completion
-        finally:
-            if hasattr(stream_response, 'close'):
-                stream_response.close()
+        for completion in stream_response:
+            yield completion.completion

application/llm/docsgpt_provider.py

@@ -121,19 +121,11 @@ class DocsGPTAPILLM(BaseLLM):
                 model="docsgpt", messages=messages, stream=stream, **kwargs
             )
 
-        try:
-            for line in response:
-                if (
-                    len(line.choices) > 0
-                    and line.choices[0].delta.content is not None
-                    and len(line.choices[0].delta.content) > 0
-                ):
-                    yield line.choices[0].delta.content
-                elif len(line.choices) > 0:
-                    yield line.choices[0]
-        finally:
-            if hasattr(response, 'close'):
-                response.close()
+        for line in response:
+            if len(line.choices) > 0 and line.choices[0].delta.content is not None and len(line.choices[0].delta.content) > 0:
+                yield line.choices[0].delta.content
+            elif len(line.choices) > 0:
+                yield line.choices[0]
 
     def _supports_tools(self):
         return True

application/llm/google_ai.py

@@ -143,7 +143,6 @@ class GoogleLLM(BaseLLM):
             raise
 
     def _clean_messages_google(self, messages):
-        """Convert OpenAI format messages to Google AI format."""
         cleaned_messages = []
         for message in messages:
             role = message.get("role")
@@ -151,8 +150,6 @@ class GoogleLLM(BaseLLM):
 
             if role == "assistant":
                 role = "model"
-            elif role == "tool":
-                role = "model"
 
             parts = []
             if role and content is not None:
@@ -191,63 +188,11 @@ class GoogleLLM(BaseLLM):
                 else:
                     raise ValueError(f"Unexpected content type: {type(content)}")
 
-                if parts:
-                    cleaned_messages.append(types.Content(role=role, parts=parts))
+                cleaned_messages.append(types.Content(role=role, parts=parts))
 
         return cleaned_messages
 
-    def _clean_schema(self, schema_obj):
-        """
-        Recursively remove unsupported fields from schema objects
-        and validate required properties.
-        """
-        if not isinstance(schema_obj, dict):
-            return schema_obj
-        allowed_fields = {
-            "type",
-            "description",
-            "items",
-            "properties",
-            "required",
-            "enum",
-            "pattern",
-            "minimum",
-            "maximum",
-            "nullable",
-            "default",
-        }
-
-        cleaned = {}
-        for key, value in schema_obj.items():
-            if key not in allowed_fields:
-                continue
-            elif key == "type" and isinstance(value, str):
-                cleaned[key] = value.upper()
-            elif isinstance(value, dict):
-                cleaned[key] = self._clean_schema(value)
-            elif isinstance(value, list):
-                cleaned[key] = [self._clean_schema(item) for item in value]
-            else:
-                cleaned[key] = value
-
-        # Validate that required properties actually exist in properties
-        if "required" in cleaned and "properties" in cleaned:
-            valid_required = []
-            properties_keys = set(cleaned["properties"].keys())
-            for required_prop in cleaned["required"]:
-                if required_prop in properties_keys:
-                    valid_required.append(required_prop)
-            if valid_required:
-                cleaned["required"] = valid_required
-            else:
-                cleaned.pop("required", None)
-        elif "required" in cleaned and "properties" not in cleaned:
-            cleaned.pop("required", None)
-
-        return cleaned
-
     def _clean_tools_format(self, tools_list):
-        """Convert OpenAI format tools to Google AI format."""
         genai_tools = []
         for tool_data in tools_list:
             if tool_data["type"] == "function":
@@ -256,16 +201,18 @@ class GoogleLLM(BaseLLM):
                 properties = parameters.get("properties", {})
 
                 if properties:
-                    cleaned_properties = {}
-                    for k, v in properties.items():
-                        cleaned_properties[k] = self._clean_schema(v)
-
                     genai_function = dict(
                         name=function["name"],
                         description=function["description"],
                         parameters={
                             "type": "OBJECT",
-                            "properties": cleaned_properties,
+                            "properties": {
+                                k: {
+                                    **v,
+                                    "type": v["type"].upper() if v["type"] else None,
+                                }
+                                for k, v in properties.items()
+                            },
                             "required": (
                                 parameters["required"]
                                 if "required" in parameters
@@ -295,7 +242,6 @@ class GoogleLLM(BaseLLM):
         response_schema=None,
         **kwargs,
     ):
-        """Generate content using Google AI API without streaming."""
         client = genai.Client(api_key=self.api_key)
         if formatting == "openai":
             messages = self._clean_messages_google(messages)
@@ -335,7 +281,6 @@ class GoogleLLM(BaseLLM):
         response_schema=None,
         **kwargs,
     ):
-        """Generate content using Google AI API with streaming."""
         client = genai.Client(api_key=self.api_key)
         if formatting == "openai":
             messages = self._clean_messages_google(messages)
@@ -373,32 +318,25 @@ class GoogleLLM(BaseLLM):
             config=config,
         )
 
-        try:
-            for chunk in response:
-                if hasattr(chunk, "candidates") and chunk.candidates:
-                    for candidate in chunk.candidates:
-                        if candidate.content and candidate.content.parts:
-                            for part in candidate.content.parts:
-                                if part.function_call:
-                                    yield part
-                                elif part.text:
-                                    yield part.text
-                elif hasattr(chunk, "text"):
-                    yield chunk.text
-        finally:
-            if hasattr(response, 'close'):
-                response.close()
+        for chunk in response:
+            if hasattr(chunk, "candidates") and chunk.candidates:
+                for candidate in chunk.candidates:
+                    if candidate.content and candidate.content.parts:
+                        for part in candidate.content.parts:
+                            if part.function_call:
+                                yield part
+                            elif part.text:
+                                yield part.text
+            elif hasattr(chunk, "text"):
+                yield chunk.text
 
     def _supports_tools(self):
-        """Return whether this LLM supports function calling."""
         return True
 
     def _supports_structured_output(self):
-        """Return whether this LLM supports structured JSON output."""
         return True
 
     def prepare_structured_output_format(self, json_schema):
-        """Convert JSON schema to Google AI structured output format."""
         if not json_schema:
             return None
 

application/llm/handlers/base.py

@@ -205,6 +205,7 @@ class LLMHandler(ABC):
                     except StopIteration as e:
                         tool_response, call_id = e.value
                         break
+
                 updated_messages.append(
                     {
                         "role": "assistant",
@@ -221,36 +222,17 @@ class LLMHandler(ABC):
                 )
 
                 updated_messages.append(self.create_tool_message(call, tool_response))
+
             except Exception as e:
                 logger.error(f"Error executing tool: {str(e)}", exc_info=True)
-                error_call = ToolCall(
-                    id=call.id, name=call.name, arguments=call.arguments
+                updated_messages.append(
+                    {
+                        "role": "tool",
+                        "content": f"Error executing tool: {str(e)}",
+                        "tool_call_id": call.id,
+                    }
                 )
-                error_response = f"Error executing tool: {str(e)}"
-                error_message = self.create_tool_message(error_call, error_response)
-                updated_messages.append(error_message)
 
-                call_parts = call.name.split("_")
-                if len(call_parts) >= 2:
-                    tool_id = call_parts[-1]  # Last part is tool ID (e.g., "1")
-                    action_name = "_".join(call_parts[:-1])
-                    tool_name = tools_dict.get(tool_id, {}).get("name", "unknown_tool")
-                    full_action_name = f"{action_name}_{tool_id}"
-                else:
-                    tool_name = "unknown_tool"
-                    action_name = call.name
-                    full_action_name = call.name
-                yield {
-                    "type": "tool_call",
-                    "data": {
-                        "tool_name": tool_name,
-                        "call_id": call.id,
-                        "action_name": full_action_name,
-                        "arguments": call.arguments,
-                        "error": error_response,
-                        "status": "error",
-                    },
-                }
         return updated_messages
 
     def handle_non_streaming(
@@ -281,11 +263,13 @@ class LLMHandler(ABC):
                 except StopIteration as e:
                     messages = e.value
                     break
+
             response = agent.llm.gen(
                 model=agent.gpt_model, messages=messages, tools=agent.tools
             )
             parsed = self.parse_response(response)
             self.llm_calls.append(build_stack_data(agent.llm))
+
         return parsed.content
 
     def handle_streaming(

application/llm/handlers/google.py

@@ -17,6 +17,7 @@ class GoogleLLMHandler(LLMHandler):
                 finish_reason="stop",
                 raw_response=response,
             )
+
         if hasattr(response, "candidates"):
             parts = response.candidates[0].content.parts if response.candidates else []
             tool_calls = [
@@ -40,6 +41,7 @@ class GoogleLLMHandler(LLMHandler):
                 finish_reason="tool_calls" if tool_calls else "stop",
                 raw_response=response,
             )
+
         else:
             tool_calls = []
             if hasattr(response, "function_call"):
@@ -59,16 +61,14 @@ class GoogleLLMHandler(LLMHandler):
 
     def create_tool_message(self, tool_call: ToolCall, result: Any) -> Dict:
         """Create Google-style tool message."""
+        from google.genai import types
 
         return {
-            "role": "model",
+            "role": "tool",
             "content": [
-                {
-                    "function_response": {
-                        "name": tool_call.name,
-                        "response": {"result": result},
-                    }
-                }
+                types.Part.from_function_response(
+                    name=tool_call.name, response={"result": result}
+                ).to_json_dict()
             ],
         }
 

application/llm/openai.py

@@ -170,19 +170,15 @@ class OpenAILLM(BaseLLM):
 
         response = self.client.chat.completions.create(**request_params)
 
-        try:
-            for line in response:
-                if (
-                    len(line.choices) > 0
-                    and line.choices[0].delta.content is not None
-                    and len(line.choices[0].delta.content) > 0
-                ):
-                    yield line.choices[0].delta.content
-                elif len(line.choices) > 0:
-                    yield line.choices[0]
-        finally:
-            if hasattr(response, 'close'):
-                response.close()
+        for line in response:
+            if (
+                len(line.choices) > 0
+                and line.choices[0].delta.content is not None
+                and len(line.choices[0].delta.content) > 0
+            ):
+                yield line.choices[0].delta.content
+            elif len(line.choices) > 0:
+                yield line.choices[0]
 
     def _supports_tools(self):
         return True

application/parser/connectors/google_drive/auth.py

@@ -17,13 +17,14 @@ class GoogleDriveAuth(BaseConnectorAuth):
     """
     
     SCOPES = [
-        'https://www.googleapis.com/auth/drive.file'
+        'https://www.googleapis.com/auth/drive.readonly',
+        'https://www.googleapis.com/auth/drive.metadata.readonly'
     ]
     
     def __init__(self):
         self.client_id = settings.GOOGLE_CLIENT_ID
         self.client_secret = settings.GOOGLE_CLIENT_SECRET
-        self.redirect_uri = f"{settings.CONNECTOR_REDIRECT_BASE_URI}"
+        self.redirect_uri = f"{settings.CONNECTOR_REDIRECT_BASE_URI}?provider=google_drive"
         
         if not self.client_id or not self.client_secret:
             raise ValueError("Google OAuth credentials not configured. Please set GOOGLE_CLIENT_ID and GOOGLE_CLIENT_SECRET in settings.")
@@ -49,7 +50,7 @@ class GoogleDriveAuth(BaseConnectorAuth):
             authorization_url, _ = flow.authorization_url(
                 access_type='offline',
                 prompt='consent',
-                include_granted_scopes='false',
+                include_granted_scopes='true',
                 state=state
             )
             

application/parser/connectors/google_drive/loader.py

@@ -32,10 +32,6 @@ class GoogleDriveLoader(BaseConnectorLoader):
         'text/plain': '.txt',
         'text/csv': '.csv',
         'text/html': '.html',
-        'text/markdown': '.md',
-        'text/x-rst': '.rst',
-        'application/json': '.json',
-        'application/epub+zip': '.epub',
         'application/rtf': '.rtf',
         'image/jpeg': '.jpg',
         'image/jpg': '.jpg',
@@ -124,7 +120,6 @@ class GoogleDriveLoader(BaseConnectorLoader):
             list_only = inputs.get('list_only', False)
             load_content = not list_only
             page_token = inputs.get('page_token')
-            search_query = inputs.get('search_query')
             self.next_page_token = None
 
             if file_ids:
@@ -133,18 +128,12 @@ class GoogleDriveLoader(BaseConnectorLoader):
                     try:
                         doc = self._load_file_by_id(file_id, load_content=load_content)
                         if doc:
-                            if not search_query or (
-                                search_query.lower() in doc.extra_info.get('file_name', '').lower()
-                            ):
-                                documents.append(doc)
+                            documents.append(doc)
                         elif hasattr(self, '_credential_refreshed') and self._credential_refreshed:
                             self._credential_refreshed = False
                             logging.info(f"Retrying load of file {file_id} after credential refresh")
                             doc = self._load_file_by_id(file_id, load_content=load_content)
-                            if doc and (
-                                not search_query or 
-                                search_query.lower() in doc.extra_info.get('file_name', '').lower()
-                            ):
+                            if doc:
                                 documents.append(doc)
                     except Exception as e:
                         logging.error(f"Error loading file {file_id}: {e}")
@@ -152,13 +141,7 @@ class GoogleDriveLoader(BaseConnectorLoader):
             else:
                 # Browsing mode: list immediate children of provided folder or root
                 parent_id = folder_id if folder_id else 'root'
-                documents = self._list_items_in_parent(
-                    parent_id, 
-                    limit=limit, 
-                    load_content=load_content, 
-                    page_token=page_token,
-                    search_query=search_query
-                )
+                documents = self._list_items_in_parent(parent_id, limit=limit, load_content=load_content, page_token=page_token)
 
             logging.info(f"Loaded {len(documents)} documents from Google Drive")
             return documents
@@ -201,18 +184,13 @@ class GoogleDriveLoader(BaseConnectorLoader):
             return None
 
 
-    def _list_items_in_parent(self, parent_id: str, limit: int = 100, load_content: bool = False, page_token: Optional[str] = None, search_query: Optional[str] = None) -> List[Document]:
+    def _list_items_in_parent(self, parent_id: str, limit: int = 100, load_content: bool = False, page_token: Optional[str] = None) -> List[Document]:
         self._ensure_service()
 
         documents: List[Document] = []
 
         try:
             query = f"'{parent_id}' in parents and trashed=false"
-
-            if search_query:
-                safe_search = search_query.replace("'", "\\'")
-                query += f" and name contains '{safe_search}'"
-
             next_token_out: Optional[str] = None
 
             while True:
@@ -227,8 +205,7 @@ class GoogleDriveLoader(BaseConnectorLoader):
                     q=query,
                     fields='nextPageToken,files(id,name,mimeType,size,createdTime,modifiedTime,parents)',
                     pageToken=page_token,
-                    pageSize=page_size,
-                    orderBy='name'
+                    pageSize=page_size
                 ).execute()
 
                 items = results.get('files', [])

application/parser/remote/github_loader.py

@@ -1,135 +1,44 @@
 import base64
 import requests
-import time
-from typing import List, Optional
+from typing import List
 from application.parser.remote.base import BaseRemote
-from application.parser.schema.base import Document
+from langchain_core.documents import Document
 import mimetypes
-from application.core.settings import settings
 
 class GitHubLoader(BaseRemote):
     def __init__(self):
-        self.access_token = settings.GITHUB_ACCESS_TOKEN
+        self.access_token = None
         self.headers = {
-            "Authorization": f"token {self.access_token}",
-            "Accept": "application/vnd.github.v3+json"
-        } if self.access_token else {
-            "Accept": "application/vnd.github.v3+json"
-        }
+            "Authorization": f"token {self.access_token}"
+        } if self.access_token else {}
         return
 
-    def is_text_file(self, file_path: str) -> bool:
-        """Determine if a file is a text file based on extension."""
-        # Common text file extensions
-        text_extensions = {
-            '.txt', '.md', '.markdown', '.rst', '.json', '.xml', '.yaml', '.yml',
-            '.py', '.js', '.ts', '.jsx', '.tsx', '.java', '.c', '.cpp', '.h', '.hpp',
-            '.cs', '.go', '.rs', '.rb', '.php', '.swift', '.kt', '.scala',
-            '.html', '.css', '.scss', '.sass', '.less',
-            '.sh', '.bash', '.zsh', '.fish',
-            '.sql', '.r', '.m', '.mat',
-            '.ini', '.cfg', '.conf', '.config', '.env',
-            '.gitignore', '.dockerignore', '.editorconfig',
-            '.log', '.csv', '.tsv'
-        }
-
-        # Get file extension
-        file_lower = file_path.lower()
-        for ext in text_extensions:
-            if file_lower.endswith(ext):
-                return True
-
-        # Also check MIME type
-        mime_type, _ = mimetypes.guess_type(file_path)
-        if mime_type and (mime_type.startswith("text") or mime_type in ["application/json", "application/xml"]):
-            return True
-
-        return False
-
-    def fetch_file_content(self, repo_url: str, file_path: str) -> Optional[str]:
-        """Fetch file content. Returns None if file should be skipped (binary files or empty files)."""
+    def fetch_file_content(self, repo_url: str, file_path: str) -> str:
         url = f"https://api.github.com/repos/{repo_url}/contents/{file_path}"
-        response = self._make_request(url)
+        response = requests.get(url, headers=self.headers)
 
-        content = response.json()
+        if response.status_code == 200:
+            content = response.json()
+            mime_type, _ = mimetypes.guess_type(file_path)  # Guess the MIME type based on the file extension
 
-        if content.get("encoding") == "base64":
-            if self.is_text_file(file_path):  # Handle only text files
-                try:
-                    decoded_content = base64.b64decode(content["content"]).decode("utf-8").strip()
-                    # Skip empty files
-                    if not decoded_content:
-                        return None
-                    return decoded_content
-                except Exception:
-                    # If decoding fails, it's probably a binary file
-                    return None
+            if content.get("encoding") == "base64":
+                if mime_type and mime_type.startswith("text"):  # Handle only text files
+                    try:
+                        decoded_content = base64.b64decode(content["content"]).decode("utf-8")
+                        return f"Filename: {file_path}\n\n{decoded_content}"
+                    except Exception as e:
+                        raise e
+                else:
+                    return f"Filename: {file_path} is a binary file and was skipped."
             else:
-                # Skip binary files by returning None
-                return None
+                return f"Filename: {file_path}\n\n{content['content']}"
         else:
-            file_content = content['content'].strip()
-            # Skip empty files
-            if not file_content:
-                return None
-            return file_content
-
-    def _make_request(self, url: str, max_retries: int = 3) -> requests.Response:
-        """Make a request with retry logic for rate limiting"""
-        for attempt in range(max_retries):
-            response = requests.get(url, headers=self.headers)
-
-            if response.status_code == 200:
-                return response
-            elif response.status_code == 403:
-                # Check if it's a rate limit issue
-                try:
-                    error_data = response.json()
-                    error_msg = error_data.get("message", "")
-
-                    # Check rate limit headers
-                    remaining = response.headers.get("X-RateLimit-Remaining", "unknown")
-                    reset_time = response.headers.get("X-RateLimit-Reset", "unknown")
-
-                    print(f"GitHub API 403 Error: {error_msg}")
-                    print(f"Rate limit remaining: {remaining}, Reset time: {reset_time}")
-
-                    if "rate limit" in error_msg.lower():
-                        if attempt < max_retries - 1:
-                            wait_time = 2 ** attempt  # Exponential backoff
-                            print(f"Rate limit hit, waiting {wait_time} seconds before retry...")
-                            time.sleep(wait_time)
-                            continue
-
-                    # Provide helpful error message
-                    if remaining == "0":
-                        raise Exception(f"GitHub API rate limit exceeded. Please set GITHUB_ACCESS_TOKEN environment variable. Reset time: {reset_time}")
-                    else:
-                        raise Exception(f"GitHub API error: {error_msg}. This may require authentication - set GITHUB_ACCESS_TOKEN environment variable.")
-                except Exception as e:
-                    if isinstance(e, Exception) and "GitHub API" in str(e):
-                        raise
-                    # If we can't parse the response, raise the original error
-                    response.raise_for_status()
-            else:
-                response.raise_for_status()
-
-        return response
+            response.raise_for_status()
 
     def fetch_repo_files(self, repo_url: str, path: str = "") -> List[str]:
         url = f"https://api.github.com/repos/{repo_url}/contents/{path}"
-        response = self._make_request(url)
-
+        response = requests.get(url, headers={**self.headers, "Accept": "application/vnd.github.v3.raw"})
         contents = response.json()
-
-        # Handle error responses from GitHub API
-        if isinstance(contents, dict) and "message" in contents:
-            raise Exception(f"GitHub API error: {contents.get('message')}")
-
-        # Ensure contents is a list
-        if not isinstance(contents, list):
-            raise TypeError(f"Expected list from GitHub API, got {type(contents).__name__}: {contents}")
-
         files = []
         for item in contents:
             if item["type"] == "file":
@@ -144,15 +53,6 @@ class GitHubLoader(BaseRemote):
         documents = []
         for file_path in files:
             content = self.fetch_file_content(repo_name, file_path)
-            # Skip binary files (content is None)
-            if content is None:
-                continue
-            documents.append(Document(
-                text=content,
-                doc_id=file_path,
-                extra_info={
-                    "title": file_path,
-                    "source": f"https://github.com/{repo_name}/blob/main/{file_path}"
-                }
-            ))
+            documents.append(Document(page_content=content, metadata={"title": file_path, 
+            "source": f"https://github.com/{repo_name}/blob/main/{file_path}"}))
         return documents

application/requirements.txt

@@ -2,7 +2,6 @@ anthropic==0.49.0
 boto3==1.38.18
 beautifulsoup4==4.13.4
 celery==5.4.0
-cryptography==42.0.8
 dataclasses-json==0.6.7
 docx2txt==0.8
 duckduckgo-search==7.5.2
@@ -10,10 +9,8 @@ ebooklib==0.18
 escodegen==1.0.11
 esprima==4.0.1
 esutils==1.0.1
-elevenlabs==2.17.0
 Flask==3.1.1
 faiss-cpu==1.9.0.post1
-fastmcp==2.11.0
 flask-restx==1.3.0
 google-genai==1.3.0
 google-api-python-client==2.179.0
@@ -30,7 +27,7 @@ jsonpatch==1.33
 jsonpointer==3.0.0
 kombu==5.4.2
 langchain==0.3.20
-langchain-community==0.4.1
+langchain-community==0.3.19
 langchain-core==0.3.59
 langchain-openai==0.3.16
 langchain-text-splitters==0.3.8
@@ -58,13 +55,13 @@ prompt-toolkit==3.0.51
 protobuf==5.29.3
 psycopg2-binary==2.9.10
 py==1.11.0
-pydantic
-pydantic-core
-pydantic-settings
+pydantic==2.10.6
+pydantic-core==2.27.2
+pydantic-settings==2.7.1
 pymongo==4.11.3
 pypdf==5.5.0
 python-dateutil==2.9.0.post0
-python-dotenv
+python-dotenv==1.0.1
 python-jose==3.4.0
 python-pptx==1.0.2
 redis==5.2.1
@@ -84,7 +81,7 @@ tzdata==2024.2
 urllib3==2.3.0
 vine==5.1.0
 wcwidth==0.2.13
-werkzeug>=3.1.0,<3.1.2
+werkzeug==3.1.3
 yarl==1.20.0
 markdownify==1.1.0
 tldextract==5.1.3

application/retriever/base.py

@@ -5,6 +5,10 @@ class BaseRetriever(ABC):
     def __init__(self):
         pass
 
+    @abstractmethod
+    def gen(self, *args, **kwargs):
+        pass
+
     @abstractmethod
     def search(self, *args, **kwargs):
         pass

application/retriever/classic_rag.py

@@ -1,6 +1,4 @@
 import logging
-import os
-
 from application.core.settings import settings
 from application.llm.llm_creator import LLMCreator
 from application.retriever.base import BaseRetriever
@@ -22,25 +20,10 @@ class ClassicRAG(BaseRetriever):
         api_key=settings.API_KEY,
         decoded_token=None,
     ):
-        """Initialize ClassicRAG retriever with vectorstore sources and LLM configuration"""
-        self.original_question = source.get("question", "")
+        self.original_question = ""
         self.chat_history = chat_history if chat_history is not None else []
         self.prompt = prompt
-        if isinstance(chunks, str):
-            try:
-                self.chunks = int(chunks)
-            except ValueError:
-                logging.warning(
-                    f"Invalid chunks value '{chunks}', using default value 2"
-                )
-                self.chunks = 2
-        else:
-            self.chunks = chunks
-        user_identifier = user_api_key if user_api_key else "default"
-        logging.info(
-            f"ClassicRAG initialized with chunks={self.chunks}, user_api_key={user_identifier}, "
-            f"sources={'active_docs' in source and source['active_docs'] is not None}"
-        )
+        self.chunks = chunks
         self.gpt_model = gpt_model
         self.token_limit = (
             token_limit
@@ -61,48 +44,26 @@ class ClassicRAG(BaseRetriever):
             user_api_key=self.user_api_key,
             decoded_token=decoded_token,
         )
-
-        if "active_docs" in source and source["active_docs"] is not None:
-            if isinstance(source["active_docs"], list):
-                self.vectorstores = source["active_docs"]
-            else:
-                self.vectorstores = [source["active_docs"]]
-        else:
-            self.vectorstores = []
+        self.vectorstore = source["active_docs"] if "active_docs" in source else None
         self.question = self._rephrase_query()
         self.decoded_token = decoded_token
-        self._validate_vectorstore_config()
-
-    def _validate_vectorstore_config(self):
-        """Validate vectorstore IDs and remove any empty/invalid entries"""
-        if not self.vectorstores:
-            logging.warning("No vectorstores configured for retrieval")
-            return
-        invalid_ids = [
-            vs_id for vs_id in self.vectorstores if not vs_id or not vs_id.strip()
-        ]
-        if invalid_ids:
-            logging.warning(f"Found invalid vectorstore IDs: {invalid_ids}")
-            self.vectorstores = [
-                vs_id for vs_id in self.vectorstores if vs_id and vs_id.strip()
-            ]
 
     def _rephrase_query(self):
-        """Rephrase user query with chat history context for better retrieval"""
         if (
             not self.original_question
             or not self.chat_history
             or self.chat_history == []
             or self.chunks == 0
-            or not self.vectorstores
+            or self.vectorstore is None
         ):
             return self.original_question
-        prompt = (
-            "Given the following conversation history:\n"
-            f"{self.chat_history}\n\n"
-            "Rephrase the following user question to be a standalone search query "
-            "that captures all relevant context from the conversation:\n"
-        )
+
+        prompt = f"""Given the following conversation history:
+        {self.chat_history}
+
+        Rephrase the following user question to be a standalone search query 
+        that captures all relevant context from the conversation:
+        """
 
         messages = [
             {"role": "system", "content": prompt},
@@ -118,89 +79,44 @@ class ClassicRAG(BaseRetriever):
             return self.original_question
 
     def _get_data(self):
-        """Retrieve relevant documents from configured vectorstores"""
-        if self.chunks == 0 or not self.vectorstores:
-            logging.info(
-                f"ClassicRAG._get_data: Skipping retrieval - chunks={self.chunks}, "
-                f"vectorstores_count={len(self.vectorstores) if self.vectorstores else 0}"
+        if self.chunks == 0 or self.vectorstore is None:
+            docs = []
+        else:
+            docsearch = VectorCreator.create_vectorstore(
+                settings.VECTOR_STORE, self.vectorstore, settings.EMBEDDINGS_KEY
             )
-            return []
-        all_docs = []
-        chunks_per_source = max(1, self.chunks // len(self.vectorstores))
+            docs_temp = docsearch.search(self.question, k=self.chunks)
+            docs = [
+                {
+                    "title": i.metadata.get(
+                        "title", i.metadata.get("post_title", i.page_content)
+                    ).split("/")[-1],
+                    "text": i.page_content,
+                    "source": (
+                        i.metadata.get("source")
+                        if i.metadata.get("source")
+                        else "local"
+                    ),
+                }
+                for i in docs_temp
+            ]
 
-        logging.info(
-            f"ClassicRAG._get_data: Starting retrieval with chunks={self.chunks}, "
-            f"vectorstores={self.vectorstores}, chunks_per_source={chunks_per_source}, "
-            f"query='{self.question[:50]}...'"
-        )
+        return docs
 
-        for vectorstore_id in self.vectorstores:
-            if vectorstore_id:
-                try:
-                    docsearch = VectorCreator.create_vectorstore(
-                        settings.VECTOR_STORE, vectorstore_id, settings.EMBEDDINGS_KEY
-                    )
-                    docs_temp = docsearch.search(self.question, k=chunks_per_source)
-
-                    for doc in docs_temp:
-                        if hasattr(doc, "page_content") and hasattr(doc, "metadata"):
-                            page_content = doc.page_content
-                            metadata = doc.metadata
-                        else:
-                            page_content = doc.get("text", doc.get("page_content", ""))
-                            metadata = doc.get("metadata", {})
-                        title = metadata.get(
-                            "title", metadata.get("post_title", page_content)
-                        )
-                        if not isinstance(title, str):
-                            title = str(title)
-                        title = title.split("/")[-1]
-
-                        filename = (
-                            metadata.get("filename")
-                            or metadata.get("file_name")
-                            or metadata.get("source")
-                        )
-                        if isinstance(filename, str):
-                            filename = os.path.basename(filename) or filename
-                        else:
-                            filename = title
-                        if not filename:
-                            filename = title
-                        source_path = metadata.get("source") or vectorstore_id
-                        all_docs.append(
-                            {
-                                "title": title,
-                                "text": page_content,
-                                "source": source_path,
-                                "filename": filename,
-                            }
-                        )
-                except Exception as e:
-                    logging.error(
-                        f"Error searching vectorstore {vectorstore_id}: {e}",
-                        exc_info=True,
-                    )
-                    continue
-        logging.info(
-            f"ClassicRAG._get_data: Retrieval complete - retrieved {len(all_docs)} documents "
-            f"(requested chunks={self.chunks}, chunks_per_source={chunks_per_source})"
-        )
-        return all_docs
+    def gen():
+        pass
 
     def search(self, query: str = ""):
-        """Search for documents using optional query override"""
         if query:
             self.original_question = query
             self.question = self._rephrase_query()
         return self._get_data()
 
     def get_params(self):
-        """Return current retriever configuration parameters"""
         return {
             "question": self.original_question,
             "rephrased_question": self.question,
-            "sources": self.vectorstores,
+            "source": self.vectorstore,
             "chunks": self.chunks,
             "token_limit": self.token_limit,
             "gpt_model": self.gpt_model,

application/security/encryption.py

@@ -1,85 +0,0 @@
-import base64
-import json
-import os
-
-from cryptography.hazmat.backends import default_backend
-from cryptography.hazmat.primitives import hashes
-from cryptography.hazmat.primitives.ciphers import algorithms, Cipher, modes
-from cryptography.hazmat.primitives.kdf.pbkdf2 import PBKDF2HMAC
-
-from application.core.settings import settings
-
-
-def _derive_key(user_id: str, salt: bytes) -> bytes:
-    app_secret = settings.ENCRYPTION_SECRET_KEY
-
-    password = f"{app_secret}#{user_id}".encode()
-
-    kdf = PBKDF2HMAC(
-        algorithm=hashes.SHA256(),
-        length=32,
-        salt=salt,
-        iterations=100000,
-        backend=default_backend(),
-    )
-
-    return kdf.derive(password)
-
-
-def encrypt_credentials(credentials: dict, user_id: str) -> str:
-    if not credentials:
-        return ""
-    try:
-        salt = os.urandom(16)
-        iv = os.urandom(16)
-        key = _derive_key(user_id, salt)
-
-        json_str = json.dumps(credentials)
-
-        cipher = Cipher(algorithms.AES(key), modes.CBC(iv), backend=default_backend())
-        encryptor = cipher.encryptor()
-
-        padded_data = _pad_data(json_str.encode())
-        encrypted_data = encryptor.update(padded_data) + encryptor.finalize()
-
-        result = salt + iv + encrypted_data
-        return base64.b64encode(result).decode()
-    except Exception as e:
-        print(f"Warning: Failed to encrypt credentials: {e}")
-        return ""
-
-
-def decrypt_credentials(encrypted_data: str, user_id: str) -> dict:
-    if not encrypted_data:
-        return {}
-    try:
-        data = base64.b64decode(encrypted_data.encode())
-
-        salt = data[:16]
-        iv = data[16:32]
-        encrypted_content = data[32:]
-
-        key = _derive_key(user_id, salt)
-
-        cipher = Cipher(algorithms.AES(key), modes.CBC(iv), backend=default_backend())
-        decryptor = cipher.decryptor()
-
-        decrypted_padded = decryptor.update(encrypted_content) + decryptor.finalize()
-        decrypted_data = _unpad_data(decrypted_padded)
-
-        return json.loads(decrypted_data.decode())
-    except Exception as e:
-        print(f"Warning: Failed to decrypt credentials: {e}")
-        return {}
-
-
-def _pad_data(data: bytes) -> bytes:
-    block_size = 16
-    padding_len = block_size - (len(data) % block_size)
-    padding = bytes([padding_len]) * padding_len
-    return data + padding
-
-
-def _unpad_data(data: bytes) -> bytes:
-    padding_len = data[-1]
-    return data[:-padding_len]

application/seed/commands.py

@@ -1,26 +0,0 @@
-import click
-
-from application.core.mongo_db import MongoDB
-from application.core.settings import settings
-from application.seed.seeder import DatabaseSeeder
-
-
-@click.group()
-def seed():
-    """Database seeding commands"""
-    pass
-
-
-@seed.command()
-@click.option("--force", is_flag=True, help="Force reseeding even if data exists")
-def init(force):
-    """Initialize database with seed data"""
-    mongo = MongoDB.get_client()
-    db = mongo[settings.MONGO_DB_NAME]
-
-    seeder = DatabaseSeeder(db)
-    seeder.seed_initial_data(force=force)
-
-
-if __name__ == "__main__":
-    seed()

application/seed/config/agents_template.yaml

@@ -1,36 +0,0 @@
-# Configuration for Premade Agents
-# This file contains template agents that will be seeded into the database
-
-agents:
-  # Basic Agent Template
-  - name: "Agent Name" # Required: Unique name for the agent
-    description: "What this agent does" # Required: Brief description of the agent's purpose
-    image: "URL_TO_IMAGE" # Optional: URL to agent's avatar/image
-    agent_type: "classic" # Required: Type of agent (e.g., classic, react, etc.)
-    prompt_id: "default" # Optional: Reference to prompt template
-    prompt: # Optional: Define new prompt
-      name: "New Prompt"
-      content: "You are new agent with cool new prompt."
-    chunks: "0" # Optional: Chunking strategy for documents
-    retriever: "" # Optional: Retriever type for document search
-
-    # Source Configuration (where the agent gets its knowledge)
-    source: # Optional: Select a source to link with agent
-      name: "Source Display Name" # Human-readable name for the source
-      url: "https://example.com/data-source" # URL or path to knowledge source
-      loader: "url" # Type of loader (url, pdf, txt, etc.)
-
-    # Tools Configuration (what capabilities the agent has)
-    tools: # Optional: Remove if agent doesn't need tools
-      - name: "tool_name" # Must match a supported tool name
-        display_name: "Tool Display Name" # Optional: Human-readable name for the tool
-        config:
-        # Tool-specific configuration
-        # Example for DuckDuckGo:
-        # token: "${DDG_API_KEY}"          # ${} denotes environment variable
-
-      # Add more tools as needed
-      # - name: "another_tool"
-      #   config:
-      #     param1: "value1"
-      #     param2: "${ENV_VAR}"

application/seed/config/premade_agents.yaml

@@ -1,94 +0,0 @@
-# Configuration for Premade Agents
-
-agents:
-  - name: "Assistant"
-    description: "Your general-purpose AI assistant. Ready to help with a wide range of tasks."
-    image: "https://d3dg1063dc54p9.cloudfront.net/imgs/agents/agent-logo.svg"
-    agent_type: "classic"
-    prompt_id: "default"
-    chunks: "0"
-    retriever: ""
-
-    # Tools Configuration
-    tools:
-      - name: "tool_name"
-        display_name: "read_webpage" 
-        config:
-
-  - name: "Researcher"
-    description: "A specialized research agent that performs deep dives into subjects."
-    image: "https://d3dg1063dc54p9.cloudfront.net/imgs/agents/agent-researcher.svg"
-    agent_type: "react"
-    prompt:
-      name: "Researcher-Agent"
-      content: |
-        You are a specialized AI research assistant, DocsGPT. Your primary function is to conduct in-depth research on a given subject or question. You are methodical, thorough, and analytical. You should perform multiple iterations of thinking to gather and synthesize information before providing a final, comprehensive answer.
-
-        You have access to the 'Read Webpage' tool. Use this tool to explore sources, gather data, and deepen your understanding. Be proactive in using the tool to fill in knowledge gaps and validate information.
-
-        Users can Upload documents for your context as attachments or sources via UI using the Conversation input box.
-        If appropriate, your answers can include code examples, formatted as follows:
-        ```(language)
-        (code)
-        ```
-        Users are also able to see charts and diagrams if you use them with valid mermaid syntax in your responses. Try to respond with mermaid charts if visualization helps with users queries. You effectively utilize chat history, ensuring relevant and tailored responses. Try to use additional provided context if it's available, otherwise use your knowledge and tool capabilities.
-        ----------------
-        Possible additional context from uploaded sources:
-        {summaries}
-
-    chunks: "0"
-    retriever: ""
-
-    # Tools Configuration
-    tools:
-      - name: "tool_name"
-        display_name: "read_webpage" 
-        config:
-
-  - name: "Search Widget"
-    description: "A powerful search widget agent. Ask it anything about DocsGPT"
-    image: "https://d3dg1063dc54p9.cloudfront.net/imgs/agents/agent-search.svg"
-    agent_type: "classic"
-    prompt:
-      name: "Search-Agent"
-      content: |
-        You are a website search assistant, DocsGPT. Your sole purpose is to help users find information within the provided context of the DocsGPT documentation. Act as a specialized search engine.
-
-        Your answers must be based *only* on the provided context. Do not use any external knowledge. If the answer is not in the context, inform the user that you could not find the information within the documentation.
-
-        Keep your responses concise and directly related to the user's query, pointing them to the most relevant information.
-        ----------------
-        Possible additional context from uploaded sources:
-        {summaries}
-
-    chunks: "8"
-    retriever: ""
-
-    source:
-      name: "DocsGPT-Docs"
-      url: "https://d3dg1063dc54p9.cloudfront.net/agent-source/docsgpt-documentation.md" # URL to DocsGPT documentation
-      loader: "url" 
-
-  - name: "Support Widget"
-    description: "A friendly support widget agent to help you with any questions."
-    image: "https://d3dg1063dc54p9.cloudfront.net/imgs/agents/agent-support.svg"
-    agent_type: "classic"
-    prompt:
-      name: "Support-Agent"
-      content: |
-        You are a helpful AI support widget agent, DocsGPT. Your goal is to assist users by answering their questions about our website, product and its features. Provide friendly, clear, and direct support.
-
-        Your knowledge is strictly limited to the provided context from the DocsGPT documentation. You must not answer questions outside of this scope. If a user asks something you cannot answer from the context, politely state that you can only help with questions about this website.
-
-        Effectively utilize chat history to understand the user's issue fully. Guide users to the information they need in a helpful and conversational manner.
-        ----------------
-        Possible additional context from uploaded sources:
-        {summaries}
-
-    chunks: "8"
-    retriever: ""
-
-    source:
-      name: "DocsGPT-Docs"
-      url: "https://d3dg1063dc54p9.cloudfront.net/agent-source/docsgpt-documentation.md" # URL to DocsGPT documentation
-      loader: "url" 

application/seed/seeder.py

@@ -1,277 +0,0 @@
-import logging
-import os
-from datetime import datetime, timezone
-from typing import Dict, List, Optional, Union
-
-import yaml
-from bson import ObjectId
-from bson.dbref import DBRef
-
-from dotenv import load_dotenv
-from pymongo import MongoClient
-
-from application.agents.tools.tool_manager import ToolManager
-from application.api.user.tasks import ingest_remote
-
-load_dotenv()
-tool_config = {}
-tool_manager = ToolManager(config=tool_config)
-
-
-class DatabaseSeeder:
-    def __init__(self, db):
-        self.db = db
-        self.tools_collection = self.db["user_tools"]
-        self.sources_collection = self.db["sources"]
-        self.agents_collection = self.db["agents"]
-        self.prompts_collection = self.db["prompts"]
-        self.system_user_id = "system"
-        self.logger = logging.getLogger(__name__)
-
-    def seed_initial_data(self, config_path: str = None, force=False):
-        """Main entry point for seeding all initial data"""
-        if not force and self._is_already_seeded():
-            self.logger.info("Database already seeded. Use force=True to reseed.")
-            return
-        config_path = config_path or os.path.join(
-            os.path.dirname(__file__), "config", "premade_agents.yaml"
-        )
-
-        try:
-            with open(config_path, "r") as f:
-                config = yaml.safe_load(f)
-                self._seed_from_config(config)
-        except Exception as e:
-            self.logger.error(f"Failed to load seeding config: {str(e)}")
-            raise
-
-    def _seed_from_config(self, config: Dict):
-        """Seed all data from configuration"""
-        self.logger.info("🌱 Starting seeding...")
-
-        if not config.get("agents"):
-            self.logger.warning("No agents found in config")
-            return
-        used_tool_ids = set()
-
-        for agent_config in config["agents"]:
-            try:
-                self.logger.info(f"Processing agent: {agent_config['name']}")
-
-                # 1. Handle Source
-
-                source_result = self._handle_source(agent_config)
-                if source_result is False:
-                    self.logger.error(
-                        f"Skipping agent {agent_config['name']} due to source ingestion failure"
-                    )
-                    continue
-                source_id = source_result
-                # 2. Handle Tools
-
-                tool_ids = self._handle_tools(agent_config)
-                if len(tool_ids) == 0:
-                    self.logger.warning(
-                        f"No valid tools for agent {agent_config['name']}"
-                    )
-                used_tool_ids.update(tool_ids)
-
-                # 3. Handle Prompt
-
-                prompt_id = self._handle_prompt(agent_config)
-
-                # 4. Create Agent
-
-                agent_data = {
-                    "user": self.system_user_id,
-                    "name": agent_config["name"],
-                    "description": agent_config["description"],
-                    "image": agent_config.get("image", ""),
-                    "source": (
-                        DBRef("sources", ObjectId(source_id)) if source_id else ""
-                    ),
-                    "tools": [str(tid) for tid in tool_ids],
-                    "agent_type": agent_config["agent_type"],
-                    "prompt_id": prompt_id or agent_config.get("prompt_id", "default"),
-                    "chunks": agent_config.get("chunks", "0"),
-                    "retriever": agent_config.get("retriever", ""),
-                    "status": "template",
-                    "createdAt": datetime.now(timezone.utc),
-                    "updatedAt": datetime.now(timezone.utc),
-                }
-
-                existing = self.agents_collection.find_one(
-                    {"user": self.system_user_id, "name": agent_config["name"]}
-                )
-                if existing:
-                    self.logger.info(f"Updating existing agent: {agent_config['name']}")
-                    self.agents_collection.update_one(
-                        {"_id": existing["_id"]}, {"$set": agent_data}
-                    )
-                    agent_id = existing["_id"]
-                else:
-                    self.logger.info(f"Creating new agent: {agent_config['name']}")
-                    result = self.agents_collection.insert_one(agent_data)
-                    agent_id = result.inserted_id
-                self.logger.info(
-                    f"Successfully processed agent: {agent_config['name']} (ID: {agent_id})"
-                )
-            except Exception as e:
-                self.logger.error(
-                    f"Error processing agent {agent_config['name']}: {str(e)}"
-                )
-                continue
-        self.logger.info("✅ Database seeding completed")
-
-    def _handle_source(self, agent_config: Dict) -> Union[ObjectId, None, bool]:
-        """Handle source ingestion and return source ID"""
-        if not agent_config.get("source"):
-            self.logger.info(
-                "No source provided for agent - will create agent without source"
-            )
-            return None
-        source_config = agent_config["source"]
-        self.logger.info(f"Ingesting source: {source_config['url']}")
-
-        try:
-            existing = self.sources_collection.find_one(
-                {"user": self.system_user_id, "remote_data": source_config["url"]}
-            )
-            if existing:
-                self.logger.info(f"Source already exists: {existing['_id']}")
-                return existing["_id"]
-            # Ingest new source using worker
-
-            task = ingest_remote.delay(
-                source_data=source_config["url"],
-                job_name=source_config["name"],
-                user=self.system_user_id,
-                loader=source_config.get("loader", "url"),
-            )
-
-            result = task.get(timeout=300)
-
-            if not task.successful():
-                raise Exception(f"Source ingestion failed: {result}")
-            source_id = None
-            if isinstance(result, dict) and "id" in result:
-                source_id = result["id"]
-            else:
-                raise Exception(f"Source ingestion result missing 'id': {result}")
-            self.logger.info(f"Source ingested successfully: {source_id}")
-            return source_id
-        except Exception as e:
-            self.logger.error(f"Failed to ingest source: {str(e)}")
-            return False
-
-    def _handle_tools(self, agent_config: Dict) -> List[ObjectId]:
-        """Handle tool creation and return list of tool IDs"""
-        tool_ids = []
-        if not agent_config.get("tools"):
-            return tool_ids
-        for tool_config in agent_config["tools"]:
-            try:
-                tool_name = tool_config["name"]
-                processed_config = self._process_config(tool_config.get("config", {}))
-                self.logger.info(f"Processing tool: {tool_name}")
-
-                existing = self.tools_collection.find_one(
-                    {
-                        "user": self.system_user_id,
-                        "name": tool_name,
-                        "config": processed_config,
-                    }
-                )
-                if existing:
-                    self.logger.info(f"Tool already exists: {existing['_id']}")
-                    tool_ids.append(existing["_id"])
-                    continue
-                tool_data = {
-                    "user": self.system_user_id,
-                    "name": tool_name,
-                    "displayName": tool_config.get("display_name", tool_name),
-                    "description": tool_config.get("description", ""),
-                    "actions": tool_manager.tools[tool_name].get_actions_metadata(),
-                    "config": processed_config,
-                    "status": True,
-                }
-
-                result = self.tools_collection.insert_one(tool_data)
-                tool_ids.append(result.inserted_id)
-                self.logger.info(f"Created new tool: {result.inserted_id}")
-            except Exception as e:
-                self.logger.error(f"Failed to process tool {tool_name}: {str(e)}")
-                continue
-        return tool_ids
-
-    def _handle_prompt(self, agent_config: Dict) -> Optional[str]:
-        """Handle prompt creation and return prompt ID"""
-        if not agent_config.get("prompt"):
-            return None
-
-        prompt_config = agent_config["prompt"]
-        prompt_name = prompt_config.get("name", f"{agent_config['name']} Prompt")
-        prompt_content = prompt_config.get("content", "")
-
-        if not prompt_content:
-            self.logger.warning(
-                f"No prompt content provided for agent {agent_config['name']}"
-            )
-            return None
-
-        self.logger.info(f"Processing prompt: {prompt_name}")
-
-        try:
-            existing = self.prompts_collection.find_one(
-                {
-                    "user": self.system_user_id,
-                    "name": prompt_name,
-                    "content": prompt_content,
-                }
-            )
-            if existing:
-                self.logger.info(f"Prompt already exists: {existing['_id']}")
-                return str(existing["_id"])
-
-            prompt_data = {
-                "name": prompt_name,
-                "content": prompt_content,
-                "user": self.system_user_id,
-            }
-
-            result = self.prompts_collection.insert_one(prompt_data)
-            prompt_id = str(result.inserted_id)
-            self.logger.info(f"Created new prompt: {prompt_id}")
-            return prompt_id
-
-        except Exception as e:
-            self.logger.error(f"Failed to process prompt {prompt_name}: {str(e)}")
-            return None
-
-    def _process_config(self, config: Dict) -> Dict:
-        """Process config values to replace environment variables"""
-        processed = {}
-        for key, value in config.items():
-            if (
-                isinstance(value, str)
-                and value.startswith("${")
-                and value.endswith("}")
-            ):
-                env_var = value[2:-1]
-                processed[key] = os.getenv(env_var, "")
-            else:
-                processed[key] = value
-        return processed
-
-    def _is_already_seeded(self) -> bool:
-        """Check if premade agents already exist"""
-        return self.agents_collection.count_documents({"user": self.system_user_id}) > 0
-
-    @classmethod
-    def initialize_from_env(cls, worker=None):
-        """Factory method to create seeder from environment"""
-        mongo_uri = os.getenv("MONGO_URI", "mongodb://localhost:27017")
-        db_name = os.getenv("MONGO_DB_NAME", "docsgpt")
-        client = MongoClient(mongo_uri)
-        db = client[db_name]
-        return cls(db)

application/storage/local.py

@@ -26,7 +26,7 @@ class LocalStorage(BaseStorage):
             return path
         return os.path.join(self.base_dir, path)
 
-    def save_file(self, file_data: BinaryIO, path: str, **kwargs) -> dict:
+    def save_file(self, file_data: BinaryIO, path: str) -> dict:
         """Save a file to local storage."""
         full_path = self._get_full_path(path)
 

application/tts/elevenlabs.py

@@ -1,31 +1,84 @@
-from io import BytesIO
+import asyncio
+import websockets
+import json
 import base64
+from io import BytesIO
 from application.tts.base import BaseTTS
-from application.core.settings import settings
 
 
 class ElevenlabsTTS(BaseTTS):
-    def __init__(self):
-        from elevenlabs.client import ElevenLabs
-
-        self.client = ElevenLabs(
-            api_key=settings.ELEVENLABS_API_KEY,
-            )
-    
+    def __init__(self):        
+        self.api_key = 'ELEVENLABS_API_KEY'# here you should put your api key
+        self.model = "eleven_flash_v2_5"
+        self.voice = "VOICE_ID" # this is the hash code for the voice not the name!
+        self.write_audio = 1
 
     def text_to_speech(self, text):
-        lang = "en"
-        audio = self.client.text_to_speech.convert(
-            voice_id="nPczCjzI2devNBz1zQrb",             
-            model_id="eleven_multilingual_v2",
-            text=text,
-            output_format="mp3_44100_128"
-        )
-        audio_data = BytesIO()
-        for chunk in audio:
-            audio_data.write(chunk)
-        audio_bytes = audio_data.getvalue()
+        asyncio.run(self._text_to_speech_websocket(text))
 
-        # Encode to base64
-        audio_base64 = base64.b64encode(audio_bytes).decode("utf-8")
-        return audio_base64, lang
+    async def _text_to_speech_websocket(self, text):
+        uri = f"wss://api.elevenlabs.io/v1/text-to-speech/{self.voice}/stream-input?model_id={self.model}"
+        websocket = await websockets.connect(uri)
+        payload = {
+            "text": " ",
+            "voice_settings": {
+                "stability": 0.5,
+                "similarity_boost": 0.8,
+            },
+            "xi_api_key": self.api_key,
+        }
+
+        await websocket.send(json.dumps(payload))
+        
+        async def listen():
+            while 1:
+                try:
+                    msg = await websocket.recv()
+                    data = json.loads(msg)
+
+                    if data.get("audio"):
+                        print("audio received")
+                        yield base64.b64decode(data["audio"])
+                    elif data.get("isFinal"):
+                        break
+                except websockets.exceptions.ConnectionClosed:
+                    print("websocket closed")
+                    break
+        listen_task =  asyncio.create_task(self.stream(listen()))
+        
+        await websocket.send(json.dumps({"text": text}))
+        # this is to signal the end of the text, either use this or flush
+        await websocket.send(json.dumps({"text": ""})) 
+
+        await listen_task
+    
+    async def stream(self, audio_stream):
+        if self.write_audio:
+            audio_bytes = BytesIO()
+            async for chunk in audio_stream:
+                if chunk:
+                    audio_bytes.write(chunk)
+            with open("output_audio.mp3", "wb") as f:
+                f.write(audio_bytes.getvalue())
+        
+        else:
+            async for chunk in audio_stream:
+                pass # depends on the streamer!
+
+
+def test_elevenlabs_websocket():
+    """
+    Tests the ElevenlabsTTS text_to_speech method with a sample prompt.
+    Prints out the base64-encoded result and writes it to 'output_audio.mp3'.
+    """
+    # Instantiate your TTS class
+    tts = ElevenlabsTTS()
+
+    # Call the method with some sample text
+    tts.text_to_speech("Hello from ElevenLabs WebSocket!")
+
+    print("Saved audio to output_audio.mp3.")
+
+
+if __name__ == "__main__":
+    test_elevenlabs_websocket()

application/tts/tts_creator.py

@@ -1,18 +0,0 @@
-from application.tts.google_tts import GoogleTTS
-from application.tts.elevenlabs import ElevenlabsTTS
-from application.tts.base import BaseTTS
-
-
-
-class TTSCreator:
-    tts_providers = {
-        "google_tts": GoogleTTS,
-        "elevenlabs": ElevenlabsTTS,
-    }
-
-    @classmethod
-    def create_tts(cls, tts_type, *args, **kwargs)-> BaseTTS:
-        tts_class = cls.tts_providers.get(tts_type.lower())
-        if not tts_class:
-            raise ValueError(f"No tts class found for type {tts_type}")
-        return tts_class(*args, **kwargs)

application/utils.py

@@ -21,7 +21,7 @@ def get_encoding():
 
 
 def get_gpt_model() -> str:
-    """Get GPT model based on provider"""
+    """Get the appropriate GPT model based on provider"""
     model_map = {
         "openai": "gpt-4o-mini",
         "anthropic": "claude-2",
@@ -32,7 +32,16 @@ def get_gpt_model() -> str:
 
 
 def safe_filename(filename):
-    """Create safe filename, preserving extension. Handles non-Latin characters."""
+    """
+    Creates a safe filename that preserves the original extension.
+    Uses secure_filename, but ensures a proper filename is returned even with non-Latin characters.
+
+    Args:
+        filename (str): The original filename
+
+    Returns:
+        str: A safe filename that can be used for storage
+    """
     if not filename:
         return str(uuid.uuid4())
     _, extension = os.path.splitext(filename)
@@ -74,14 +83,8 @@ def count_tokens_docs(docs):
     return tokens
 
 
-def get_missing_fields(data, required_fields):
-    """Check for missing required fields. Returns list of missing field names."""
-    return [field for field in required_fields if field not in data]
-
-
 def check_required_fields(data, required_fields):
-    """Validate required fields. Returns Flask 400 response if validation fails, None otherwise."""
-    missing_fields = get_missing_fields(data, required_fields)
+    missing_fields = [field for field in required_fields if field not in data]
     if missing_fields:
         return make_response(
             jsonify(
@@ -95,8 +98,7 @@ def check_required_fields(data, required_fields):
     return None
 
 
-def get_field_validation_errors(data, required_fields):
-    """Check for missing and empty fields. Returns dict with 'missing_fields' and 'empty_fields', or None."""
+def validate_required_fields(data, required_fields):
     missing_fields = []
     empty_fields = []
 
@@ -105,24 +107,12 @@ def get_field_validation_errors(data, required_fields):
             missing_fields.append(field)
         elif not data[field]:
             empty_fields.append(field)
-    if missing_fields or empty_fields:
-        return {"missing_fields": missing_fields, "empty_fields": empty_fields}
-    return None
-
-
-def validate_required_fields(data, required_fields):
-    """Validate required fields (must exist and be non-empty). Returns Flask 400 response if validation fails, None otherwise."""
-    errors_dict = get_field_validation_errors(data, required_fields)
-    if errors_dict:
-        errors = []
-        if errors_dict["missing_fields"]:
-            errors.append(
-                f"Missing required fields: {', '.join(errors_dict['missing_fields'])}"
-            )
-        if errors_dict["empty_fields"]:
-            errors.append(
-                f"Empty values in required fields: {', '.join(errors_dict['empty_fields'])}"
-            )
+    errors = []
+    if missing_fields:
+        errors.append(f"Missing required fields: {', '.join(missing_fields)}")
+    if empty_fields:
+        errors.append(f"Empty values in required fields: {', '.join(empty_fields)}")
+    if errors:
         return make_response(
             jsonify({"success": False, "message": " | ".join(errors)}), 400
         )
@@ -134,7 +124,10 @@ def get_hash(data):
 
 
 def limit_chat_history(history, max_token_limit=None, gpt_model="docsgpt"):
-    """Limit chat history to fit within token limit."""
+    """
+    Limits chat history based on token count.
+    Returns a list of messages that fit within the token limit.
+    """
     from application.core.settings import settings
 
     max_token_limit = (
@@ -168,17 +161,13 @@ def limit_chat_history(history, max_token_limit=None, gpt_model="docsgpt"):
 
 
 def validate_function_name(function_name):
-    """Validate function name matches allowed pattern (alphanumeric, underscore, hyphen)."""
+    """Validates if a function name matches the allowed pattern."""
     if not re.match(r"^[a-zA-Z0-9_-]+$", function_name):
         return False
     return True
 
 
 def generate_image_url(image_path):
-    if isinstance(image_path, str) and (
-        image_path.startswith("http://") or image_path.startswith("https://")
-    ):
-        return image_path
     strategy = getattr(settings, "URL_STRATEGY", "backend")
     if strategy == "s3":
         bucket_name = getattr(settings, "S3_BUCKET_NAME", "docsgpt-test-bucket")

application/vectorstore/base.py

@@ -1,43 +1,20 @@
-import logging
-import os
 from abc import ABC, abstractmethod
-
-from langchain_openai import OpenAIEmbeddings
+import os
 from sentence_transformers import SentenceTransformer
-
+from langchain_openai import OpenAIEmbeddings
 from application.core.settings import settings
 
-
 class EmbeddingsWrapper:
     def __init__(self, model_name, *args, **kwargs):
-        logging.info(f"Initializing EmbeddingsWrapper with model: {model_name}")
-        try:
-            kwargs.setdefault("trust_remote_code", True)
-            self.model = SentenceTransformer(
-                model_name,
-                config_kwargs={"allow_dangerous_deserialization": True},
-                *args,
-                **kwargs,
-            )
-            if self.model is None or self.model._first_module() is None:
-                raise ValueError(
-                    f"SentenceTransformer model failed to load properly for: {model_name}"
-                )
-            self.dimension = self.model.get_sentence_embedding_dimension()
-            logging.info(f"Successfully loaded model with dimension: {self.dimension}")
-        except Exception as e:
-            logging.error(
-                f"Failed to initialize SentenceTransformer with model {model_name}: {str(e)}",
-                exc_info=True,
-            )
-            raise
+        self.model = SentenceTransformer(model_name, config_kwargs={'allow_dangerous_deserialization': True}, *args, **kwargs)
+        self.dimension = self.model.get_sentence_embedding_dimension()
 
     def embed_query(self, query: str):
         return self.model.encode(query).tolist()
-
+    
     def embed_documents(self, documents: list):
         return self.model.encode(documents).tolist()
-
+    
     def __call__(self, text):
         if isinstance(text, str):
             return self.embed_query(text)
@@ -47,14 +24,15 @@ class EmbeddingsWrapper:
             raise ValueError("Input must be a string or a list of strings")
 
 
+
 class EmbeddingsSingleton:
     _instances = {}
 
     @staticmethod
     def get_instance(embeddings_name, *args, **kwargs):
         if embeddings_name not in EmbeddingsSingleton._instances:
-            EmbeddingsSingleton._instances[embeddings_name] = (
-                EmbeddingsSingleton._create_instance(embeddings_name, *args, **kwargs)
+            EmbeddingsSingleton._instances[embeddings_name] = EmbeddingsSingleton._create_instance(
+                embeddings_name, *args, **kwargs
             )
         return EmbeddingsSingleton._instances[embeddings_name]
 
@@ -62,15 +40,9 @@ class EmbeddingsSingleton:
     def _create_instance(embeddings_name, *args, **kwargs):
         embeddings_factory = {
             "openai_text-embedding-ada-002": OpenAIEmbeddings,
-            "huggingface_sentence-transformers/all-mpnet-base-v2": lambda: EmbeddingsWrapper(
-                "sentence-transformers/all-mpnet-base-v2"
-            ),
-            "huggingface_sentence-transformers-all-mpnet-base-v2": lambda: EmbeddingsWrapper(
-                "sentence-transformers/all-mpnet-base-v2"
-            ),
-            "huggingface_hkunlp/instructor-large": lambda: EmbeddingsWrapper(
-                "hkunlp/instructor-large"
-            ),
+            "huggingface_sentence-transformers/all-mpnet-base-v2": lambda: EmbeddingsWrapper("sentence-transformers/all-mpnet-base-v2"),
+            "huggingface_sentence-transformers-all-mpnet-base-v2": lambda: EmbeddingsWrapper("sentence-transformers/all-mpnet-base-v2"),
+            "huggingface_hkunlp/instructor-large": lambda: EmbeddingsWrapper("hkunlp/instructor-large"),
         }
 
         if embeddings_name in embeddings_factory:
@@ -78,83 +50,41 @@ class EmbeddingsSingleton:
         else:
             return EmbeddingsWrapper(embeddings_name, *args, **kwargs)
 
-
 class BaseVectorStore(ABC):
     def __init__(self):
         pass
 
     @abstractmethod
     def search(self, *args, **kwargs):
-        """Search for similar documents/chunks in the vectorstore"""
-        pass
-
-    @abstractmethod
-    def add_texts(self, texts, metadatas=None, *args, **kwargs):
-        """Add texts with their embeddings to the vectorstore"""
-        pass
-
-    def delete_index(self, *args, **kwargs):
-        """Delete the entire index/collection"""
-        pass
-
-    def save_local(self, *args, **kwargs):
-        """Save vectorstore to local storage"""
-        pass
-
-    def get_chunks(self, *args, **kwargs):
-        """Get all chunks from the vectorstore"""
-        pass
-
-    def add_chunk(self, text, metadata=None, *args, **kwargs):
-        """Add a single chunk to the vectorstore"""
-        pass
-
-    def delete_chunk(self, chunk_id, *args, **kwargs):
-        """Delete a specific chunk from the vectorstore"""
         pass
 
     def is_azure_configured(self):
-        return (
-            settings.OPENAI_API_BASE
-            and settings.OPENAI_API_VERSION
-            and settings.AZURE_DEPLOYMENT_NAME
-        )
+        return settings.OPENAI_API_BASE and settings.OPENAI_API_VERSION and settings.AZURE_DEPLOYMENT_NAME
 
     def _get_embeddings(self, embeddings_name, embeddings_key=None):
         if embeddings_name == "openai_text-embedding-ada-002":
             if self.is_azure_configured():
                 os.environ["OPENAI_API_TYPE"] = "azure"
                 embedding_instance = EmbeddingsSingleton.get_instance(
-                    embeddings_name, model=settings.AZURE_EMBEDDINGS_DEPLOYMENT_NAME
+                    embeddings_name,
+                    model=settings.AZURE_EMBEDDINGS_DEPLOYMENT_NAME
                 )
             else:
                 embedding_instance = EmbeddingsSingleton.get_instance(
-                    embeddings_name, openai_api_key=embeddings_key
+                    embeddings_name,
+                    openai_api_key=embeddings_key
                 )
         elif embeddings_name == "huggingface_sentence-transformers/all-mpnet-base-v2":
-            possible_paths = [
-                "/app/models/all-mpnet-base-v2",  # Docker absolute path
-                "./models/all-mpnet-base-v2",  # Relative path
-            ]
-            local_model_path = None
-            for path in possible_paths:
-                if os.path.exists(path):
-                    local_model_path = path
-                    logging.info(f"Found local model at path: {path}")
-                    break
-                else:
-                    logging.info(f"Path does not exist: {path}")
-            if local_model_path:
+            if os.path.exists("./models/all-mpnet-base-v2"):
                 embedding_instance = EmbeddingsSingleton.get_instance(
-                    local_model_path,
+                    embeddings_name = "./models/all-mpnet-base-v2",
                 )
             else:
-                logging.warning(
-                    f"Local model not found in any of the paths: {possible_paths}. Falling back to HuggingFace download."
-                )
                 embedding_instance = EmbeddingsSingleton.get_instance(
                     embeddings_name,
                 )
         else:
             embedding_instance = EmbeddingsSingleton.get_instance(embeddings_name)
+
         return embedding_instance
+    

application/worker.py

@@ -19,7 +19,6 @@ from bson.objectid import ObjectId
 from application.agents.agent_creator import AgentCreator
 from application.api.answer.services.stream_processor import get_prompt
 
-from application.cache import get_redis_instance
 from application.core.mongo_db import MongoDB
 from application.core.settings import settings
 from application.parser.chunking import Chunker
@@ -39,7 +38,6 @@ sources_collection = db["sources"]
 
 # Constants
 
-
 MIN_TOKENS = 150
 MAX_TOKENS = 1250
 RECURSION_DEPTH = 2
@@ -216,7 +214,8 @@ def run_agent_logic(agent_config, input_data):
 
 
 def ingest_worker(
-    self, directory, formats, job_name, file_path, filename, user, retriever="classic"
+    self, directory, formats, job_name, file_path, filename, user, 
+    retriever="classic"
 ):
     """
     Ingest and process documents.
@@ -241,7 +240,7 @@ def ingest_worker(
     sample = False
 
     storage = StorageCreator.get_storage()
-
+    
     logging.info(f"Ingest path: {file_path}", extra={"user": user, "job": job_name})
 
     # Create temporary working directory
@@ -254,32 +253,30 @@ def ingest_worker(
                 # Handle directory case
                 logging.info(f"Processing directory: {file_path}")
                 files_list = storage.list_files(file_path)
-
+                
                 for storage_file_path in files_list:
                     if storage.is_directory(storage_file_path):
                         continue
-
+                        
                     # Create relative path structure in temp directory
                     rel_path = os.path.relpath(storage_file_path, file_path)
                     local_file_path = os.path.join(temp_dir, rel_path)
-
+                    
                     os.makedirs(os.path.dirname(local_file_path), exist_ok=True)
-
+                    
                     # Download file
                     try:
                         file_data = storage.get_file(storage_file_path)
                         with open(local_file_path, "wb") as f:
                             f.write(file_data.read())
                     except Exception as e:
-                        logging.error(
-                            f"Error downloading file {storage_file_path}: {e}"
-                        )
+                        logging.error(f"Error downloading file {storage_file_path}: {e}")
                         continue
             else:
                 # Handle single file case
                 temp_filename = os.path.basename(file_path)
                 temp_file_path = os.path.join(temp_dir, temp_filename)
-
+                
                 file_data = storage.get_file(file_path)
                 with open(temp_file_path, "wb") as f:
                     f.write(file_data.read())
@@ -288,10 +285,7 @@ def ingest_worker(
                 if temp_filename.endswith(".zip"):
                     logging.info(f"Extracting zip file: {temp_filename}")
                     extract_zip_recursive(
-                        temp_file_path,
-                        temp_dir,
-                        current_depth=0,
-                        max_depth=RECURSION_DEPTH,
+                        temp_file_path, temp_dir, current_depth=0, max_depth=RECURSION_DEPTH
                     )
 
             self.update_state(state="PROGRESS", meta={"current": 1})
@@ -306,8 +300,8 @@ def ingest_worker(
                 file_metadata=metadata_from_filename,
             )
             raw_docs = reader.load_data()
-
-            directory_structure = getattr(reader, "directory_structure", {})
+            
+            directory_structure = getattr(reader, 'directory_structure', {})
             logging.info(f"Directory structure from reader: {directory_structure}")
 
             chunker = Chunker(
@@ -377,10 +371,7 @@ def reingest_source_worker(self, source_id, user):
     try:
         from application.vectorstore.vector_creator import VectorCreator
 
-        self.update_state(
-            state="PROGRESS",
-            meta={"current": 10, "status": "Initializing re-ingestion scan"},
-        )
+        self.update_state(state="PROGRESS", meta={"current": 10, "status": "Initializing re-ingestion scan"})
 
         source = sources_collection.find_one({"_id": ObjectId(source_id), "user": user})
         if not source:
@@ -389,9 +380,7 @@ def reingest_source_worker(self, source_id, user):
         storage = StorageCreator.get_storage()
         source_file_path = source.get("file_path", "")
 
-        self.update_state(
-            state="PROGRESS", meta={"current": 20, "status": "Scanning current files"}
-        )
+        self.update_state(state="PROGRESS", meta={"current": 20, "status": "Scanning current files"})
 
         with tempfile.TemporaryDirectory() as temp_dir:
             # Download all files from storage to temp directory, preserving directory structure
@@ -402,6 +391,7 @@ def reingest_source_worker(self, source_id, user):
                     if storage.is_directory(storage_file_path):
                         continue
 
+
                     rel_path = os.path.relpath(storage_file_path, source_file_path)
                     local_file_path = os.path.join(temp_dir, rel_path)
 
@@ -413,39 +403,23 @@ def reingest_source_worker(self, source_id, user):
                         with open(local_file_path, "wb") as f:
                             f.write(file_data.read())
                     except Exception as e:
-                        logging.error(
-                            f"Error downloading file {storage_file_path}: {e}"
-                        )
+                        logging.error(f"Error downloading file {storage_file_path}: {e}")
                         continue
 
             reader = SimpleDirectoryReader(
                 input_dir=temp_dir,
                 recursive=True,
                 required_exts=[
-                    ".rst",
-                    ".md",
-                    ".pdf",
-                    ".txt",
-                    ".docx",
-                    ".csv",
-                    ".epub",
-                    ".html",
-                    ".mdx",
-                    ".json",
-                    ".xlsx",
-                    ".pptx",
-                    ".png",
-                    ".jpg",
-                    ".jpeg",
+                    ".rst", ".md", ".pdf", ".txt", ".docx", ".csv", ".epub",
+                    ".html", ".mdx", ".json", ".xlsx", ".pptx", ".png",
+                    ".jpg", ".jpeg",
                 ],
                 exclude_hidden=True,
                 file_metadata=metadata_from_filename,
             )
             reader.load_data()
             directory_structure = reader.directory_structure
-            logging.info(
-                f"Directory structure built with token counts: {directory_structure}"
-            )
+            logging.info(f"Directory structure built with token counts: {directory_structure}")
 
             try:
                 old_directory_structure = source.get("directory_structure") or {}
@@ -459,17 +433,11 @@ def reingest_source_worker(self, source_id, user):
                     files = set()
                     if isinstance(struct, dict):
                         for name, meta in struct.items():
-                            current_path = (
-                                os.path.join(prefix, name) if prefix else name
-                            )
-                            if isinstance(meta, dict) and (
-                                "type" in meta and "size_bytes" in meta
-                            ):
+                            current_path = os.path.join(prefix, name) if prefix else name
+                            if isinstance(meta, dict) and ("type" in meta and "size_bytes" in meta):
                                 files.add(current_path)
                             elif isinstance(meta, dict):
-                                files |= _flatten_directory_structure(
-                                    meta, current_path
-                                )
+                                files |= _flatten_directory_structure(meta, current_path)
                     return files
 
                 old_files = _flatten_directory_structure(old_directory_structure)
@@ -489,9 +457,7 @@ def reingest_source_worker(self, source_id, user):
                     logging.info("No files removed since last ingest.")
 
             except Exception as e:
-                logging.error(
-                    f"Error comparing directory structures: {e}", exc_info=True
-                )
+                logging.error(f"Error comparing directory structures: {e}", exc_info=True)
                 added_files = []
                 removed_files = []
             try:
@@ -511,21 +477,14 @@ def reingest_source_worker(self, source_id, user):
                     settings.EMBEDDINGS_KEY,
                 )
 
-                self.update_state(
-                    state="PROGRESS",
-                    meta={"current": 40, "status": "Processing file changes"},
-                )
+                self.update_state(state="PROGRESS", meta={"current": 40, "status": "Processing file changes"})
 
                 # 1) Delete chunks from removed files
                 deleted = 0
                 if removed_files:
                     try:
                         for ch in vector_store.get_chunks() or []:
-                            metadata = (
-                                ch.get("metadata", {})
-                                if isinstance(ch, dict)
-                                else getattr(ch, "metadata", {})
-                            )
+                            metadata = ch.get("metadata", {}) if isinstance(ch, dict) else getattr(ch, "metadata", {})
                             raw_source = metadata.get("source")
 
                             source_file = str(raw_source) if raw_source else ""
@@ -537,17 +496,10 @@ def reingest_source_worker(self, source_id, user):
                                         vector_store.delete_chunk(cid)
                                         deleted += 1
                                     except Exception as de:
-                                        logging.error(
-                                            f"Failed deleting chunk {cid}: {de}"
-                                        )
-                        logging.info(
-                            f"Deleted {deleted} chunks from {len(removed_files)} removed files"
-                        )
+                                        logging.error(f"Failed deleting chunk {cid}: {de}")
+                        logging.info(f"Deleted {deleted} chunks from {len(removed_files)} removed files")
                     except Exception as e:
-                        logging.error(
-                            f"Error during deletion of removed file chunks: {e}",
-                            exc_info=True,
-                        )
+                        logging.error(f"Error during deletion of removed file chunks: {e}", exc_info=True)
 
                 # 2) Add chunks from new files
                 added = 0
@@ -576,86 +528,58 @@ def reingest_source_worker(self, source_id, user):
                             )
                             chunked_new = chunker_new.chunk(documents=raw_docs_new)
 
-                            for (
-                                file_path,
-                                token_count,
-                            ) in reader_new.file_token_counts.items():
+                            for file_path, token_count in reader_new.file_token_counts.items():
                                 try:
-                                    rel_path = os.path.relpath(
-                                        file_path, start=temp_dir
-                                    )
+                                    rel_path = os.path.relpath(file_path, start=temp_dir)
                                     path_parts = rel_path.split(os.sep)
                                     current_dir = directory_structure
 
                                     for part in path_parts[:-1]:
-                                        if part in current_dir and isinstance(
-                                            current_dir[part], dict
-                                        ):
+                                        if part in current_dir and isinstance(current_dir[part], dict):
                                             current_dir = current_dir[part]
                                         else:
                                             break
 
                                     filename = path_parts[-1]
-                                    if filename in current_dir and isinstance(
-                                        current_dir[filename], dict
-                                    ):
-                                        current_dir[filename][
-                                            "token_count"
-                                        ] = token_count
-                                        logging.info(
-                                            f"Updated token count for {rel_path}: {token_count}"
-                                        )
+                                    if filename in current_dir and isinstance(current_dir[filename], dict):
+                                        current_dir[filename]["token_count"] = token_count
+                                        logging.info(f"Updated token count for {rel_path}: {token_count}")
                                 except Exception as e:
-                                    logging.warning(
-                                        f"Could not update token count for {file_path}: {e}"
-                                    )
+                                    logging.warning(f"Could not update token count for {file_path}: {e}")
 
                             for d in chunked_new:
                                 meta = dict(d.extra_info or {})
                                 try:
                                     raw_src = meta.get("source")
-                                    if isinstance(raw_src, str) and os.path.isabs(
-                                        raw_src
-                                    ):
-                                        meta["source"] = os.path.relpath(
-                                            raw_src, start=temp_dir
-                                        )
+                                    if isinstance(raw_src, str) and os.path.isabs(raw_src):
+                                        meta["source"] = os.path.relpath(raw_src, start=temp_dir)
                                 except Exception:
                                     pass
 
                                 vector_store.add_chunk(d.text, metadata=meta)
                                 added += 1
-                            logging.info(
-                                f"Added {added} chunks from {len(added_files)} new files"
-                            )
+                            logging.info(f"Added {added} chunks from {len(added_files)} new files")
                     except Exception as e:
-                        logging.error(
-                            f"Error during ingestion of new files: {e}", exc_info=True
-                        )
+                        logging.error(f"Error during ingestion of new files: {e}", exc_info=True)
 
                 # 3) Update source directory structure timestamp
                 try:
                     total_tokens = sum(reader.file_token_counts.values())
-
+                    
                     sources_collection.update_one(
                         {"_id": ObjectId(source_id)},
                         {
                             "$set": {
                                 "directory_structure": directory_structure,
                                 "date": datetime.datetime.now(),
-                                "tokens": total_tokens,
+                                "tokens": total_tokens
                             }
                         },
                     )
                 except Exception as e:
-                    logging.error(
-                        f"Error updating directory_structure in DB: {e}", exc_info=True
-                    )
+                    logging.error(f"Error updating directory_structure in DB: {e}", exc_info=True)
 
-                self.update_state(
-                    state="PROGRESS",
-                    meta={"current": 100, "status": "Re-ingestion completed"},
-                )
+                self.update_state(state="PROGRESS", meta={"current": 100, "status": "Re-ingestion completed"})
 
                 return {
                     "source_id": source_id,
@@ -667,16 +591,15 @@ def reingest_source_worker(self, source_id, user):
                     "chunks_deleted": deleted,
                 }
             except Exception as e:
-                logging.error(
-                    f"Error while processing file changes: {e}", exc_info=True
-                )
+                logging.error(f"Error while processing file changes: {e}", exc_info=True)
                 raise
 
+
+
     except Exception as e:
         logging.error(f"Error in reingest_source_worker: {e}", exc_info=True)
         raise
 
-
 def remote_worker(
     self,
     source_data,
@@ -728,7 +651,7 @@ def remote_worker(
             "id": str(id),
             "type": loader,
             "remote_data": source_data,
-            "sync_frequency": sync_frequency,
+            "sync_frequency": sync_frequency
         }
 
         if operation_mode == "sync":
@@ -741,13 +664,7 @@ def remote_worker(
         if os.path.exists(full_path):
             shutil.rmtree(full_path)
     logging.info("remote_worker task completed successfully")
-    return {
-        "id": str(id),
-        "urls": source_data,
-        "name_job": name_job,
-        "user": user,
-        "limited": False,
-    }
+    return {"urls": source_data, "name_job": name_job, "user": user, "limited": False}
 
 
 def sync(
@@ -795,7 +712,7 @@ def sync_worker(self, frequency):
                 self, source_data, name, user, source_type, frequency, retriever, doc_id
             )
             sync_counts["total_sync_count"] += 1
-            sync_counts[
+            sync_counts[ 
                 "sync_success" if resp["status"] == "success" else "sync_failure"
             ] += 1
     return {
@@ -832,14 +749,15 @@ def attachment_worker(self, file_info, user):
                 input_files=[local_path], exclude_hidden=True, errors="ignore"
             )
             .load_data()[0]
-            .text,
+            .text, 
         )
-
+        
+        
         token_count = num_tokens_from_string(content)
         if token_count > 100000:
             content = content[:250000]
             token_count = num_tokens_from_string(content)
-
+        
         self.update_state(
             state="PROGRESS", meta={"current": 80, "status": "Storing in database"}
         )
@@ -954,49 +872,37 @@ def ingest_connector(
         doc_id: Document ID for sync operations (required when operation_mode="sync")
         sync_frequency: How often to sync ("never", "daily", "weekly", "monthly")
     """
-    logging.info(
-        f"Starting remote ingestion from {source_type} for user: {user}, job: {job_name}"
-    )
+    logging.info(f"Starting remote ingestion from {source_type} for user: {user}, job: {job_name}")
     self.update_state(state="PROGRESS", meta={"current": 1})
-
+    
     with tempfile.TemporaryDirectory() as temp_dir:
         try:
             # Step 1: Initialize the appropriate loader
-            self.update_state(
-                state="PROGRESS",
-                meta={"current": 10, "status": "Initializing connector"},
-            )
+            self.update_state(state="PROGRESS", meta={"current": 10, "status": "Initializing connector"})
 
             if not session_token:
                 raise ValueError(f"{source_type} connector requires session_token")
 
             if not ConnectorCreator.is_supported(source_type):
-                raise ValueError(
-                    f"Unsupported connector type: {source_type}. Supported types: {ConnectorCreator.get_supported_connectors()}"
-                )
+                raise ValueError(f"Unsupported connector type: {source_type}. Supported types: {ConnectorCreator.get_supported_connectors()}")
 
-            remote_loader = ConnectorCreator.create_connector(
-                source_type, session_token
-            )
+            remote_loader = ConnectorCreator.create_connector(source_type, session_token)
 
             # Create a clean config for storage
             api_source_config = {
                 "file_ids": file_ids or [],
                 "folder_ids": folder_ids or [],
-                "recursive": recursive,
+                "recursive": recursive
             }
 
             # Step 2: Download files to temp directory
-            self.update_state(
-                state="PROGRESS", meta={"current": 20, "status": "Downloading files"}
-            )
+            self.update_state(state="PROGRESS", meta={"current": 20, "status": "Downloading files"})
             download_info = remote_loader.download_to_directory(
-                temp_dir, api_source_config
+                temp_dir,
+                api_source_config
             )
-
-            if download_info.get("empty_result", False) or not download_info.get(
-                "files_downloaded", 0
-            ):
+            
+            if download_info.get("empty_result", False) or not download_info.get("files_downloaded", 0):
                 logging.warning(f"No files were downloaded from {source_type}")
                 # Create empty result directly instead of calling a separate method
                 return {
@@ -1007,42 +913,28 @@ def ingest_connector(
                     "source_config": api_source_config,
                     "directory_structure": "{}",
                 }
-
+            
             # Step 3: Use SimpleDirectoryReader to process downloaded files
-            self.update_state(
-                state="PROGRESS", meta={"current": 40, "status": "Processing files"}
-            )
+            self.update_state(state="PROGRESS", meta={"current": 40, "status": "Processing files"})
             reader = SimpleDirectoryReader(
                 input_dir=temp_dir,
                 recursive=True,
                 required_exts=[
-                    ".rst",
-                    ".md",
-                    ".pdf",
-                    ".txt",
-                    ".docx",
-                    ".csv",
-                    ".epub",
-                    ".html",
-                    ".mdx",
-                    ".json",
-                    ".xlsx",
-                    ".pptx",
-                    ".png",
-                    ".jpg",
-                    ".jpeg",
+                    ".rst", ".md", ".pdf", ".txt", ".docx", ".csv", ".epub",
+                    ".html", ".mdx", ".json", ".xlsx", ".pptx", ".png",
+                    ".jpg", ".jpeg",
                 ],
                 exclude_hidden=True,
                 file_metadata=metadata_from_filename,
             )
             raw_docs = reader.load_data()
-            directory_structure = getattr(reader, "directory_structure", {})
+            directory_structure = getattr(reader, 'directory_structure', {})
 
+
+            
             # Step 4: Process documents (chunking, embedding, etc.)
-            self.update_state(
-                state="PROGRESS", meta={"current": 60, "status": "Processing documents"}
-            )
-
+            self.update_state(state="PROGRESS", meta={"current": 60, "status": "Processing documents"})
+            
             chunker = Chunker(
                 chunking_strategy="classic_chunk",
                 max_tokens=MAX_TOKENS,
@@ -1050,26 +942,22 @@ def ingest_connector(
                 duplicate_headers=False,
             )
             raw_docs = chunker.chunk(documents=raw_docs)
-
+            
             # Preserve source information in document metadata
             for doc in raw_docs:
-                if hasattr(doc, "extra_info") and doc.extra_info:
-                    source = doc.extra_info.get("source")
+                if hasattr(doc, 'extra_info') and doc.extra_info:
+                    source = doc.extra_info.get('source')
                     if source and os.path.isabs(source):
                         # Convert absolute path to relative path
-                        doc.extra_info["source"] = os.path.relpath(
-                            source, start=temp_dir
-                        )
-
+                        doc.extra_info['source'] = os.path.relpath(source, start=temp_dir)
+            
             docs = [Document.to_langchain_format(raw_doc) for raw_doc in raw_docs]
-
+            
             if operation_mode == "upload":
                 id = ObjectId()
             elif operation_mode == "sync":
                 if not doc_id or not ObjectId.is_valid(doc_id):
-                    logging.error(
-                        "Invalid doc_id provided for sync operation: %s", doc_id
-                    )
+                    logging.error("Invalid doc_id provided for sync operation: %s", doc_id)
                     raise ValueError("doc_id must be provided for sync operation.")
                 id = ObjectId(doc_id)
             else:
@@ -1078,9 +966,7 @@ def ingest_connector(
             vector_store_path = os.path.join(temp_dir, "vector_store")
             os.makedirs(vector_store_path, exist_ok=True)
 
-            self.update_state(
-                state="PROGRESS", meta={"current": 80, "status": "Storing documents"}
-            )
+            self.update_state(state="PROGRESS", meta={"current": 80, "status": "Storing documents"})
             embed_and_store_documents(docs, vector_store_path, id, self)
 
             tokens = count_tokens_docs(docs)
@@ -1092,12 +978,13 @@ def ingest_connector(
                 "tokens": tokens,
                 "retriever": retriever,
                 "id": str(id),
-                "type": "connector:file",
-                "remote_data": json.dumps(
-                    {"provider": source_type, **api_source_config}
-                ),
+                "type": "connector",
+                "remote_data": json.dumps({
+                    "provider": source_type,
+                    **api_source_config
+                }),
                 "directory_structure": json.dumps(directory_structure),
-                "sync_frequency": sync_frequency,
+                "sync_frequency": sync_frequency 
             }
 
             if operation_mode == "sync":
@@ -1108,9 +995,7 @@ def ingest_connector(
             upload_index(vector_store_path, file_data)
 
             # Ensure we mark the task as complete
-            self.update_state(
-                state="PROGRESS", meta={"current": 100, "status": "Complete"}
-            )
+            self.update_state(state="PROGRESS", meta={"current": 100, "status": "Complete"})
 
             logging.info(f"Remote ingestion completed: {job_name}")
 
@@ -1120,136 +1005,9 @@ def ingest_connector(
                 "tokens": tokens,
                 "type": source_type,
                 "id": str(id),
-                "status": "complete",
+                "status": "complete"
             }
-
+            
         except Exception as e:
             logging.error(f"Error during remote ingestion: {e}", exc_info=True)
             raise
-
-
-def mcp_oauth(self, config: Dict[str, Any], user_id: str = None) -> Dict[str, Any]:
-    """Worker to handle MCP OAuth flow asynchronously."""
-
-    logging.info(
-        "[MCP OAuth] Worker started for user_id=%s, config=%s", user_id, config
-    )
-    try:
-        import asyncio
-
-        from application.agents.tools.mcp_tool import MCPTool
-
-        task_id = self.request.id
-        logging.info("[MCP OAuth] Task ID: %s", task_id)
-        redis_client = get_redis_instance()
-
-        def update_status(status_data: Dict[str, Any]):
-            logging.info("[MCP OAuth] Updating status: %s", status_data)
-            status_key = f"mcp_oauth_status:{task_id}"
-            redis_client.setex(status_key, 600, json.dumps(status_data))
-
-        update_status(
-            {
-                "status": "in_progress",
-                "message": "Starting OAuth flow...",
-                "task_id": task_id,
-            }
-        )
-
-        tool_config = config.copy()
-        tool_config["oauth_task_id"] = task_id
-        logging.info("[MCP OAuth] Initializing MCPTool with config: %s", tool_config)
-        mcp_tool = MCPTool(tool_config, user_id)
-
-        async def run_oauth_discovery():
-            if not mcp_tool._client:
-                mcp_tool._setup_client()
-            return await mcp_tool._execute_with_client("list_tools")
-
-        update_status(
-            {
-                "status": "awaiting_redirect",
-                "message": "Waiting for OAuth redirect...",
-                "task_id": task_id,
-            }
-        )
-
-        loop = asyncio.new_event_loop()
-        asyncio.set_event_loop(loop)
-
-        try:
-            logging.info("[MCP OAuth] Starting event loop for OAuth discovery...")
-            tools_response = loop.run_until_complete(run_oauth_discovery())
-            logging.info(
-                "[MCP OAuth] Tools response after async call: %s", tools_response
-            )
-
-            status_key = f"mcp_oauth_status:{task_id}"
-            redis_status = redis_client.get(status_key)
-            if redis_status:
-                logging.info(
-                    "[MCP OAuth] Redis status after async call: %s", redis_status
-                )
-            else:
-                logging.warning(
-                    "[MCP OAuth] No Redis status found after async call for key: %s",
-                    status_key,
-                )
-            tools = mcp_tool.get_actions_metadata()
-
-            update_status(
-                {
-                    "status": "completed",
-                    "message": f"OAuth completed successfully. Found {len(tools)} tools.",
-                    "tools": tools,
-                    "tools_count": len(tools),
-                    "task_id": task_id,
-                }
-            )
-
-            logging.info(
-                "[MCP OAuth] OAuth flow completed successfully for task_id=%s", task_id
-            )
-            return {"success": True, "tools": tools, "tools_count": len(tools)}
-        except Exception as e:
-            error_msg = f"OAuth flow failed: {str(e)}"
-            logging.error(
-                "[MCP OAuth] Exception in OAuth discovery: %s", error_msg, exc_info=True
-            )
-            update_status(
-                {
-                    "status": "error",
-                    "message": error_msg,
-                    "error": str(e),
-                    "task_id": task_id,
-                }
-            )
-            return {"success": False, "error": error_msg}
-        finally:
-            logging.info("[MCP OAuth] Closing event loop for task_id=%s", task_id)
-            loop.close()
-    except Exception as e:
-        error_msg = f"Failed to initialize OAuth flow: {str(e)}"
-        logging.error(
-            "[MCP OAuth] Exception during initialization: %s", error_msg, exc_info=True
-        )
-        update_status(
-            {
-                "status": "error",
-                "message": error_msg,
-                "error": str(e),
-                "task_id": task_id,
-            }
-        )
-        return {"success": False, "error": error_msg}
-
-
-def mcp_oauth_status(self, task_id: str) -> Dict[str, Any]:
-    """Check the status of an MCP OAuth flow."""
-    redis_client = get_redis_instance()
-    status_key = f"mcp_oauth_status:{task_id}"
-
-    status_data = redis_client.get(status_key)
-    if status_data:
-        return json.loads(status_data)
-    return {"status": "not_found", "message": "Status not found"}

deployment/docker-compose-hub.yaml

@@ -6,7 +6,6 @@ services:
     environment:
       - VITE_API_HOST=http://localhost:7091
       - VITE_API_STREAMING=$VITE_API_STREAMING
-      - VITE_GOOGLE_CLIENT_ID=$VITE_GOOGLE_CLIENT_ID
     ports:
       - "5173:5173"
     depends_on:
@@ -72,4 +71,4 @@ services:
       - mongodb_data_container:/data/db
 
 volumes:
-  mongodb_data_container:
+  mongodb_data_container:

deployment/docker-compose.yaml

@@ -7,7 +7,6 @@ services:
     environment:
       - VITE_API_HOST=http://localhost:7091
       - VITE_API_STREAMING=$VITE_API_STREAMING
-      - VITE_GOOGLE_CLIENT_ID=$VITE_GOOGLE_CLIENT_ID
     ports:
       - "5173:5173"
     depends_on:

docs/pages/Agents/basics.mdx

@@ -107,13 +107,3 @@ Once an agent is created, you can:
     * Modify any of its configuration settings (name, description, source, prompt, tools, type).
     * **Generate a Public Link:** From the edit screen, you can create a shareable public link that allows others to import and use your agent.
     * **Get a Webhook URL:** You can also obtain a Webhook URL for the agent. This allows external applications or services to trigger the agent and receive responses programmatically, enabling powerful integrations and automations.
-
-## Seeding Premade Agents from YAML
-
-You can bootstrap a fresh DocsGPT deployment with a curated set of agents by seeding them directly into MongoDB.
-
-1. **Customize the configuration** – edit `application/seed/config/premade_agents.yaml` (or copy from `application/seed/config/agents_template.yaml`) to describe the agents you want to provision. Each entry lets you define prompts, tools, and optional data sources.
-2. **Ensure dependencies are running** – MongoDB must be reachable using the credentials in `.env`, and a Celery worker should be available if any agent sources need to be ingested via `ingest_remote`.
-3. **Execute the seeder** – run `python -m application.seed.commands init`. Add `--force` when you need to reseed an existing environment.
-
-The seeder keeps templates under the `system` user so they appear in the UI for anyone to clone or customize. Environment variable placeholders such as `${MY_TOKEN}` inside tool configs are resolved during the seeding process.

docs/pages/Deploying/Development-Environment.mdx

@@ -42,7 +42,7 @@ To run the DocsGPT backend locally, you'll need to set up a Python environment a
 
     *   **Option 1: Using a `.env` file (Recommended):**
         *   If you haven't already, create a file named `.env` in the **root directory** of your DocsGPT project.
-        *   Modify the `.env` file to adjust settings as needed. You can find a comprehensive list of configurable options in [`application/core/settings.py`](https://github.com/arc53/DocsGPT/blob/main/application/core/settings.py).
+        *   Modify the `.env` file to adjust settings as needed. You can find a comprehensive list of configurable options in [`application/core/settings.py`](application/core/settings.py).
 
     *   **Option 2: Exporting Environment Variables:**
         *   Alternatively, you can export environment variables directly in your terminal. However, using a `.env` file is generally more organized for development.
@@ -67,7 +67,7 @@ To run the DocsGPT backend locally, you'll need to set up a Python environment a
 
 3.  **Download Embedding Model:**
 
-    The backend requires an embedding model. Download the `mpnet-base-v2` model and place it in the `models/` directory within the project root. You can use the following script:
+    The backend requires an embedding model. Download the `mpnet-base-v2` model and place it in the `model/` directory within the project root. You can use the following script:
 
     ```bash
     wget https://d3dg1063dc54p9.cloudfront.net/models/embeddings/mpnet-base-v2.zip
@@ -75,7 +75,7 @@ To run the DocsGPT backend locally, you'll need to set up a Python environment a
     rm mpnet-base-v2.zip
     ```
 
-    Alternatively, you can manually download the zip file from [here](https://d3dg1063dc54p9.cloudfront.net/models/embeddings/mpnet-base-v2.zip), unzip it, and place the extracted folder in `models/`.
+    Alternatively, you can manually download the zip file from [here](https://d3dg1063dc54p9.cloudfront.net/models/embeddings/mpnet-base-v2.zip), unzip it, and place the extracted folder in `model/`.
 
 4.  **Install Backend Dependencies:**
 
@@ -160,4 +160,4 @@ To run the DocsGPT frontend locally, you'll need Node.js and npm (Node Package M
 
     This command will start the Vite development server. The frontend application will typically be accessible at [http://localhost:5173/](http://localhost:5173/). The terminal will display the exact URL where the frontend is running.
 
-With both the backend and frontend running, you should now have a fully functional DocsGPT development environment. You can access the application in your browser at [http://localhost:5173/](http://localhost:5173/) and start developing!
+With both the backend and frontend running, you should now have a fully functional DocsGPT development environment. You can access the application in your browser at [http://localhost:5173/](http://localhost:5173/) and start developing!

docs/pages/Guides/Integrations/_meta.json

@@ -1,6 +0,0 @@
-{
-  "google-drive-connector": {
-    "title": "🔗 Google Drive",
-    "href": "/Guides/Integrations/google-drive-connector"
-  }
-}

docs/pages/Guides/Integrations/google-drive-connector.mdx

@@ -1,212 +0,0 @@
----
-title: Google Drive Connector
-description: Connect your Google Drive as an external knowledge base to upload and process files directly from your Google Drive account.
----
-
-import { Callout } from 'nextra/components'
-import { Steps } from 'nextra/components'
-
-# Google Drive Connector
-
-The Google Drive Connector allows you to seamlessly connect your Google Drive account as an external knowledge base. This integration enables you to upload and process files directly from your Google Drive without manually downloading and uploading them to DocsGPT.
-
-## Features
-
-- **Direct File Access**: Browse and select files directly from your Google Drive
-- **Comprehensive File Support**: Supports all major document formats including:
-  - Google Workspace files (Docs, Sheets, Slides)
-  - Microsoft Office files (.docx, .xlsx, .pptx, .doc, .ppt, .xls)
-  - PDF documents
-  - Text files (.txt, .md, .rst, .html, .rtf)
-  - Data files (.csv, .json)
-  - Image files (.png, .jpg, .jpeg)
-  - E-books (.epub)
-- **Secure Authentication**: Uses OAuth 2.0 for secure access to your Google Drive
-- **Real-time Sync**: Process files directly from Google Drive without local downloads
-
-<Callout type="info" emoji="ℹ️">
-The Google Drive Connector requires proper configuration of Google API credentials. Follow the setup instructions below to enable this feature.
-</Callout>
-
-## Prerequisites
-
-Before setting up the Google Drive Connector, you'll need:
-
-1. A Google Cloud Platform (GCP) project
-2. Google Drive API enabled
-3. OAuth 2.0 credentials configured
-4. DocsGPT instance with proper environment variables
-
-## Setup Instructions
-
-<Steps>
-
-### Step 1: Create a Google Cloud Project
-
-1. Go to the [Google Cloud Console](https://console.cloud.google.com/)
-2. Create a new project or select an existing one
-3. Note down your Project ID for later use
-
-### Step 2: Enable Google Drive API
-
-1. In the Google Cloud Console, navigate to **APIs & Services** > **Library**
-2. Search for "Google Drive API"
-3. Click on "Google Drive API" and click **Enable**
-
-### Step 3: Create OAuth 2.0 Credentials
-
-1. Go to **APIs & Services** > **Credentials**
-2. Click **Create Credentials** > **OAuth client ID**
-3. If prompted, configure the OAuth consent screen:
-   - Choose **External** user type (unless you're using Google Workspace)
-   - Fill in the required fields (App name, User support email, Developer contact)
-   - Add your domain to **Authorized domains** if deploying publicly
-4. For Application type, select **Web application**
-5. Add your DocsGPT frontend URL to **Authorized JavaScript origins**:
-   - For local development: `http://localhost:3000`
-   - For production: `https://yourdomain.com`
-6. Add your DocsGPT callback URL to **Authorized redirect URIs**:
-   - For local development: `http://localhost:7091/api/connectors/callback?provider=google_drive`
-   - For production: `https://yourdomain.com/api/connectors/callback?provider=google_drive`
-7. Click **Create** and note down the **Client ID** and **Client Secret**
-
-
-
-### Step 4: Configure Backend Environment Variables
-
-Add the following environment variables to your backend configuration:
-
-**For Docker deployment**, add to your `.env` file in the root directory:
-
-```env
-# Google Drive Connector Configuration
-GOOGLE_CLIENT_ID=your_google_client_id_here
-GOOGLE_CLIENT_SECRET=your_google_client_secret_here
-```
-
-**For manual deployment**, set these environment variables in your system or application configuration.
-
-### Step 5: Configure Frontend Environment Variables
-
-Add the following environment variables to your frontend `.env` file:
-
-```env
-# Google Drive Frontend Configuration
-VITE_GOOGLE_CLIENT_ID=your_google_client_id_here
-```
-
-<Callout type="warning" emoji="⚠️">
-Make sure to use the same Google Client ID in both backend and frontend configurations.
-</Callout>
-
-### Step 6: Restart Your Application
-
-After configuring the environment variables:
-
-1. **For Docker**: Restart your Docker containers
-   ```bash
-   docker-compose down
-   docker-compose up -d
-   ```
-
-2. **For manual deployment**: Restart both backend and frontend services
-
-</Steps>
-
-## Using the Google Drive Connector
-
-Once configured, you can use the Google Drive Connector to upload files:
-
-<Steps>
-
-### Step 1: Access the Upload Interface
-
-1. Navigate to the DocsGPT interface
-2. Go to the upload/training section
-3. You should now see "Google Drive" as an available upload option
-
-### Step 2: Connect Your Google Account
-
-1. Select "Google Drive" as your upload method
-2. Click "Connect to Google Drive"
-3. You'll be redirected to Google's OAuth consent screen
-4. Grant the necessary permissions to DocsGPT
-5. You'll be redirected back to DocsGPT with a successful connection
-
-### Step 3: Select Files
-
-1. Once connected, click "Select Files"
-2. The Google Drive picker will open
-3. Browse your Google Drive and select the files you want to process
-4. Click "Select" to confirm your choices
-
-### Step 4: Process Files
-
-1. Review your selected files
-2. Click "Train" or "Upload" to process the files
-3. DocsGPT will download and process the files from your Google Drive
-4. Once processing is complete, the files will be available in your knowledge base
-
-</Steps>
-
-## Supported File Types
-
-The Google Drive Connector supports the following file types:
-
-| File Type | Extensions | Description |
-|-----------|------------|-------------|
-| **Google Workspace** | - | Google Docs, Sheets, Slides (automatically converted) |
-| **Microsoft Office** | .docx, .xlsx, .pptx | Modern Office formats |
-| **Legacy Office** | .doc, .ppt, .xls | Older Office formats |
-| **PDF Documents** | .pdf | Portable Document Format |
-| **Text Files** | .txt, .md, .rst, .html, .rtf | Various text formats |
-| **Data Files** | .csv, .json | Structured data formats |
-| **Images** | .png, .jpg, .jpeg | Image files (with OCR if enabled) |
-| **E-books** | .epub | Electronic publication format |
-
-## Troubleshooting
-
-### Common Issues
-
-**"Google Drive option not appearing"**
-- Verify that `VITE_GOOGLE_CLIENT_ID` is set in frontend environment
-- Check that `VITE_GOOGLE_CLIENT_ID` environment variable is present in your frontend configuration
-- Check browser console for any JavaScript errors
-- Ensure the frontend has been restarted after adding environment variables
-
-**"Authentication failed"**
-- Verify that your OAuth 2.0 credentials are correctly configured
-- Check that the redirect URI `http://<your-domain>/api/connectors/callback?provider=google_drive` is correctly added in GCP console
-- Ensure the Google Drive API is enabled in your GCP project
-
-**"Permission denied" errors**
-- Verify that the OAuth consent screen is properly configured
-- Check that your Google account has access to the files you're trying to select
-- Ensure the required scopes are granted during authentication
-
-**"Files not processing"**
-- Check that the backend environment variables are correctly set
-- Verify that the OAuth credentials have the necessary permissions
-- Check the backend logs for any error messages
-
-### Environment Variable Checklist
-
-**Backend (.env in root directory):**
-- ✅ `GOOGLE_CLIENT_ID`
-- ✅ `GOOGLE_CLIENT_SECRET`
-
-**Frontend (.env in frontend directory):**
-- ✅ `VITE_GOOGLE_CLIENT_ID`
-
-### Security Considerations
-
-- Keep your Google Client Secret secure and never expose it in frontend code
-- Regularly rotate your OAuth credentials
-- Use HTTPS in production to protect authentication tokens
-- Ensure proper OAuth consent screen configuration for production use
-
-<Callout type="tip" emoji="💡">
-For production deployments, make sure to add your actual domain to the OAuth consent screen and authorized origins/redirect URIs.
-</Callout>
-
-

docs/pages/Guides/_meta.json

@@ -20,8 +20,5 @@
   "Architecture": {
     "title": "🏗️ Architecture",
     "href": "/Guides/Architecture"
-  },
-  "Integrations": {
-    "title": "🔗 Integrations"
   }
 }

docs/pages/quickstart.mdx

@@ -43,8 +43,7 @@ The easiest way to launch DocsGPT is using the provided `setup.sh` script. This
    2) Serve Local (with Ollama)
    3) Connect Local Inference Engine
    4) Connect Cloud API Provider
-   5) Advanced: Build images locally (for developers)
-   Choose option (1-5):
+   Choose option (1-4):
    ```
 
    Let's break down each option:
@@ -57,8 +56,6 @@ The easiest way to launch DocsGPT is using the provided `setup.sh` script. This
 
    * **4) Connect Cloud API Provider:** This option lets you connect DocsGPT to a commercial Cloud API provider such as OpenAI, Google (Vertex AI/Gemini), Anthropic (Claude), Groq, HuggingFace Inference API, or Azure OpenAI. You will need an API key from your chosen provider. Select this if you prefer to use a powerful cloud-based LLM.
 
-   * **5) Modify DocsGPT's source code and rebuild the Docker images locally. Instead of pulling prebuilt images from Docker Hub or using the hosted/public API, you build the entire backend and frontend from source, customizing how DocsGPT works internally, or run it in an environment without internet access.
-
    After selecting an option and providing any required information (like API keys or model names), the script will configure your `.env` file and start DocsGPT using Docker Compose.
 
 4. **Access DocsGPT in your browser:**

frontend/.env.development

@@ -1,6 +1,4 @@
 # Please put appropriate value
 VITE_BASE_URL=http://localhost:5173
 VITE_API_HOST=http://127.0.0.1:7091
-VITE_API_STREAMING=true
-VITE_NOTIFICATION_TEXT="What's new in 0.14.0 — Changelog"
-VITE_NOTIFICATION_LINK="#"
+VITE_API_STREAMING=true

frontend/package-lock.json

@@ -12,16 +12,15 @@
         "chart.js": "^4.4.4",
         "clsx": "^2.1.1",
         "copy-to-clipboard": "^3.3.3",
-        "i18next": "^25.5.3",
+        "i18next": "^24.2.0",
         "i18next-browser-languagedetector": "^8.0.2",
         "lodash": "^4.17.21",
-        "mermaid": "^11.12.0",
+        "mermaid": "^11.6.0",
         "prop-types": "^15.8.1",
         "react": "^19.1.0",
         "react-chartjs-2": "^5.3.0",
         "react-dom": "^19.0.0",
         "react-dropzone": "^14.3.8",
-        "react-google-drive-picker": "^1.2.2",
         "react-i18next": "^15.4.0",
         "react-markdown": "^9.0.1",
         "react-redux": "^9.2.0",
@@ -90,22 +89,22 @@
       }
     },
     "node_modules/@antfu/install-pkg": {
-      "version": "1.1.0",
-      "resolved": "https://registry.npmjs.org/@antfu/install-pkg/-/install-pkg-1.1.0.tgz",
-      "integrity": "sha512-MGQsmw10ZyI+EJo45CdSER4zEb+p31LpDAFp2Z3gkSd1yqVZGi0Ebx++YTEMonJy4oChEMLsxZ64j8FH6sSqtQ==",
+      "version": "1.0.0",
+      "resolved": "https://registry.npmjs.org/@antfu/install-pkg/-/install-pkg-1.0.0.tgz",
+      "integrity": "sha512-xvX6P/lo1B3ej0OsaErAjqgFYzYVcJpamjLAFLYh9vRJngBrMoUG7aVnrGTeqM7yxbyTD5p3F2+0/QUEh8Vzhw==",
       "license": "MIT",
       "dependencies": {
-        "package-manager-detector": "^1.3.0",
-        "tinyexec": "^1.0.1"
+        "package-manager-detector": "^0.2.8",
+        "tinyexec": "^0.3.2"
       },
       "funding": {
         "url": "https://github.com/sponsors/antfu"
       }
     },
     "node_modules/@antfu/utils": {
-      "version": "9.3.0",
-      "resolved": "https://registry.npmjs.org/@antfu/utils/-/utils-9.3.0.tgz",
-      "integrity": "sha512-9hFT4RauhcUzqOE4f1+frMKLZrgNog5b06I7VmZQV1BkvwvqrbC8EBZf3L1eEL2AKb6rNKjER0sEvJiSP1FXEA==",
+      "version": "8.1.1",
+      "resolved": "https://registry.npmjs.org/@antfu/utils/-/utils-8.1.1.tgz",
+      "integrity": "sha512-Mex9nXf9vR6AhcXmMrlz/HVgYYZpVGJ6YlPgwl7UnaFpnshXs6EK/oa5Gpf3CzENMjkvEx2tQtntGnb7UtSTOQ==",
       "license": "MIT",
       "funding": {
         "url": "https://github.com/sponsors/antfu"
@@ -321,9 +320,9 @@
       }
     },
     "node_modules/@babel/runtime": {
-      "version": "7.28.4",
-      "resolved": "https://registry.npmjs.org/@babel/runtime/-/runtime-7.28.4.tgz",
-      "integrity": "sha512-Q/N6JNWvIvPnLDvjlE1OUBLPQHH6l3CltCEsHIujp45zQUSSh8K+gHnaEX45yAT1nyngnINhvWtzN+Nb9D8RAQ==",
+      "version": "7.27.3",
+      "resolved": "https://registry.npmjs.org/@babel/runtime/-/runtime-7.27.3.tgz",
+      "integrity": "sha512-7EYtGezsdiDMyY80+65EzwiGmcJqpmcZCojSXaRgdrBaGtWTgDZKq69cPIVped6MkIM78cTQ2GOiEYjwOlG4xw==",
       "license": "MIT",
       "engines": {
         "node": ">=6.9.0"
@@ -957,18 +956,18 @@
       "license": "MIT"
     },
     "node_modules/@iconify/utils": {
-      "version": "3.0.2",
-      "resolved": "https://registry.npmjs.org/@iconify/utils/-/utils-3.0.2.tgz",
-      "integrity": "sha512-EfJS0rLfVuRuJRn4psJHtK2A9TqVnkxPpHY6lYHiB9+8eSuudsxbwMiavocG45ujOo6FJ+CIRlRnlOGinzkaGQ==",
+      "version": "2.3.0",
+      "resolved": "https://registry.npmjs.org/@iconify/utils/-/utils-2.3.0.tgz",
+      "integrity": "sha512-GmQ78prtwYW6EtzXRU1rY+KwOKfz32PD7iJh6Iyqw68GiKuoZ2A6pRtzWONz5VQJbp50mEjXh/7NkumtrAgRKA==",
       "license": "MIT",
       "dependencies": {
-        "@antfu/install-pkg": "^1.1.0",
-        "@antfu/utils": "^9.2.0",
+        "@antfu/install-pkg": "^1.0.0",
+        "@antfu/utils": "^8.1.0",
         "@iconify/types": "^2.0.0",
-        "debug": "^4.4.1",
-        "globals": "^15.15.0",
+        "debug": "^4.4.0",
+        "globals": "^15.14.0",
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-        "local-pkg": "^1.1.1",
+        "local-pkg": "^1.0.0",
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@@ -1053,9 +1052,9 @@
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+      "resolved": "https://registry.npmjs.org/@mermaid-js/parser/-/parser-0.4.0.tgz",
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@@ -2856,9 +2855,9 @@
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-      "resolved": "https://registry.npmjs.org/acorn/-/acorn-8.15.0.tgz",
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+      "version": "8.14.1",
+      "resolved": "https://registry.npmjs.org/acorn/-/acorn-8.14.1.tgz",
+      "integrity": "sha512-OvQ/2pUDKmgfCg++xsTX1wGxfTaszcHVcTctW4UJB4hibJx2HXxxO5UmVgyjMa+ZDsiaf5wWLXYpRWMmBI0QHg==",
       "license": "MIT",
       "bin": {
         "acorn": "bin/acorn"
@@ -4141,16 +4140,15 @@
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-      "version": "1.11.18",
-      "resolved": "https://registry.npmjs.org/dayjs/-/dayjs-1.11.18.tgz",
-      "integrity": "sha512-zFBQ7WFRvVRhKcWoUh+ZA1g2HVgUbsZm9sbddh8EC5iv93sui8DVVz1Npvz+r6meo9VKfa8NyLWBsQK1VvIKPA==",
+      "version": "1.11.13",
+      "resolved": "https://registry.npmjs.org/dayjs/-/dayjs-1.11.13.tgz",
+      "integrity": "sha512-oaMBel6gjolK862uaPQOVTA7q3TZhuSvuMQAAglQDOWYO9A91IrAOUJEyKVlqJlHE0vq5p5UXxzdPfMH/x6xNg==",
       "license": "MIT"
     },
     "node_modules/debug": {
-      "version": "4.4.3",
-      "resolved": "https://registry.npmjs.org/debug/-/debug-4.4.3.tgz",
-      "integrity": "sha512-RGwwWnwQvkVfavKVt22FGLw+xYSdzARwm0ru6DhTVA3umU5hZc28V3kO4stgYryrTlLpuvgI9GiijltAjNbcqA==",
-      "license": "MIT",
+      "version": "4.4.0",
+      "resolved": "https://registry.npmjs.org/debug/-/debug-4.4.0.tgz",
+      "integrity": "sha512-6WTZ/IxCY/T6BALoZHaE4ctp9xm+Z5kY/pzYaCHRFeyVhojxlrm+46y68HA6hr0TcwEssoxNiDEUJQjfPZ/RYA==",
       "dependencies": {
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       },
@@ -5327,9 +5325,9 @@
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-      "version": "1.0.7",
-      "resolved": "https://registry.npmjs.org/exsolve/-/exsolve-1.0.7.tgz",
-      "integrity": "sha512-VO5fQUzZtI6C+vx4w/4BWJpg3s/5l+6pRQEHzFRM8WFi4XffSP1Z+4qi7GbjWbvRQEbdIco5mIMq+zX4rPuLrw==",
+      "version": "1.0.4",
+      "resolved": "https://registry.npmjs.org/exsolve/-/exsolve-1.0.4.tgz",
+      "integrity": "sha512-xsZH6PXaER4XoV+NiT7JHp1bJodJVT+cxeSH1G0f0tlT0lJqYuHUP3bUx2HtfTDvOagMINYp8rsqusxud3RXhw==",
       "license": "MIT"
     },
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@@ -6218,9 +6216,9 @@
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-      "version": "25.5.3",
-      "resolved": "https://registry.npmjs.org/i18next/-/i18next-25.5.3.tgz",
-      "integrity": "sha512-joFqorDeQ6YpIXni944upwnuHBf5IoPMuqAchGVeQLdWC2JOjxgM9V8UGLhNIIH/Q8QleRxIi0BSRQehSrDLcg==",
+      "version": "24.2.0",
+      "resolved": "https://registry.npmjs.org/i18next/-/i18next-24.2.0.tgz",
+      "integrity": "sha512-ArJJTS1lV6lgKH7yEf4EpgNZ7+THl7bsGxxougPYiXRTJ/Fe1j08/TBpV9QsXCIYVfdE/HWG/xLezJ5DOlfBOA==",
       "funding": [
         {
           "type": "individual",
@@ -6235,9 +6233,8 @@
           "url": "https://www.i18next.com/how-to/faq#i18next-is-awesome.-how-can-i-support-the-project"
         }
       ],
-      "license": "MIT",
       "dependencies": {
-        "@babel/runtime": "^7.27.6"
+        "@babel/runtime": "^7.23.2"
       },
       "peerDependencies": {
         "typescript": "^5"
@@ -6910,14 +6907,13 @@
       }
     },
     "node_modules/katex": {
-      "version": "0.16.23",
-      "resolved": "https://registry.npmjs.org/katex/-/katex-0.16.23.tgz",
-      "integrity": "sha512-7VlC1hsEEolL9xNO05v9VjrvWZePkCVBJqj8ruICxYjZfHaHbaU53AlP+PODyFIXEnaEIEWi3wJy7FPZ95JAVg==",
+      "version": "0.16.21",
+      "resolved": "https://registry.npmjs.org/katex/-/katex-0.16.21.tgz",
+      "integrity": "sha512-XvqR7FgOHtWupfMiigNzmh+MgUVmDGU2kXZm899ZkPfcuoPuFxyHmXsgATDpFZDAXCI8tvinaVcDo8PIIJSo4A==",
       "funding": [
         "https://opencollective.com/katex",
         "https://github.com/sponsors/katex"
       ],
-      "license": "MIT",
       "dependencies": {
         "commander": "^8.3.0"
       },
@@ -7282,14 +7278,14 @@
       }
     },
     "node_modules/local-pkg": {
-      "version": "1.1.2",
-      "resolved": "https://registry.npmjs.org/local-pkg/-/local-pkg-1.1.2.tgz",
-      "integrity": "sha512-arhlxbFRmoQHl33a0Zkle/YWlmNwoyt6QNZEIJcqNbdrsix5Lvc4HyyI3EnwxTYlZYc32EbYrQ8SzEZ7dqgg9A==",
+      "version": "1.1.1",
+      "resolved": "https://registry.npmjs.org/local-pkg/-/local-pkg-1.1.1.tgz",
+      "integrity": "sha512-WunYko2W1NcdfAFpuLUoucsgULmgDBRkdxHxWQ7mK0cQqwPiy8E1enjuRBrhLtZkB5iScJ1XIPdhVEFK8aOLSg==",
       "license": "MIT",
       "dependencies": {
         "mlly": "^1.7.4",
-        "pkg-types": "^2.3.0",
-        "quansync": "^0.2.11"
+        "pkg-types": "^2.0.1",
+        "quansync": "^0.2.8"
       },
       "engines": {
         "node": ">=14"
@@ -7485,15 +7481,15 @@
       }
     },
     "node_modules/marked": {
-      "version": "16.4.0",
-      "resolved": "https://registry.npmjs.org/marked/-/marked-16.4.0.tgz",
-      "integrity": "sha512-CTPAcRBq57cn3R8n3hwc2REddc28hjR7RzDXQ+lXLmMJYqn20BaI2cGw6QjgZGIgVfp2Wdfw4aMzgNteQ6qJgQ==",
+      "version": "15.0.7",
+      "resolved": "https://registry.npmjs.org/marked/-/marked-15.0.7.tgz",
+      "integrity": "sha512-dgLIeKGLx5FwziAnsk4ONoGwHwGPJzselimvlVskE9XLN4Orv9u2VA3GWw/lYUqjfA0rUT/6fqKwfZJapP9BEg==",
       "license": "MIT",
       "bin": {
         "marked": "bin/marked.js"
       },
       "engines": {
-        "node": ">= 20"
+        "node": ">= 18"
       }
     },
     "node_modules/math-intrinsics": {
@@ -7929,14 +7925,14 @@
       }
     },
     "node_modules/mermaid": {
-      "version": "11.12.0",
-      "resolved": "https://registry.npmjs.org/mermaid/-/mermaid-11.12.0.tgz",
-      "integrity": "sha512-ZudVx73BwrMJfCFmSSJT84y6u5brEoV8DOItdHomNLz32uBjNrelm7mg95X7g+C6UoQH/W6mBLGDEDv73JdxBg==",
+      "version": "11.6.0",
+      "resolved": "https://registry.npmjs.org/mermaid/-/mermaid-11.6.0.tgz",
+      "integrity": "sha512-PE8hGUy1LDlWIHWBP05SFdqUHGmRcCcK4IzpOKPE35eOw+G9zZgcnMpyunJVUEOgb//KBORPjysKndw8bFLuRg==",
       "license": "MIT",
       "dependencies": {
-        "@braintree/sanitize-url": "^7.1.1",
-        "@iconify/utils": "^3.0.1",
-        "@mermaid-js/parser": "^0.6.2",
+        "@braintree/sanitize-url": "^7.0.4",
+        "@iconify/utils": "^2.1.33",
+        "@mermaid-js/parser": "^0.4.0",
         "@types/d3": "^7.4.3",
         "cytoscape": "^3.29.3",
         "cytoscape-cose-bilkent": "^4.1.0",
@@ -7944,12 +7940,12 @@
         "d3": "^7.9.0",
         "d3-sankey": "^0.12.3",
         "dagre-d3-es": "7.0.11",
-        "dayjs": "^1.11.18",
-        "dompurify": "^3.2.5",
-        "katex": "^0.16.22",
+        "dayjs": "^1.11.13",
+        "dompurify": "^3.2.4",
+        "katex": "^0.16.9",
         "khroma": "^2.1.0",
         "lodash-es": "^4.17.21",
-        "marked": "^16.2.1",
+        "marked": "^15.0.7",
         "roughjs": "^4.6.6",
         "stylis": "^4.3.6",
         "ts-dedent": "^2.2.0",
@@ -8608,15 +8604,15 @@
       }
     },
     "node_modules/mlly": {
-      "version": "1.8.0",
-      "resolved": "https://registry.npmjs.org/mlly/-/mlly-1.8.0.tgz",
-      "integrity": "sha512-l8D9ODSRWLe2KHJSifWGwBqpTZXIXTeo8mlKjY+E2HAakaTeNpqAyBZ8GSqLzHgw4XmHmC8whvpjJNMbFZN7/g==",
+      "version": "1.7.4",
+      "resolved": "https://registry.npmjs.org/mlly/-/mlly-1.7.4.tgz",
+      "integrity": "sha512-qmdSIPC4bDJXgZTCR7XosJiNKySV7O215tsPtDN9iEO/7q/76b/ijtgRu/+epFXSJhijtTCCGp3DWS549P3xKw==",
       "license": "MIT",
       "dependencies": {
-        "acorn": "^8.15.0",
-        "pathe": "^2.0.3",
-        "pkg-types": "^1.3.1",
-        "ufo": "^1.6.1"
+        "acorn": "^8.14.0",
+        "pathe": "^2.0.1",
+        "pkg-types": "^1.3.0",
+        "ufo": "^1.5.4"
       }
     },
     "node_modules/mlly/node_modules/confbox": {
@@ -8925,10 +8921,13 @@
       }
     },
     "node_modules/package-manager-detector": {
-      "version": "1.4.0",
-      "resolved": "https://registry.npmjs.org/package-manager-detector/-/package-manager-detector-1.4.0.tgz",
-      "integrity": "sha512-rRZ+pR1Usc+ND9M2NkmCvE/LYJS+8ORVV9X0KuNSY/gFsp7RBHJM/ADh9LYq4Vvfq6QkKrW6/weuh8SMEtN5gw==",
-      "license": "MIT"
+      "version": "0.2.11",
+      "resolved": "https://registry.npmjs.org/package-manager-detector/-/package-manager-detector-0.2.11.tgz",
+      "integrity": "sha512-BEnLolu+yuz22S56CU1SUKq3XC3PkwD5wv4ikR4MfGvnRVcmzXR9DwSlW2fEamyTPyXHomBJRzgapeuBvRNzJQ==",
+      "license": "MIT",
+      "dependencies": {
+        "quansync": "^0.2.7"
+      }
     },
     "node_modules/parent-module": {
       "version": "1.0.1",
@@ -9083,13 +9082,13 @@
       }
     },
     "node_modules/pkg-types": {
-      "version": "2.3.0",
-      "resolved": "https://registry.npmjs.org/pkg-types/-/pkg-types-2.3.0.tgz",
-      "integrity": "sha512-SIqCzDRg0s9npO5XQ3tNZioRY1uK06lA41ynBC1YmFTmnY6FjUjVt6s4LoADmwoig1qqD0oK8h1p/8mlMx8Oig==",
+      "version": "2.1.0",
+      "resolved": "https://registry.npmjs.org/pkg-types/-/pkg-types-2.1.0.tgz",
+      "integrity": "sha512-wmJwA+8ihJixSoHKxZJRBQG1oY8Yr9pGLzRmSsNms0iNWyHHAlZCa7mmKiFR10YPZuz/2k169JiS/inOjBCZ2A==",
       "license": "MIT",
       "dependencies": {
-        "confbox": "^0.2.2",
-        "exsolve": "^1.0.7",
+        "confbox": "^0.2.1",
+        "exsolve": "^1.0.1",
         "pathe": "^2.0.3"
       }
     },
@@ -9301,9 +9300,9 @@
       }
     },
     "node_modules/quansync": {
-      "version": "0.2.11",
-      "resolved": "https://registry.npmjs.org/quansync/-/quansync-0.2.11.tgz",
-      "integrity": "sha512-AifT7QEbW9Nri4tAwR5M/uzpBuqfZf+zwaEM/QkzEjj7NBuFD2rBuy0K3dE+8wltbezDV7JMA0WfnCPYRSYbXA==",
+      "version": "0.2.10",
+      "resolved": "https://registry.npmjs.org/quansync/-/quansync-0.2.10.tgz",
+      "integrity": "sha512-t41VRkMYbkHyCYmOvx/6URnN80H7k4X0lLdBMGsz+maAwrJQYB1djpV6vHrQIBE0WBSGqhtEHrK9U3DWWH8v7A==",
       "funding": [
         {
           "type": "individual",
@@ -9383,16 +9382,6 @@
         "react": ">= 16.8 || 18.0.0"
       }
     },
-    "node_modules/react-google-drive-picker": {
-      "version": "1.2.2",
-      "resolved": "https://registry.npmjs.org/react-google-drive-picker/-/react-google-drive-picker-1.2.2.tgz",
-      "integrity": "sha512-x30mYkt9MIwPCgL+fyK75HZ8E6G5L/WGW0bfMG6kbD4NG2kmdlmV9oH5lPa6P6d46y9hj5Y3btAMrZd4JRRkSA==",
-      "license": "MIT",
-      "peerDependencies": {
-        "react": ">=17.0.0",
-        "react-dom": ">=17.0.0"
-      }
-    },
     "node_modules/react-i18next": {
       "version": "15.4.0",
       "resolved": "https://registry.npmjs.org/react-i18next/-/react-i18next-15.4.0.tgz",
@@ -10538,9 +10527,9 @@
       "dev": true
     },
     "node_modules/tinyexec": {
-      "version": "1.0.1",
-      "resolved": "https://registry.npmjs.org/tinyexec/-/tinyexec-1.0.1.tgz",
-      "integrity": "sha512-5uC6DDlmeqiOwCPmK9jMSdOuZTh8bU39Ys6yidB+UTt5hfZUPGAypSgFRiEp+jbi9qH40BLDvy85jIU88wKSqw==",
+      "version": "0.3.2",
+      "resolved": "https://registry.npmjs.org/tinyexec/-/tinyexec-0.3.2.tgz",
+      "integrity": "sha512-KQQR9yN7R5+OSwaK0XQoj22pwHoTlgYqmUscPYoknOoWCWfj/5/ABTMRi69FrKU5ffPVh5QcFikpWJI/P1ocHA==",
       "license": "MIT"
     },
     "node_modules/tinyglobby": {
@@ -10790,9 +10779,9 @@
       }
     },
     "node_modules/ufo": {
-      "version": "1.6.1",
-      "resolved": "https://registry.npmjs.org/ufo/-/ufo-1.6.1.tgz",
-      "integrity": "sha512-9a4/uxlTWJ4+a5i0ooc1rU7C7YOw3wT+UGqdeNNHWnOF9qcMBgLRS+4IYUqbczewFx4mLEig6gawh7X6mFlEkA==",
+      "version": "1.5.4",
+      "resolved": "https://registry.npmjs.org/ufo/-/ufo-1.5.4.tgz",
+      "integrity": "sha512-UsUk3byDzKd04EyoZ7U4DOlxQaD14JUKQl6/P7wiX4FNvUfm3XL246n9W5AmqwW5RSFJ27NAuM0iLscAOYUiGQ==",
       "license": "MIT"
     },
     "node_modules/unbox-primitive": {

frontend/package.json

@@ -23,16 +23,15 @@
     "chart.js": "^4.4.4",
     "clsx": "^2.1.1",
     "copy-to-clipboard": "^3.3.3",
-    "i18next": "^25.5.3",
+    "i18next": "^24.2.0",
     "i18next-browser-languagedetector": "^8.0.2",
     "lodash": "^4.17.21",
-    "mermaid": "^11.12.0",
+    "mermaid": "^11.6.0",
     "prop-types": "^15.8.1",
     "react": "^19.1.0",
     "react-chartjs-2": "^5.3.0",
     "react-dom": "^19.0.0",
     "react-dropzone": "^14.3.8",
-    "react-google-drive-picker": "^1.2.2",
     "react-i18next": "^15.4.0",
     "react-markdown": "^9.0.1",
     "react-redux": "^9.2.0",

frontend/public/toolIcons/tool_mcp_tool.svg

@@ -1,4 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" width="64" height="64" color="#000000" fill="none">
-    <path d="M3.49994 11.7501L11.6717 3.57855C12.7762 2.47398 14.5672 2.47398 15.6717 3.57855C16.7762 4.68312 16.7762 6.47398 15.6717 7.57855M15.6717 7.57855L9.49994 13.7501M15.6717 7.57855C16.7762 6.47398 18.5672 6.47398 19.6717 7.57855C20.7762 8.68312 20.7762 10.474 19.6717 11.5785L12.7072 18.543C12.3167 18.9335 12.3167 19.5667 12.7072 19.9572L13.9999 21.2499" stroke="currentColor" stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round"></path>
-    <path d="M17.4999 9.74921L11.3282 15.921C10.2237 17.0255 8.43272 17.0255 7.32823 15.921C6.22373 14.8164 6.22373 13.0255 7.32823 11.921L13.4999 5.74939" stroke="currentColor" stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round"></path>
-</svg>

frontend/public/toolIcons/tool_memory.svg

@@ -1,3 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" height="24px" viewBox="0 -960 960 960" width="24px" fill="#e3e3e3">
-  <path d="M240-80q-33 0-56.5-23.5T160-160v-480q0-33 23.5-56.5T240-720h80v-80q0-17 11.5-28.5T360-840q17 0 28.5 11.5T400-800v80h40v-80q0-17 11.5-28.5T480-840q17 0 28.5 11.5T520-800v80h40v-80q0-17 11.5-28.5T600-840q17 0 28.5 11.5T640-800v80h80q33 0 56.5 23.5T800-640v480q0 33-23.5 56.5T720-80H240Zm0-80h480v-480H240v480Zm120-320v-80h240v80H360Zm0 120v-80h240v80H360Zm0 120v-80h160v80H360ZM240-160v-480 480Z"/>
-</svg>

frontend/public/toolIcons/tool_notes.svg

@@ -1 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" height="24px" viewBox="0 -960 960 960" width="24px" fill="#e3e3e3"><path d="M320-240h320v-80H320v80Zm0-160h320v-80H320v80ZM240-80q-33 0-56.5-23.5T160-160v-640q0-33 23.5-56.5T240-880h320l240 240v480q0 33-23.5 56.5T720-80H240Zm280-520v-200H240v640h480v-440H520ZM240-800v200-200 640-640Z"/></svg>

frontend/public/toolIcons/tool_todo_list.svg

@@ -1 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" height="24px" viewBox="0 -960 960 960" width="24px" fill="#e3e3e3"><path d="M240-80q-33 0-56.5-23.5T160-160v-640q0-33 23.5-56.5T240-880h480q33 0 56.5 23.5T800-800v640q0 33-23.5 56.5T720-80H240Zm0-80h480v-640H240v640Zm88-104 56-56-56-56-56 56 56 56Zm0-160 56-56-56-56-56 56 56 56Zm0-160 56-56-56-56-56 56 56 56Zm120 280h232v-80H448v80Zm0-160h232v-80H448v80Zm0-160h232v-80H448v80ZM240-160v-640 640Z"/></svg>

frontend/src/App.tsx

@@ -7,7 +7,6 @@ import Agents from './agents';
 import SharedAgentGate from './agents/SharedAgentGate';
 import ActionButtons from './components/ActionButtons';
 import Spinner from './components/Spinner';
-import UploadToast from './components/UploadToast';
 import Conversation from './conversation/Conversation';
 import { SharedConversation } from './conversation/SharedConversation';
 import { useDarkTheme, useMediaQuery } from './hooks';
@@ -15,7 +14,6 @@ import useTokenAuth from './hooks/useTokenAuth';
 import Navigation from './Navigation';
 import PageNotFound from './PageNotFound';
 import Setting from './settings';
-import Notification from './components/Notification';
 
 function AuthWrapper({ children }: { children: React.ReactNode }) {
   const { isAuthLoading } = useTokenAuth();
@@ -35,45 +33,28 @@ function MainLayout() {
   const [navOpen, setNavOpen] = useState(!(isMobile || isTablet));
 
   return (
-    <div className="dark:bg-raisin-black relative h-screen overflow-hidden">
+    <div className="relative h-screen overflow-hidden dark:bg-raisin-black">
       <Navigation navOpen={navOpen} setNavOpen={setNavOpen} />
       <ActionButtons showNewChat={true} showShare={true} />
       <div
-        className={`h-[calc(100dvh-64px)] overflow-auto transition-all duration-300 ease-in-out lg:h-screen ${
+        className={`h-[calc(100dvh-64px)] overflow-auto lg:h-screen ${
           !(isMobile || isTablet)
-            ? `${navOpen ? 'lg:ml-72' : 'lg:ml-0'}`
+            ? `ml-0 ${!navOpen ? 'lg:mx-auto' : 'lg:ml-72'}`
             : 'ml-0 lg:ml-16'
         }`}
       >
         <Outlet />
       </div>
-      <UploadToast />
     </div>
   );
 }
 export default function App() {
   const [, , componentMounted] = useDarkTheme();
-  const [showNotification, setShowNotification] = useState<boolean>(() => {
-    const saved = localStorage.getItem('showNotification');
-    return saved ? JSON.parse(saved) : true;
-  });
-  const notificationText = import.meta.env.VITE_NOTIFICATION_TEXT;
-  const notificationLink = import.meta.env.VITE_NOTIFICATION_LINK;
   if (!componentMounted) {
     return <div />;
   }
   return (
     <div className="relative h-full overflow-hidden">
-      {notificationLink && notificationText && showNotification && (
-        <Notification
-          notificationText={notificationText}
-          notificationLink={notificationLink}
-          handleCloseNotification={() => {
-            setShowNotification(false);
-            localStorage.setItem('showNotification', 'false');
-          }}
-        />
-      )}
       <Routes>
         <Route
           element={

frontend/src/Hero.tsx

@@ -29,7 +29,7 @@ export default function Hero({
       </div>
 
       {/* Demo Buttons Section */}
-      <div className="mb-3 w-full max-w-full md:mb-3">
+      <div className="mb-8 w-full max-w-full md:mb-16">
         <div className="grid grid-cols-1 gap-3 text-xs md:grid-cols-1 md:gap-4 lg:grid-cols-2">
           {demos?.map(
             (demo: { header: string; query: string }, key: number) =>

frontend/src/Navigation.tsx

@@ -9,13 +9,12 @@ import userService from './api/services/userService';
 import Add from './assets/add.svg';
 import DocsGPT3 from './assets/cute_docsgpt3.svg';
 import Discord from './assets/discord.svg';
-import PanelLeftClose from './assets/panel-left-close.svg';
-import PanelLeftOpen from './assets/panel-left-open.svg';
-import Github from './assets/git_nav.svg';
+import Expand from './assets/expand.svg';
+import Github from './assets/github.svg';
 import Hamburger from './assets/hamburger.svg';
 import openNewChat from './assets/openNewChat.svg';
 import Pin from './assets/pin.svg';
-import AgentImage from './components/AgentImage';
+import Robot from './assets/robot.svg';
 import SettingGear from './assets/settingGear.svg';
 import Spark from './assets/spark.svg';
 import SpinnerDark from './assets/spinner-dark.svg';
@@ -293,36 +292,27 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
   useDefaultDocument();
   return (
     <>
-      {(isMobile || isTablet) && navOpen && (
-        <div
-          className="fixed inset-0 z-10 bg-black opacity-50 transition-opacity duration-300"
-          onClick={() => setNavOpen(false)}
-        />
-      )}
-
-      {
-        <div className="absolute top-3 left-3 z-20 hidden transition-all duration-300 ease-in-out lg:block">
+      {!navOpen && (
+        <div className="absolute top-3 left-3 z-20 hidden transition-all duration-25 lg:block">
           <div className="flex items-center gap-3">
-            {!navOpen && (
-              <button
-                onClick={() => {
-                  setNavOpen(!navOpen);
-                }}
-                className="transition-transform duration-200 hover:scale-110"
-              >
-                <img
-                  src={PanelLeftOpen}
-                  alt="Open navigation menu"
-                  className="m-auto transition-all duration-300 ease-in-out"
-                />
-              </button>
-            )}
+            <button
+              onClick={() => {
+                setNavOpen(!navOpen);
+              }}
+            >
+              <img
+                src={Expand}
+                alt="Toggle navigation menu"
+                className={`${
+                  !navOpen ? 'rotate-180' : 'rotate-0'
+                } m-auto transition-all duration-200`}
+              />
+            </button>
             {queries?.length > 0 && (
               <button
                 onClick={() => {
                   newChat();
                 }}
-                className="transition-transform duration-200 hover:scale-110"
               >
                 <img
                   src={openNewChat}
@@ -336,12 +326,12 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
             </div>
           </div>
         </div>
-      }
+      )}
       <div
         ref={navRef}
         className={`${
           !navOpen && '-ml-96 md:-ml-72'
-        } bg-lotion dark:border-r-purple-taupe dark:bg-chinese-black fixed top-0 z-20 flex h-full w-72 flex-col border-r border-b-0 transition-all duration-300 ease-in-out dark:text-white`}
+        } bg-lotion dark:border-r-purple-taupe dark:bg-chinese-black fixed top-0 z-20 flex h-full w-72 flex-col border-r border-b-0 transition-all duration-20 dark:text-white`}
       >
         <div
           className={'visible mt-2 flex h-[6vh] w-full justify-between md:h-12'}
@@ -355,7 +345,7 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
             }}
           >
             <a href="/" className="flex gap-1.5">
-              <img className="h-10" src={DocsGPT3} alt="DocsGPT Logo" />
+              <img className="mb-2 h-10" src={DocsGPT3} alt="DocsGPT Logo" />
               <p className="my-auto text-2xl font-semibold">DocsGPT</p>
             </a>
           </div>
@@ -366,9 +356,11 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
             }}
           >
             <img
-              src={navOpen ? PanelLeftClose : PanelLeftOpen}
-              alt={navOpen ? 'Collapse sidebar' : 'Expand sidebar'}
-              className="m-auto transition-all duration-300 ease-in-out hover:scale-110"
+              src={Expand}
+              alt="Toggle navigation menu"
+              className={`${
+                !navOpen ? 'rotate-180' : 'rotate-0'
+              } m-auto transition-all duration-200`}
             />
           </button>
         </div>
@@ -402,7 +394,7 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
           {conversations?.loading && !isDeletingConversation && (
             <div className="absolute top-1/2 left-1/2 -translate-x-1/2 -translate-y-1/2 transform">
               <img
-                src={isDarkTheme ? Spinner : SpinnerDark}
+                src={isDarkTheme ? SpinnerDark : Spinner}
                 className="animate-spin cursor-pointer bg-transparent"
                 alt="Loading conversations"
               />
@@ -427,8 +419,12 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
                     >
                       <div className="flex items-center gap-2">
                         <div className="flex w-6 justify-center">
-                          <AgentImage
-                            src={agent.image}
+                          <img
+                            src={
+                              agent.image && agent.image.trim() !== ''
+                                ? agent.image
+                                : Robot
+                            }
                             alt="agent-logo"
                             className="h-6 w-6 rounded-full object-contain"
                           />
@@ -572,25 +568,21 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
                 >
                   <img
                     src={Discord}
-                    width={24}
-                    height={24}
                     alt="Join Discord community"
                     className="m-2 w-6 self-center filter dark:invert"
                   />
                 </NavLink>
                 <NavLink
                   target="_blank"
-                  to={'https://x.com/docsgptai'}
+                  to={'https://twitter.com/docsgptai'}
                   className={
                     'rounded-full hover:bg-gray-100 dark:hover:bg-[#28292E]'
                   }
                 >
                   <img
                     src={Twitter}
-                    width={20}
-                    height={20}
-                    alt="Follow us on X"
-                    className="m-2 self-center filter dark:invert"
+                    alt="Follow us on Twitter"
+                    className="m-2 w-5 self-center filter dark:invert"
                   />
                 </NavLink>
                 <NavLink
@@ -603,9 +595,7 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
                   <img
                     src={Github}
                     alt="View on GitHub"
-                    width={28}
-                    height={28}
-                    className="m-2 self-center filter dark:invert"
+                    className="m-2 w-6 self-center filter dark:invert"
                   />
                 </NavLink>
               </div>

frontend/src/PageNotFound.tsx

@@ -2,11 +2,11 @@ import { Link } from 'react-router-dom';
 
 export default function PageNotFound() {
   return (
-    <div className="dark:bg-raisin-black grid min-h-screen">
-      <p className="text-jet dark:bg-outer-space mx-auto my-auto mt-20 flex w-full max-w-6xl flex-col place-items-center gap-6 rounded-3xl bg-gray-100 p-6 lg:p-10 xl:p-16 dark:text-gray-100">
+    <div className="grid min-h-screen dark:bg-raisin-black">
+      <p className="mx-auto my-auto mt-20 flex w-full max-w-6xl flex-col place-items-center gap-6 rounded-3xl bg-gray-100 p-6 text-jet dark:bg-outer-space dark:text-gray-100 lg:p-10 xl:p-16">
         <h1>404</h1>
         <p>The page you are looking for does not exist.</p>
-        <button className="pointer-cursor bg-blue-1000 hover:bg-blue-3000 mr-4 flex cursor-pointer items-center justify-center rounded-full px-4 py-2 text-white transition-colors duration-100">
+        <button className="pointer-cursor mr-4 flex cursor-pointer items-center justify-center rounded-full bg-blue-1000 px-4 py-2 text-white transition-colors duration-100 hover:bg-blue-3000">
           <Link to="/">Go Back Home</Link>
         </button>
       </p>

frontend/src/agents/AgentCard.tsx

@@ -1,22 +1,14 @@
-import { SyntheticEvent, useRef, useState } from 'react';
+import { useRef, useState } from 'react';
 import { useDispatch, useSelector } from 'react-redux';
 import { useNavigate } from 'react-router-dom';
 
 import userService from '../api/services/userService';
-import Duplicate from '../assets/duplicate.svg';
-import Edit from '../assets/edit.svg';
-import Link from '../assets/link-gray.svg';
-import Monitoring from '../assets/monitoring.svg';
-import Pin from '../assets/pin.svg';
-import Trash from '../assets/red-trash.svg';
+import Robot from '../assets/robot.svg';
 import ThreeDots from '../assets/three-dots.svg';
-import UnPin from '../assets/unpin.svg';
-import AgentImage from '../components/AgentImage';
 import ContextMenu, { MenuOption } from '../components/ContextMenu';
 import ConfirmationModal from '../modals/ConfirmationModal';
 import { ActiveState } from '../models/misc';
 import {
-  selectAgents,
   selectToken,
   setAgents,
   setSelectedAgent,
@@ -26,205 +18,46 @@ import { Agent } from './types';
 type AgentCardProps = {
   agent: Agent;
   agents: Agent[];
-  updateAgents?: (agents: Agent[]) => void;
-  section: string;
+  menuOptions?: MenuOption[];
+  onDelete?: (agentId: string) => void;
 };
 
 export default function AgentCard({
   agent,
   agents,
-  updateAgents,
-  section,
+  menuOptions,
+  onDelete,
 }: AgentCardProps) {
   const navigate = useNavigate();
   const dispatch = useDispatch();
   const token = useSelector(selectToken);
-  const userAgents = useSelector(selectAgents);
 
-  const [isMenuOpen, setIsMenuOpen] = useState<boolean>(false);
+  const [isMenuOpen, setIsMenuOpen] = useState(false);
   const [deleteConfirmation, setDeleteConfirmation] =
     useState<ActiveState>('INACTIVE');
 
   const menuRef = useRef<HTMLDivElement>(null);
 
-  const menuOptionsConfig: Record<string, MenuOption[]> = {
-    template: [
-      {
-        icon: Duplicate,
-        label: 'Duplicate',
-        onClick: (e: SyntheticEvent) => {
-          e.stopPropagation();
-          handleDuplicate();
-        },
-        variant: 'primary',
-        iconWidth: 18,
-        iconHeight: 18,
-      },
-    ],
-    user: [
-      {
-        icon: Monitoring,
-        label: 'Logs',
-        onClick: (e: SyntheticEvent) => {
-          e.stopPropagation();
-          navigate(`/agents/logs/${agent.id}`);
-        },
-        variant: 'primary',
-        iconWidth: 14,
-        iconHeight: 14,
-      },
-      {
-        icon: Edit,
-        label: 'Edit',
-        onClick: (e: SyntheticEvent) => {
-          e.stopPropagation();
-          navigate(`/agents/edit/${agent.id}`);
-        },
-        variant: 'primary',
-        iconWidth: 14,
-        iconHeight: 14,
-      },
-      ...(agent.status === 'published'
-        ? [
-            {
-              icon: agent.pinned ? UnPin : Pin,
-              label: agent.pinned ? 'Unpin' : 'Pin agent',
-              onClick: (e: SyntheticEvent) => {
-                e.stopPropagation();
-                togglePin();
-              },
-              variant: 'primary' as const,
-              iconWidth: 18,
-              iconHeight: 18,
-            },
-          ]
-        : []),
-      {
-        icon: Trash,
-        label: 'Delete',
-        onClick: (e: SyntheticEvent) => {
-          e.stopPropagation();
-          setDeleteConfirmation('ACTIVE');
-        },
-        variant: 'danger',
-        iconWidth: 13,
-        iconHeight: 13,
-      },
-    ],
-    shared: [
-      {
-        icon: Link,
-        label: 'Open',
-        onClick: (e: SyntheticEvent) => {
-          e.stopPropagation();
-          navigate(`/agents/shared/${agent.shared_token}`);
-        },
-        variant: 'primary',
-        iconWidth: 12,
-        iconHeight: 12,
-      },
-      {
-        icon: agent.pinned ? UnPin : Pin,
-        label: agent.pinned ? 'Unpin' : 'Pin agent',
-        onClick: (e: SyntheticEvent) => {
-          e.stopPropagation();
-          togglePin();
-        },
-        variant: 'primary',
-        iconWidth: 18,
-        iconHeight: 18,
-      },
-      {
-        icon: Trash,
-        label: 'Remove',
-        onClick: (e: SyntheticEvent) => {
-          e.stopPropagation();
-          handleHideSharedAgent();
-        },
-        variant: 'danger',
-        iconWidth: 13,
-        iconHeight: 13,
-      },
-    ],
-  };
-  const menuOptions = menuOptionsConfig[section] || [];
-
-  const handleClick = () => {
-    if (section === 'user') {
-      if (agent.status === 'published') {
-        dispatch(setSelectedAgent(agent));
-        navigate(`/`);
-      }
-    }
-    if (section === 'shared') {
-      navigate(`/agents/shared/${agent.shared_token}`);
+  const handleCardClick = () => {
+    if (agent.status === 'published') {
+      dispatch(setSelectedAgent(agent));
+      navigate('/');
     }
   };
 
-  const togglePin = async () => {
-    try {
-      const response = await userService.togglePinAgent(agent.id ?? '', token);
-      if (!response.ok) throw new Error('Failed to pin agent');
-      const updatedAgents = agents.map((prevAgent) => {
-        if (prevAgent.id === agent.id)
-          return { ...prevAgent, pinned: !prevAgent.pinned };
-        return prevAgent;
-      });
-      updateAgents?.(updatedAgents);
-    } catch (error) {
-      console.error('Error:', error);
-    }
+  const defaultDelete = async (agentId: string) => {
+    const response = await userService.deleteAgent(agentId, token);
+    if (!response.ok) throw new Error('Failed to delete agent');
+    const data = await response.json();
+    dispatch(setAgents(agents.filter((prevAgent) => prevAgent.id !== data.id)));
   };
 
-  const handleHideSharedAgent = async () => {
-    try {
-      const response = await userService.removeSharedAgent(
-        agent.id ?? '',
-        token,
-      );
-      if (!response.ok) throw new Error('Failed to hide shared agent');
-      const updatedAgents = agents.filter(
-        (prevAgent) => prevAgent.id !== agent.id,
-      );
-      updateAgents?.(updatedAgents);
-    } catch (error) {
-      console.error('Error:', error);
-    }
-  };
-
-  const handleDelete = async () => {
-    try {
-      const response = await userService.deleteAgent(agent.id ?? '', token);
-      if (!response.ok) throw new Error('Failed to delete agent');
-      const updatedAgents = agents.filter(
-        (prevAgent) => prevAgent.id !== agent.id,
-      );
-      updateAgents?.(updatedAgents);
-    } catch (error) {
-      console.error('Error:', error);
-    }
-  };
-
-  const handleDuplicate = async () => {
-    try {
-      const response = await userService.adoptAgent(agent.id ?? '', token);
-      if (!response.ok) throw new Error('Failed to duplicate agent');
-      const data = await response.json();
-      if (userAgents) {
-        const updatedAgents = [...userAgents, data.agent];
-        dispatch(setAgents(updatedAgents));
-      } else dispatch(setAgents([data.agent]));
-    } catch (error) {
-      console.error('Error:', error);
-    }
-  };
   return (
     <div
-      className={`relative flex h-44 w-full flex-col justify-between rounded-[1.2rem] bg-[#F6F6F6] px-6 py-5 hover:bg-[#ECECEC] md:w-48 dark:bg-[#383838] dark:hover:bg-[#383838]/80 ${agent.status === 'published' && 'cursor-pointer'}`}
-      onClick={(e) => {
-        e.stopPropagation();
-        handleClick();
-      }}
+      className={`relative flex h-44 w-48 flex-col justify-between rounded-[1.2rem] bg-[#F6F6F6] px-6 py-5 hover:bg-[#ECECEC] dark:bg-[#383838] dark:hover:bg-[#383838]/80 ${
+        agent.status === 'published' ? 'cursor-pointer' : ''
+      }`}
+      onClick={handleCardClick}
     >
       <div
         ref={menuRef}
@@ -234,25 +67,30 @@ export default function AgentCard({
         }}
         className="absolute top-4 right-4 z-10 cursor-pointer"
       >
-        <img src={ThreeDots} alt={'use-agent'} className="h-[19px] w-[19px]" />
-        <ContextMenu
-          isOpen={isMenuOpen}
-          setIsOpen={setIsMenuOpen}
-          options={menuOptions}
-          anchorRef={menuRef}
-          position="bottom-right"
-          offset={{ x: 0, y: 0 }}
-        />
+        <img src={ThreeDots} alt="options" className="h-[19px] w-[19px]" />
+        {menuOptions && (
+          <ContextMenu
+            isOpen={isMenuOpen}
+            setIsOpen={setIsMenuOpen}
+            options={menuOptions}
+            anchorRef={menuRef}
+            position="top-right"
+            offset={{ x: 0, y: 0 }}
+          />
+        )}
       </div>
+
       <div className="w-full">
         <div className="flex w-full items-center gap-1 px-1">
-          <AgentImage
-            src={agent.image}
+          <img
+            src={agent.image && agent.image.trim() !== '' ? agent.image : Robot}
             alt={`${agent.name}`}
             className="h-7 w-7 rounded-full object-contain"
           />
           {agent.status === 'draft' && (
-            <p className="text-xs text-black opacity-50 dark:text-[#E0E0E0]">{`(Draft)`}</p>
+            <p className="text-xs text-black opacity-50 dark:text-[#E0E0E0]">
+              (Draft)
+            </p>
           )}
         </div>
         <div className="mt-2">
@@ -267,13 +105,14 @@ export default function AgentCard({
           </p>
         </div>
       </div>
+
       <ConfirmationModal
         message="Are you sure you want to delete this agent?"
         modalState={deleteConfirmation}
         setModalState={setDeleteConfirmation}
         submitLabel="Delete"
         handleSubmit={() => {
-          handleDelete();
+          onDelete ? onDelete(agent.id || '') : defaultDelete(agent.id || '');
           setDeleteConfirmation('INACTIVE');
         }}
         cancelLabel="Cancel"

frontend/src/agents/AgentLogs.tsx

@@ -49,7 +49,7 @@ export default function AgentLogs() {
         </p>
       </div>
       <div className="mt-5 flex w-full flex-wrap items-center justify-between gap-2 px-4">
-        <h1 className="text-eerie-black m-0 text-[32px] font-bold md:text-[40px] dark:text-white">
+        <h1 className="text-eerie-black m-0 text-[40px] font-bold dark:text-white">
           Agent Logs
         </h1>
       </div>

frontend/src/agents/AgentPreview.tsx

@@ -109,18 +109,18 @@ export default function AgentPreview() {
     } else setLastQueryReturnedErr(false);
   }, [queries]);
   return (
-    <div className="relative h-full w-full">
-      <div className="scrollbar-thin absolute inset-0 bottom-[180px] overflow-hidden px-4 pt-4 [&>div>div]:!w-full [&>div>div]:!max-w-none">
-        <ConversationMessages
-          handleQuestion={handleQuestion}
-          handleQuestionSubmission={handleQuestionSubmission}
-          queries={queries}
-          status={status}
-          showHeroOnEmpty={false}
-        />
-      </div>
-      <div className="absolute right-0 bottom-0 left-0 flex w-full flex-col gap-4 pb-2">
-        <div className="w-full px-4">
+    <div>
+      <div className="dark:bg-raisin-black flex h-full flex-col items-center justify-between gap-2 overflow-y-hidden">
+        <div className="h-[512px] w-full overflow-y-auto">
+          <ConversationMessages
+            handleQuestion={handleQuestion}
+            handleQuestionSubmission={handleQuestionSubmission}
+            queries={queries}
+            status={status}
+            showHeroOnEmpty={false}
+          />
+        </div>
+        <div className="flex w-[95%] max-w-[1500px] flex-col items-center gap-4 pb-2 md:w-9/12 lg:w-8/12 xl:w-8/12 2xl:w-6/12">
           <MessageInput
             onSubmit={(text) => handleQuestionSubmission(text)}
             loading={status === 'loading'}
@@ -128,11 +128,11 @@ export default function AgentPreview() {
             showToolButton={selectedAgent ? false : true}
             autoFocus={false}
           />
+          <p className="text-gray-4000 dark:text-sonic-silver w-full self-center bg-transparent pt-2 text-center text-xs md:inline">
+            This is a preview of the agent. You can publish it to start using it
+            in conversations.
+          </p>
         </div>
-        <p className="text-gray-4000 dark:text-sonic-silver w-full bg-transparent text-center text-xs md:inline">
-          This is a preview of the agent. You can publish it to start using it
-          in conversations.
-        </p>
       </div>
     </div>
   );

frontend/src/agents/AgentsList.tsx

@@ -1,134 +0,0 @@
-import { useEffect, useState } from 'react';
-import { useDispatch, useSelector } from 'react-redux';
-import { useNavigate } from 'react-router-dom';
-
-import Spinner from '../components/Spinner';
-import {
-  setConversation,
-  updateConversationId,
-} from '../conversation/conversationSlice';
-import {
-  selectSelectedAgent,
-  selectToken,
-  setSelectedAgent,
-} from '../preferences/preferenceSlice';
-import AgentCard from './AgentCard';
-import { agentSectionsConfig } from './agents.config';
-import { Agent } from './types';
-
-export default function AgentsList() {
-  const dispatch = useDispatch();
-  const token = useSelector(selectToken);
-  const selectedAgent = useSelector(selectSelectedAgent);
-
-  useEffect(() => {
-    dispatch(setConversation([]));
-    dispatch(
-      updateConversationId({
-        query: { conversationId: null },
-      }),
-    );
-    if (selectedAgent) dispatch(setSelectedAgent(null));
-  }, [token]);
-  return (
-    <div className="p-4 md:p-12">
-      <h1 className="text-eerie-black mb-0 text-[32px] font-bold lg:text-[40px] dark:text-[#E0E0E0]">
-        Agents
-      </h1>
-      <p className="dark:text-gray-4000 mt-5 text-[15px] text-[#71717A]">
-        Discover and create custom versions of DocsGPT that combine
-        instructions, extra knowledge, and any combination of skills
-      </p>
-      {agentSectionsConfig.map((sectionConfig) => (
-        <AgentSection key={sectionConfig.id} config={sectionConfig} />
-      ))}
-    </div>
-  );
-}
-
-function AgentSection({
-  config,
-}: {
-  config: (typeof agentSectionsConfig)[number];
-}) {
-  const navigate = useNavigate();
-  const dispatch = useDispatch();
-  const token = useSelector(selectToken);
-  const agents = useSelector(config.selectData);
-
-  const [loading, setLoading] = useState(true);
-
-  const updateAgents = (updatedAgents: Agent[]) => {
-    dispatch(config.updateAction(updatedAgents));
-  };
-
-  useEffect(() => {
-    const getAgents = async () => {
-      setLoading(true);
-      try {
-        const response = await config.fetchAgents(token);
-        if (!response.ok)
-          throw new Error(`Failed to fetch ${config.id} agents`);
-        const data = await response.json();
-        dispatch(config.updateAction(data));
-      } catch (error) {
-        console.error(`Error fetching ${config.id} agents:`, error);
-        dispatch(config.updateAction([]));
-      } finally {
-        setLoading(false);
-      }
-    };
-    getAgents();
-  }, [token, config, dispatch]);
-  return (
-    <div className="mt-8 flex flex-col gap-4">
-      <div className="flex w-full items-center justify-between">
-        <div className="flex flex-col gap-2">
-          <h2 className="text-[18px] font-semibold text-[#18181B] dark:text-[#E0E0E0]">
-            {config.title}
-          </h2>
-          <p className="text-[13px] text-[#71717A]">{config.description}</p>
-        </div>
-        {config.showNewAgentButton && (
-          <button
-            className="bg-purple-30 hover:bg-violets-are-blue rounded-full px-4 py-2 text-sm text-white"
-            onClick={() => navigate('/agents/new')}
-          >
-            New Agent
-          </button>
-        )}
-      </div>
-      <div>
-        {loading ? (
-          <div className="flex h-72 w-full items-center justify-center">
-            <Spinner />
-          </div>
-        ) : agents && agents.length > 0 ? (
-          <div className="grid grid-cols-1 gap-4 sm:flex sm:flex-wrap">
-            {agents.map((agent) => (
-              <AgentCard
-                key={agent.id}
-                agent={agent}
-                agents={agents}
-                updateAgents={updateAgents}
-                section={config.id}
-              />
-            ))}
-          </div>
-        ) : (
-          <div className="flex h-72 w-full flex-col items-center justify-center gap-3 text-base text-[#18181B] dark:text-[#E0E0E0]">
-            <p>{config.emptyStateDescription}</p>
-            {config.showNewAgentButton && (
-              <button
-                className="bg-purple-30 hover:bg-violets-are-blue ml-2 rounded-full px-4 py-2 text-sm text-white"
-                onClick={() => navigate('/agents/new')}
-              >
-                New Agent
-              </button>
-            )}
-          </div>
-        )}
-      </div>
-    </div>
-  );
-}

frontend/src/agents/NewAgent.tsx

@@ -23,7 +23,7 @@ import PromptsModal from '../preferences/PromptsModal';
 import Prompts from '../settings/Prompts';
 import { UserToolType } from '../settings/types';
 import AgentPreview from './AgentPreview';
-import { Agent, ToolSummary } from './types';
+import { Agent } from './types';
 
 const embeddingsName =
   import.meta.env.VITE_EMBEDDINGS_NAME ||
@@ -45,18 +45,13 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
     description: '',
     image: '',
     source: '',
-    sources: [],
-    chunks: '2',
-    retriever: 'classic',
+    chunks: '',
+    retriever: '',
     prompt_id: 'default',
     tools: [],
-    agent_type: 'classic',
+    agent_type: '',
     status: '',
     json_schema: undefined,
-    limited_token_mode: false,
-    token_limit: undefined,
-    limited_request_mode: false,
-    request_limit: undefined,
   });
   const [imageFile, setImageFile] = useState<File | null>(null);
   const [prompts, setPrompts] = useState<
@@ -68,7 +63,9 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
   const [selectedSourceIds, setSelectedSourceIds] = useState<
     Set<string | number>
   >(new Set());
-  const [selectedTools, setSelectedTools] = useState<ToolSummary[]>([]);
+  const [selectedToolIds, setSelectedToolIds] = useState<Set<string | number>>(
+    new Set(),
+  );
   const [deleteConfirmation, setDeleteConfirmation] =
     useState<ActiveState>('INACTIVE');
   const [agentDetails, setAgentDetails] = useState<ActiveState>('INACTIVE');
@@ -78,8 +75,7 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
   const [publishLoading, setPublishLoading] = useState(false);
   const [jsonSchemaText, setJsonSchemaText] = useState('');
   const [jsonSchemaValid, setJsonSchemaValid] = useState(true);
-  const [isAdvancedSectionExpanded, setIsAdvancedSectionExpanded] =
-    useState(false);
+  const [isJsonSchemaExpanded, setIsJsonSchemaExpanded] = useState(false);
 
   const initialAgentRef = useRef<Agent | null>(null);
   const sourceAnchorButtonRef = useRef<HTMLButtonElement>(null);
@@ -125,8 +121,7 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
       agent.name && agent.description && agent.prompt_id && agent.agent_type;
     const isJsonSchemaValidOrEmpty =
       jsonSchemaText.trim() === '' || jsonSchemaValid;
-    const hasSource = selectedSourceIds.size > 0;
-    return hasRequiredFields && isJsonSchemaValidOrEmpty && hasSource;
+    return hasRequiredFields && isJsonSchemaValidOrEmpty;
   };
 
   const isJsonSchemaInvalid = () => {
@@ -155,57 +150,13 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
     const formData = new FormData();
     formData.append('name', agent.name);
     formData.append('description', agent.description);
-
-    if (selectedSourceIds.size > 1) {
-      const sourcesArray = Array.from(selectedSourceIds)
-        .map((id) => {
-          const sourceDoc = sourceDocs?.find(
-            (source) =>
-              source.id === id || source.retriever === id || source.name === id,
-          );
-          if (sourceDoc?.name === 'Default' && !sourceDoc?.id) {
-            return 'default';
-          }
-          return sourceDoc?.id || id;
-        })
-        .filter(Boolean);
-      formData.append('sources', JSON.stringify(sourcesArray));
-      formData.append('source', '');
-    } else if (selectedSourceIds.size === 1) {
-      const singleSourceId = Array.from(selectedSourceIds)[0];
-      const sourceDoc = sourceDocs?.find(
-        (source) =>
-          source.id === singleSourceId ||
-          source.retriever === singleSourceId ||
-          source.name === singleSourceId,
-      );
-      let finalSourceId;
-      if (sourceDoc?.name === 'Default' && !sourceDoc?.id)
-        finalSourceId = 'default';
-      else finalSourceId = sourceDoc?.id || singleSourceId;
-      formData.append('source', String(finalSourceId));
-      formData.append('sources', JSON.stringify([]));
-    } else {
-      formData.append('source', '');
-      formData.append('sources', JSON.stringify([]));
-    }
-
+    formData.append('source', agent.source);
     formData.append('chunks', agent.chunks);
     formData.append('retriever', agent.retriever);
     formData.append('prompt_id', agent.prompt_id);
     formData.append('agent_type', agent.agent_type);
     formData.append('status', 'draft');
 
-    if (agent.limited_token_mode && agent.token_limit) {
-      formData.append('limited_token_mode', 'True');
-      formData.append('token_limit', JSON.stringify(agent.token_limit));
-    } else formData.append('token_limit', '0');
-
-    if (agent.limited_request_mode && agent.request_limit) {
-      formData.append('limited_request_mode', 'True');
-      formData.append('request_limit', JSON.stringify(agent.request_limit));
-    } else formData.append('request_limit', '0');
-
     if (imageFile) formData.append('image', imageFile);
 
     if (agent.tools && agent.tools.length > 0)
@@ -245,41 +196,7 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
     const formData = new FormData();
     formData.append('name', agent.name);
     formData.append('description', agent.description);
-
-    if (selectedSourceIds.size > 1) {
-      const sourcesArray = Array.from(selectedSourceIds)
-        .map((id) => {
-          const sourceDoc = sourceDocs?.find(
-            (source) =>
-              source.id === id || source.retriever === id || source.name === id,
-          );
-          if (sourceDoc?.name === 'Default' && !sourceDoc?.id) {
-            return 'default';
-          }
-          return sourceDoc?.id || id;
-        })
-        .filter(Boolean);
-      formData.append('sources', JSON.stringify(sourcesArray));
-      formData.append('source', '');
-    } else if (selectedSourceIds.size === 1) {
-      const singleSourceId = Array.from(selectedSourceIds)[0];
-      const sourceDoc = sourceDocs?.find(
-        (source) =>
-          source.id === singleSourceId ||
-          source.retriever === singleSourceId ||
-          source.name === singleSourceId,
-      );
-      let finalSourceId;
-      if (sourceDoc?.name === 'Default' && !sourceDoc?.id)
-        finalSourceId = 'default';
-      else finalSourceId = sourceDoc?.id || singleSourceId;
-      formData.append('source', String(finalSourceId));
-      formData.append('sources', JSON.stringify([]));
-    } else {
-      formData.append('source', '');
-      formData.append('sources', JSON.stringify([]));
-    }
-
+    formData.append('source', agent.source);
     formData.append('chunks', agent.chunks);
     formData.append('retriever', agent.retriever);
     formData.append('prompt_id', agent.prompt_id);
@@ -295,16 +212,6 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
       formData.append('json_schema', JSON.stringify(agent.json_schema));
     }
 
-    if (agent.limited_token_mode && agent.token_limit) {
-      formData.append('limited_token_mode', 'True');
-      formData.append('token_limit', JSON.stringify(agent.token_limit));
-    } else formData.append('token_limit', '0');
-
-    if (agent.limited_request_mode && agent.request_limit) {
-      formData.append('limited_request_mode', 'True');
-      formData.append('request_limit', JSON.stringify(agent.request_limit));
-    } else formData.append('request_limit', '0');
-
     try {
       setPublishLoading(true);
       const response =
@@ -360,7 +267,7 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
       const data = await response.json();
       const tools: OptionType[] = data.tools.map((tool: UserToolType) => ({
         id: tool.id,
-        label: tool.customName ? tool.customName : tool.displayName,
+        label: tool.displayName,
         icon: `/toolIcons/tool_${tool.name}.svg`,
       }));
       setUserTools(tools);
@@ -377,26 +284,6 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
     getPrompts();
   }, [token]);
 
-  // Auto-select default source if none selected
-  useEffect(() => {
-    if (sourceDocs && sourceDocs.length > 0 && selectedSourceIds.size === 0) {
-      const defaultSource = sourceDocs.find((s) => s.name === 'Default');
-      if (defaultSource) {
-        setSelectedSourceIds(
-          new Set([
-            defaultSource.id || defaultSource.retriever || defaultSource.name,
-          ]),
-        );
-      } else {
-        setSelectedSourceIds(
-          new Set([
-            sourceDocs[0].id || sourceDocs[0].retriever || sourceDocs[0].name,
-          ]),
-        );
-      }
-    }
-  }, [sourceDocs, selectedSourceIds.size]);
-
   useEffect(() => {
     if ((mode === 'edit' || mode === 'draft') && agentId) {
       const getAgent = async () => {
@@ -406,34 +293,10 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
           throw new Error('Failed to fetch agent');
         }
         const data = await response.json();
-
-        if (data.sources && data.sources.length > 0) {
-          const mappedSources = data.sources.map((sourceId: string) => {
-            if (sourceId === 'default') {
-              const defaultSource = sourceDocs?.find(
-                (source) => source.name === 'Default',
-              );
-              return defaultSource?.retriever || 'classic';
-            }
-            return sourceId;
-          });
-          setSelectedSourceIds(new Set(mappedSources));
-        } else if (data.source) {
-          if (data.source === 'default') {
-            const defaultSource = sourceDocs?.find(
-              (source) => source.name === 'Default',
-            );
-            setSelectedSourceIds(
-              new Set([defaultSource?.retriever || 'classic']),
-            );
-          } else {
-            setSelectedSourceIds(new Set([data.source]));
-          }
-        } else if (data.retriever) {
+        if (data.source) setSelectedSourceIds(new Set([data.source]));
+        else if (data.retriever)
           setSelectedSourceIds(new Set([data.retriever]));
-        }
-
-        if (data.tool_details) setSelectedTools(data.tool_details);
+        if (data.tools) setSelectedToolIds(new Set(data.tools));
         if (data.status === 'draft') setEffectiveMode('draft');
         if (data.json_schema) {
           const jsonText = JSON.stringify(data.json_schema, null, 2);
@@ -448,68 +311,39 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
   }, [agentId, mode, token]);
 
   useEffect(() => {
-    const selectedSources = Array.from(selectedSourceIds)
-      .map((id) =>
-        sourceDocs?.find(
-          (source) =>
-            source.id === id || source.retriever === id || source.name === id,
-        ),
-      )
-      .filter(Boolean);
-
-    if (selectedSources.length > 0) {
-      // Handle multiple sources
-      if (selectedSources.length > 1) {
-        // Multiple sources selected - store in sources array
-        const sourceIds = selectedSources
-          .map((source) => source?.id)
-          .filter((id): id is string => Boolean(id));
+    const selectedSource = Array.from(selectedSourceIds).map((id) =>
+      sourceDocs?.find(
+        (source) =>
+          source.id === id || source.retriever === id || source.name === id,
+      ),
+    );
+    if (selectedSource[0]?.model === embeddingsName) {
+      if (selectedSource[0] && 'id' in selectedSource[0]) {
         setAgent((prev) => ({
           ...prev,
-          sources: sourceIds,
-          source: '', // Clear single source for multiple sources
+          source: selectedSource[0]?.id || 'default',
           retriever: '',
         }));
-      } else {
-        // Single source selected - maintain backward compatibility
-        const selectedSource = selectedSources[0];
-        if (selectedSource?.model === embeddingsName) {
-          if (selectedSource && 'id' in selectedSource) {
-            setAgent((prev) => ({
-              ...prev,
-              source: selectedSource?.id || 'default',
-              sources: [], // Clear sources array for single source
-              retriever: '',
-            }));
-          } else {
-            setAgent((prev) => ({
-              ...prev,
-              source: '',
-              sources: [], // Clear sources array
-              retriever: selectedSource?.retriever || 'classic',
-            }));
-          }
-        }
-      }
-    } else {
-      // No sources selected
-      setAgent((prev) => ({
-        ...prev,
-        source: '',
-        sources: [],
-        retriever: '',
-      }));
+      } else
+        setAgent((prev) => ({
+          ...prev,
+          source: '',
+          retriever: selectedSource[0]?.retriever || 'classic',
+        }));
     }
   }, [selectedSourceIds]);
 
   useEffect(() => {
+    const selectedTool = Array.from(selectedToolIds).map((id) =>
+      userTools.find((tool) => tool.id === id),
+    );
     setAgent((prev) => ({
       ...prev,
-      tools: Array.from(selectedTools)
+      tools: selectedTool
         .map((tool) => tool?.id)
         .filter((id): id is string => typeof id === 'string'),
     }));
-  }, [selectedTools]);
+  }, [selectedToolIds]);
 
   useEffect(() => {
     if (isPublishable()) dispatch(setSelectedAgent(agent));
@@ -534,7 +368,7 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
     setHasChanges(isChanged);
   }, [agent, dispatch, effectiveMode, imageFile, jsonSchemaText]);
   return (
-    <div className="flex flex-col px-4 pt-4 pb-2 max-[1179px]:min-h-[100dvh] min-[1180px]:h-[100dvh] md:px-12 md:pt-12 md:pb-3">
+    <div className="p-4 md:p-12">
       <div className="flex items-center gap-3 px-4">
         <button
           className="rounded-full border p-3 text-sm text-gray-400 dark:border-0 dark:bg-[#28292D] dark:text-gray-500 dark:hover:bg-[#2E2F34]"
@@ -547,7 +381,7 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
         </p>
       </div>
       <div className="mt-5 flex w-full flex-wrap items-center justify-between gap-2 px-4">
-        <h1 className="text-eerie-black m-0 text-[32px] font-bold lg:text-[40px] dark:text-white">
+        <h1 className="text-eerie-black m-0 text-[40px] font-bold dark:text-white">
           {modeConfig[effectiveMode].heading}
         </h1>
         <div className="flex flex-wrap items-center gap-1">
@@ -615,9 +449,9 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
           </button>
         </div>
       </div>
-      <div className="mt-3 flex w-full flex-1 grid-cols-5 flex-col gap-10 rounded-[30px] bg-[#F6F6F6] p-5 max-[1179px]:overflow-visible min-[1180px]:grid min-[1180px]:gap-5 min-[1180px]:overflow-hidden dark:bg-[#383838]">
-        <div className="scrollbar-thin col-span-2 flex flex-col gap-5 max-[1179px]:overflow-visible min-[1180px]:max-h-full min-[1180px]:overflow-y-auto min-[1180px]:pr-3">
-          <div className="dark:bg-raisin-black rounded-[30px] bg-white px-6 py-3 dark:text-[#E0E0E0]">
+      <div className="mt-5 flex w-full grid-cols-5 flex-col gap-10 min-[1180px]:grid min-[1180px]:gap-5">
+        <div className="col-span-2 flex flex-col gap-5">
+          <div className="rounded-[30px] bg-[#F6F6F6] px-6 py-3 dark:bg-[#383838] dark:text-[#E0E0E0]">
             <h2 className="text-lg font-semibold">Meta</h2>
             <input
               className="border-silver text-jet dark:bg-raisin-black dark:text-bright-gray dark:placeholder:text-silver mt-3 w-full rounded-3xl border bg-white px-5 py-3 text-sm outline-hidden placeholder:text-gray-400 dark:border-[#7E7E7E]"
@@ -627,7 +461,7 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
               onChange={(e) => setAgent({ ...agent, name: e.target.value })}
             />
             <textarea
-              className="border-silver text-jet dark:bg-raisin-black dark:text-bright-gray dark:placeholder:text-silver mt-3 h-32 w-full rounded-xl border bg-white px-5 py-4 text-sm outline-hidden placeholder:text-gray-400 dark:border-[#7E7E7E]"
+              className="border-silver text-jet dark:bg-raisin-black dark:text-bright-gray dark:placeholder:text-silver mt-3 h-32 w-full rounded-3xl border bg-white px-5 py-4 text-sm outline-hidden placeholder:text-gray-400 dark:border-[#7E7E7E]"
               placeholder="Describe your agent"
               value={agent.description}
               onChange={(e) =>
@@ -650,7 +484,7 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
               />
             </div>
           </div>
-          <div className="dark:bg-raisin-black rounded-[30px] bg-white px-6 py-3 dark:text-[#E0E0E0]">
+          <div className="rounded-[30px] bg-[#F6F6F6] px-6 py-3 dark:bg-[#383838] dark:text-[#E0E0E0]">
             <h2 className="text-lg font-semibold">Source</h2>
             <div className="mt-3">
               <div className="flex flex-wrap items-center gap-1">
@@ -665,18 +499,18 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
                 >
                   {selectedSourceIds.size > 0
                     ? Array.from(selectedSourceIds)
-                        .map((id) => {
-                          const matchedDoc = sourceDocs?.find(
-                            (source) =>
-                              source.id === id ||
-                              source.name === id ||
-                              source.retriever === id,
-                          );
-                          return matchedDoc?.name || `External KB`;
-                        })
+                        .map(
+                          (id) =>
+                            sourceDocs?.find(
+                              (source) =>
+                                source.id === id ||
+                                source.name === id ||
+                                source.retriever === id,
+                            )?.name,
+                        )
                         .filter(Boolean)
                         .join(', ')
-                    : 'Select sources'}
+                    : 'Select source'}
                 </button>
                 <MultiSelectPopup
                   isOpen={isSourcePopupOpen}
@@ -691,38 +525,13 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
                   }
                   selectedIds={selectedSourceIds}
                   onSelectionChange={(newSelectedIds: Set<string | number>) => {
-                    if (
-                      newSelectedIds.size === 0 &&
-                      sourceDocs &&
-                      sourceDocs.length > 0
-                    ) {
-                      const defaultSource = sourceDocs.find(
-                        (s) => s.name === 'Default',
-                      );
-                      if (defaultSource) {
-                        setSelectedSourceIds(
-                          new Set([
-                            defaultSource.id ||
-                              defaultSource.retriever ||
-                              defaultSource.name,
-                          ]),
-                        );
-                      } else {
-                        setSelectedSourceIds(
-                          new Set([
-                            sourceDocs[0].id ||
-                              sourceDocs[0].retriever ||
-                              sourceDocs[0].name,
-                          ]),
-                        );
-                      }
-                    } else {
-                      setSelectedSourceIds(newSelectedIds);
-                    }
+                    setSelectedSourceIds(newSelectedIds);
+                    setIsSourcePopupOpen(false);
                   }}
-                  title="Select Sources"
+                  title="Select Source"
                   searchPlaceholder="Search sources..."
-                  noOptionsMessage="No sources available"
+                  noOptionsMessage="No source available"
+                  singleSelect={true}
                 />
               </div>
               <div className="mt-3">
@@ -744,7 +553,7 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
               </div>
             </div>
           </div>
-          <div className="dark:bg-raisin-black rounded-[30px] bg-white px-6 py-3 dark:text-[#E0E0E0]">
+          <div className="rounded-[30px] bg-[#F6F6F6] px-6 py-3 dark:bg-[#383838] dark:text-[#E0E0E0]">
             <div className="flex flex-wrap items-end gap-1">
               <div className="min-w-20 grow basis-full sm:basis-0">
                 <Prompts
@@ -781,21 +590,23 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
               </button>
             </div>
           </div>
-          <div className="dark:bg-raisin-black rounded-[30px] bg-white px-6 py-3 dark:text-[#E0E0E0]">
+          <div className="rounded-[30px] bg-[#F6F6F6] px-6 py-3 dark:bg-[#383838] dark:text-[#E0E0E0]">
             <h2 className="text-lg font-semibold">Tools</h2>
             <div className="mt-3 flex flex-wrap items-center gap-1">
               <button
                 ref={toolAnchorButtonRef}
                 onClick={() => setIsToolsPopupOpen(!isToolsPopupOpen)}
                 className={`border-silver dark:bg-raisin-black w-full truncate rounded-3xl border bg-white px-5 py-3 text-left text-sm dark:border-[#7E7E7E] ${
-                  selectedTools.length > 0
+                  selectedToolIds.size > 0
                     ? 'text-jet dark:text-bright-gray'
                     : 'dark:text-silver text-gray-400'
                 }`}
               >
-                {selectedTools.length > 0
-                  ? selectedTools
-                      .map((tool) => tool.display_name || tool.name)
+                {selectedToolIds.size > 0
+                  ? Array.from(selectedToolIds)
+                      .map(
+                        (id) => userTools.find((tool) => tool.id === id)?.label,
+                      )
                       .filter(Boolean)
                       .join(', ')
                   : 'Select tools'}
@@ -805,17 +616,9 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
                 onClose={() => setIsToolsPopupOpen(false)}
                 anchorRef={toolAnchorButtonRef}
                 options={userTools}
-                selectedIds={new Set(selectedTools.map((tool) => tool.id))}
+                selectedIds={selectedToolIds}
                 onSelectionChange={(newSelectedIds: Set<string | number>) =>
-                  setSelectedTools(
-                    userTools
-                      .filter((tool) => newSelectedIds.has(tool.id))
-                      .map((tool) => ({
-                        id: String(tool.id),
-                        name: tool.label,
-                        display_name: tool.label,
-                      })),
-                  )
+                  setSelectedToolIds(newSelectedIds)
                 }
                 title="Select Tools"
                 searchPlaceholder="Search tools..."
@@ -823,7 +626,7 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
               />
             </div>
           </div>
-          <div className="dark:bg-raisin-black rounded-[30px] bg-white px-6 py-3 dark:text-[#E0E0E0]">
+          <div className="rounded-[30px] bg-[#F6F6F6] px-6 py-3 dark:bg-[#383838] dark:text-[#E0E0E0]">
             <h2 className="text-lg font-semibold">Agent type</h2>
             <div className="mt-3">
               <Dropdown
@@ -848,11 +651,9 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
               />
             </div>
           </div>
-          <div className="dark:bg-raisin-black rounded-[30px] bg-white px-6 py-3 dark:text-[#E0E0E0]">
+          <div className="rounded-[30px] bg-[#F6F6F6] px-6 py-3 dark:bg-[#383838] dark:text-[#E0E0E0]">
             <button
-              onClick={() =>
-                setIsAdvancedSectionExpanded(!isAdvancedSectionExpanded)
-              }
+              onClick={() => setIsJsonSchemaExpanded(!isJsonSchemaExpanded)}
               className="flex w-full items-center justify-between text-left focus:outline-none"
             >
               <div>
@@ -861,7 +662,7 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
               <div className="ml-4 flex items-center">
                 <svg
                   className={`h-5 w-5 transform transition-transform duration-200 ${
-                    isAdvancedSectionExpanded ? 'rotate-180' : ''
+                    isJsonSchemaExpanded ? 'rotate-180' : ''
                   }`}
                   fill="none"
                   stroke="currentColor"
@@ -876,7 +677,7 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
                 </svg>
               </div>
             </button>
-            {isAdvancedSectionExpanded && (
+            {isJsonSchemaExpanded && (
               <div className="mt-3">
                 <div>
                   <h2 className="text-sm font-medium">JSON response schema</h2>
@@ -919,124 +720,13 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
                       : 'Invalid JSON - fix to enable saving'}
                   </div>
                 )}
-
-                <div className="mt-6">
-                  <div className="flex items-center justify-between">
-                    <div>
-                      <h2 className="text-sm font-medium">Token limiting</h2>
-                      <p className="mt-1 text-xs text-gray-600 dark:text-gray-400">
-                        Limit daily total tokens that can be used by this agent
-                      </p>
-                    </div>
-                    <button
-                      onClick={() => {
-                        const newTokenMode = !agent.limited_token_mode;
-                        setAgent({
-                          ...agent,
-                          limited_token_mode: newTokenMode,
-                          limited_request_mode: newTokenMode
-                            ? false
-                            : agent.limited_request_mode,
-                        });
-                      }}
-                      className={`relative h-6 w-11 rounded-full transition-colors ${
-                        agent.limited_token_mode
-                          ? 'bg-purple-30'
-                          : 'bg-gray-300 dark:bg-gray-600'
-                      }`}
-                    >
-                      <span
-                        className={`absolute top-0.5 h-5 w-5 transform rounded-full bg-white transition-transform ${
-                          agent.limited_token_mode ? '' : '-translate-x-5'
-                        }`}
-                      />
-                    </button>
-                  </div>
-                  <input
-                    type="number"
-                    min="0"
-                    value={agent.token_limit || ''}
-                    onChange={(e) =>
-                      setAgent({
-                        ...agent,
-                        token_limit: e.target.value
-                          ? parseInt(e.target.value)
-                          : undefined,
-                      })
-                    }
-                    disabled={!agent.limited_token_mode}
-                    placeholder="Enter token limit"
-                    className={`border-silver text-jet dark:bg-raisin-black dark:text-bright-gray dark:placeholder:text-silver mt-2 w-full rounded-3xl border bg-white px-5 py-3 text-sm outline-hidden placeholder:text-gray-400 dark:border-[#7E7E7E] ${
-                      !agent.limited_token_mode
-                        ? 'cursor-not-allowed opacity-50'
-                        : ''
-                    }`}
-                  />
-                </div>
-
-                <div className="mt-6">
-                  <div className="flex items-center justify-between">
-                    <div>
-                      <h2 className="text-sm font-medium">Request limiting</h2>
-                      <p className="mt-1 text-xs text-gray-600 dark:text-gray-400">
-                        Limit daily total requests that can be made to this
-                        agent
-                      </p>
-                    </div>
-                    <button
-                      onClick={() => {
-                        const newRequestMode = !agent.limited_request_mode;
-                        setAgent({
-                          ...agent,
-                          limited_request_mode: newRequestMode,
-                          limited_token_mode: newRequestMode
-                            ? false
-                            : agent.limited_token_mode,
-                        });
-                      }}
-                      className={`relative h-6 w-11 rounded-full transition-colors ${
-                        agent.limited_request_mode
-                          ? 'bg-purple-30'
-                          : 'bg-gray-300 dark:bg-gray-600'
-                      }`}
-                    >
-                      <span
-                        className={`absolute top-0.5 h-5 w-5 transform rounded-full bg-white transition-transform ${
-                          agent.limited_request_mode ? '' : '-translate-x-5'
-                        }`}
-                      />
-                    </button>
-                  </div>
-                  <input
-                    type="number"
-                    min="0"
-                    value={agent.request_limit || ''}
-                    onChange={(e) =>
-                      setAgent({
-                        ...agent,
-                        request_limit: e.target.value
-                          ? parseInt(e.target.value)
-                          : undefined,
-                      })
-                    }
-                    disabled={!agent.limited_request_mode}
-                    placeholder="Enter request limit"
-                    className={`border-silver text-jet dark:bg-raisin-black dark:text-bright-gray dark:placeholder:text-silver mt-2 w-full rounded-3xl border bg-white px-5 py-3 text-sm outline-hidden placeholder:text-gray-400 dark:border-[#7E7E7E] ${
-                      !agent.limited_request_mode
-                        ? 'cursor-not-allowed opacity-50'
-                        : ''
-                    }`}
-                  />
-                </div>
               </div>
             )}
           </div>
         </div>
-        <div className="col-span-3 flex flex-col gap-2 max-[1179px]:h-auto max-[1179px]:px-0 max-[1179px]:py-0 min-[1180px]:h-full min-[1180px]:py-2 dark:text-[#E0E0E0]">
+        <div className="col-span-3 flex flex-col gap-3 rounded-[30px] bg-[#F6F6F6] px-6 py-3 dark:bg-[#383838] dark:text-[#E0E0E0]">
           <h2 className="text-lg font-semibold">Preview</h2>
-          <div className="flex-1 max-[1179px]:overflow-visible min-[1180px]:min-h-0 min-[1180px]:overflow-hidden">
-            <AgentPreviewArea />
-          </div>
+          <AgentPreviewArea />
         </div>
       </div>
       <ConfirmationModal
@@ -1073,9 +763,9 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
 function AgentPreviewArea() {
   const selectedAgent = useSelector(selectSelectedAgent);
   return (
-    <div className="dark:bg-raisin-black w-full rounded-[30px] border border-[#F6F6F6] bg-white max-[1179px]:h-[600px] min-[1180px]:h-full dark:border-[#7E7E7E]">
+    <div className="dark:bg-raisin-black h-full w-full rounded-[30px] border border-[#F6F6F6] bg-white max-[1180px]:h-192 dark:border-[#7E7E7E]">
       {selectedAgent?.status === 'published' ? (
-        <div className="flex h-full w-full flex-col overflow-hidden rounded-[30px]">
+        <div className="flex h-full w-full flex-col justify-end overflow-auto rounded-[30px]">
           <AgentPreview />
         </div>
       ) : (

frontend/src/agents/SharedAgent.tsx

@@ -6,7 +6,7 @@ import { useParams } from 'react-router-dom';
 import userService from '../api/services/userService';
 import NoFilesDarkIcon from '../assets/no-files-dark.svg';
 import NoFilesIcon from '../assets/no-files.svg';
-import AgentImage from '../components/AgentImage';
+import Robot from '../assets/robot.svg';
 import MessageInput from '../components/MessageInput';
 import Spinner from '../components/Spinner';
 import ConversationMessages from '../conversation/ConversationMessages';
@@ -152,8 +152,12 @@ export default function SharedAgent() {
   return (
     <div className="relative h-full w-full">
       <div className="absolute top-5 left-4 hidden items-center gap-3 sm:flex">
-        <AgentImage
-          src={sharedAgent.image}
+        <img
+          src={
+            sharedAgent.image && sharedAgent.image.trim() !== ''
+              ? sharedAgent.image
+              : Robot
+          }
           alt="agent-logo"
           className="h-6 w-6 rounded-full object-contain"
         />
@@ -177,15 +181,13 @@ export default function SharedAgent() {
           />
         </div>
         <div className="flex w-[95%] max-w-[1500px] flex-col items-center pb-2 md:w-9/12 lg:w-8/12 xl:w-8/12 2xl:w-6/12">
-          <div className="w-full px-2">
-            <MessageInput
-              onSubmit={(text) => handleQuestionSubmission(text)}
-              loading={status === 'loading'}
-              showSourceButton={sharedAgent ? false : true}
-              showToolButton={sharedAgent ? false : true}
-              autoFocus={false}
-            />
-          </div>
+          <MessageInput
+            onSubmit={(text) => handleQuestionSubmission(text)}
+            loading={status === 'loading'}
+            showSourceButton={sharedAgent ? false : true}
+            showToolButton={sharedAgent ? false : true}
+            autoFocus={false}
+          />
           <p className="text-gray-4000 dark:text-sonic-silver hidden w-screen self-center bg-transparent py-2 text-center text-xs md:inline md:w-full">
             {t('tagline')}
           </p>

frontend/src/agents/SharedAgentCard.tsx

@@ -1,19 +1,13 @@
-import AgentImage from '../components/AgentImage';
+import Robot from '../assets/robot.svg';
 import { Agent } from './types';
 
 export default function SharedAgentCard({ agent }: { agent: Agent }) {
-  // Check if shared metadata exists and has properties (type is 'any' so we validate it's a non-empty object)
-  const hasSharedMetadata =
-    agent.shared_metadata &&
-    typeof agent.shared_metadata === 'object' &&
-    agent.shared_metadata !== null &&
-    Object.keys(agent.shared_metadata).length > 0;
   return (
     <div className="border-dark-gray dark:border-grey flex w-full max-w-[720px] flex-col rounded-3xl border p-6 shadow-xs sm:w-fit sm:min-w-[480px]">
       <div className="flex items-center gap-3">
         <div className="flex h-12 w-12 items-center justify-center overflow-hidden rounded-full p-1">
-          <AgentImage
-            src={agent.image}
+          <img
+            src={agent.image && agent.image.trim() !== '' ? agent.image : Robot}
             className="h-full w-full rounded-full object-contain"
           />
         </div>
@@ -26,7 +20,7 @@ export default function SharedAgentCard({ agent }: { agent: Agent }) {
           </p>
         </div>
       </div>
-      {hasSharedMetadata && (
+      {agent.shared_metadata && (
         <div className="mt-4 flex items-center gap-8">
           {agent.shared_metadata?.shared_by && (
             <p className="text-eerie-black text-xs font-light sm:text-sm dark:text-[#E0E0E0]">

frontend/src/agents/agentPreviewSlice.ts

@@ -1,20 +1,19 @@
 import { createAsyncThunk, createSlice, PayloadAction } from '@reduxjs/toolkit';
-
-import {
-  handleFetchAnswer,
-  handleFetchAnswerSteaming,
-} from '../conversation/conversationHandlers';
 import {
   Answer,
   ConversationState,
   Query,
   Status,
 } from '../conversation/conversationModels';
-import store from '../store';
 import {
-  clearAttachments,
+  handleFetchAnswer,
+  handleFetchAnswerSteaming,
+} from '../conversation/conversationHandlers';
+import {
   selectCompletedAttachments,
+  clearAttachments,
 } from '../upload/uploadSlice';
+import store from '../store';
 
 const initialState: ConversationState = {
   queries: [],
@@ -57,7 +56,7 @@ export const fetchPreviewAnswer = createAsyncThunk<
           question,
           signal,
           state.preference.token,
-          state.preference.selectedDocs,
+          state.preference.selectedDocs!,
           null, // No conversation ID for previews
           state.preference.prompt.id,
           state.preference.chunks,
@@ -128,7 +127,7 @@ export const fetchPreviewAnswer = createAsyncThunk<
           question,
           signal,
           state.preference.token,
-          state.preference.selectedDocs,
+          state.preference.selectedDocs!,
           null, // No conversation ID for previews
           state.preference.prompt.id,
           state.preference.chunks,

frontend/src/agents/agents.config.ts

@@ -1,42 +0,0 @@
-import userService from '../api/services/userService';
-import {
-  selectAgents,
-  selectTemplateAgents,
-  selectSharedAgents,
-  setAgents,
-  setTemplateAgents,
-  setSharedAgents,
-} from '../preferences/preferenceSlice';
-
-export const agentSectionsConfig = [
-  {
-    id: 'template',
-    title: 'By DocsGPT',
-    description: 'Agents provided by DocsGPT',
-    showNewAgentButton: false,
-    emptyStateDescription: 'No template agents found.',
-    fetchAgents: (token: string | null) => userService.getTemplateAgents(token),
-    selectData: selectTemplateAgents,
-    updateAction: setTemplateAgents,
-  },
-  {
-    id: 'user',
-    title: 'By me',
-    description: 'Agents created or published by you',
-    showNewAgentButton: true,
-    emptyStateDescription: 'You don’t have any created agents yet.',
-    fetchAgents: (token: string | null) => userService.getAgents(token),
-    selectData: selectAgents,
-    updateAction: setAgents,
-  },
-  {
-    id: 'shared',
-    title: 'Shared with me',
-    description: 'Agents imported by using a public link',
-    showNewAgentButton: false,
-    emptyStateDescription: 'No shared agents found.',
-    fetchAgents: (token: string | null) => userService.getSharedAgents(token),
-    selectData: selectSharedAgents,
-    updateAction: setSharedAgents,
-  },
-];

frontend/src/agents/index.tsx

@@ -1,9 +1,37 @@
-import { Route, Routes } from 'react-router-dom';
+import { SyntheticEvent, useEffect, useRef, useState } from 'react';
+import { useDispatch, useSelector } from 'react-redux';
+import { Route, Routes, useNavigate } from 'react-router-dom';
 
+import userService from '../api/services/userService';
+import Edit from '../assets/edit.svg';
+import Link from '../assets/link-gray.svg';
+import Monitoring from '../assets/monitoring.svg';
+import Pin from '../assets/pin.svg';
+import Trash from '../assets/red-trash.svg';
+import Robot from '../assets/robot.svg';
+import ThreeDots from '../assets/three-dots.svg';
+import UnPin from '../assets/unpin.svg';
+import ContextMenu, { MenuOption } from '../components/ContextMenu';
+import Spinner from '../components/Spinner';
+import {
+  setConversation,
+  updateConversationId,
+} from '../conversation/conversationSlice';
+import ConfirmationModal from '../modals/ConfirmationModal';
+import { ActiveState } from '../models/misc';
+import {
+  selectAgents,
+  selectSelectedAgent,
+  selectSharedAgents,
+  selectToken,
+  setAgents,
+  setSelectedAgent,
+  setSharedAgents,
+} from '../preferences/preferenceSlice';
 import AgentLogs from './AgentLogs';
-import AgentsList from './AgentsList';
 import NewAgent from './NewAgent';
 import SharedAgent from './SharedAgent';
+import { Agent } from './types';
 
 export default function Agents() {
   return (
@@ -16,3 +44,431 @@ export default function Agents() {
     </Routes>
   );
 }
+
+const sectionConfig = {
+  user: {
+    title: 'By me',
+    description: 'Agents created or published by you',
+    showNewAgentButton: true,
+    emptyStateDescription: 'You don’t have any created agents yet',
+  },
+  shared: {
+    title: 'Shared with me',
+    description: 'Agents imported by using a public link',
+    showNewAgentButton: false,
+    emptyStateDescription: 'No shared agents found',
+  },
+};
+
+function AgentsList() {
+  const dispatch = useDispatch();
+  const token = useSelector(selectToken);
+  const agents = useSelector(selectAgents);
+  const sharedAgents = useSelector(selectSharedAgents);
+  const selectedAgent = useSelector(selectSelectedAgent);
+
+  const [loadingUserAgents, setLoadingUserAgents] = useState<boolean>(true);
+  const [loadingSharedAgents, setLoadingSharedAgents] = useState<boolean>(true);
+
+  const getAgents = async () => {
+    try {
+      setLoadingUserAgents(true);
+      const response = await userService.getAgents(token);
+      if (!response.ok) throw new Error('Failed to fetch agents');
+      const data = await response.json();
+      dispatch(setAgents(data));
+      setLoadingUserAgents(false);
+    } catch (error) {
+      console.error('Error:', error);
+      setLoadingUserAgents(false);
+    }
+  };
+
+  const getSharedAgents = async () => {
+    try {
+      setLoadingSharedAgents(true);
+      const response = await userService.getSharedAgents(token);
+      if (!response.ok) throw new Error('Failed to fetch shared agents');
+      const data = await response.json();
+      dispatch(setSharedAgents(data));
+      setLoadingSharedAgents(false);
+    } catch (error) {
+      console.error('Error:', error);
+      setLoadingSharedAgents(false);
+    }
+  };
+
+  useEffect(() => {
+    getAgents();
+    getSharedAgents();
+    dispatch(setConversation([]));
+    dispatch(
+      updateConversationId({
+        query: { conversationId: null },
+      }),
+    );
+    if (selectedAgent) dispatch(setSelectedAgent(null));
+  }, [token]);
+  return (
+    <div className="p-4 md:p-12">
+      <h1 className="text-eerie-black mb-0 text-[40px] font-bold dark:text-[#E0E0E0]">
+        Agents
+      </h1>
+      <p className="dark:text-gray-4000 mt-5 text-[15px] text-[#71717A]">
+        Discover and create custom versions of DocsGPT that combine
+        instructions, extra knowledge, and any combination of skills
+      </p>
+      {/* Premade agents section */}
+      {/* <div className="mt-6">
+        <h2 className="text-[18px] font-semibold text-[#18181B] dark:text-[#E0E0E0]">
+          Premade by DocsGPT
+        </h2>
+        <div className="mt-4 flex w-full flex-wrap gap-4">
+          {Array.from({ length: 5 }, (_, index) => (
+            <div
+              key={index}
+              className="relative flex h-44 w-48 flex-col justify-between rounded-[1.2rem] bg-[#F6F6F6] px-6 py-5 dark:bg-[#383838]"
+            >
+              <button onClick={() => {}} className="absolute right-4 top-4">
+                <img
+                  src={Copy}
+                  alt={'use-agent'}
+                  className="h-[19px] w-[19px]"
+                />
+              </button>
+              <div className="w-full">
+                <div className="flex w-full items-center px-1">
+                  <img
+                    src={Robot}
+                    alt="agent-logo"
+                    className="h-7 w-7 rounded-full"
+                  />
+                </div>
+                <div className="mt-2">
+                  <p
+                    title={''}
+                    className="truncate px-1 text-[13px] font-semibold capitalize leading-relaxed text-raisin-black-light dark:text-bright-gray"
+                  >
+                    {}
+                  </p>
+                  <p className="mt-1 h-20 overflow-auto px-1 text-[12px] leading-relaxed text-old-silver dark:text-sonic-silver-light">
+                    {}
+                  </p>
+                </div>
+              </div>
+              <div className="absolute bottom-4 right-4"></div>
+            </div>
+          ))}
+        </div>
+      </div> */}
+      <AgentSection
+        agents={agents ?? []}
+        updateAgents={(updatedAgents) => {
+          dispatch(setAgents(updatedAgents));
+        }}
+        loading={loadingUserAgents}
+        section="user"
+      />
+      <AgentSection
+        agents={sharedAgents ?? []}
+        updateAgents={(updatedAgents) => {
+          dispatch(setSharedAgents(updatedAgents));
+        }}
+        loading={loadingSharedAgents}
+        section="shared"
+      />
+    </div>
+  );
+}
+
+function AgentSection({
+  agents,
+  updateAgents,
+  loading,
+  section,
+}: {
+  agents: Agent[];
+  updateAgents?: (agents: Agent[]) => void;
+  loading: boolean;
+  section: keyof typeof sectionConfig;
+}) {
+  const navigate = useNavigate();
+  return (
+    <div className="mt-8 flex flex-col gap-4">
+      <div className="flex w-full items-center justify-between">
+        <div className="flex flex-col gap-2">
+          <h2 className="text-[18px] font-semibold text-[#18181B] dark:text-[#E0E0E0]">
+            {sectionConfig[section].title}
+          </h2>
+          <p className="text-[13px] text-[#71717A]">
+            {sectionConfig[section].description}
+          </p>
+        </div>
+        {sectionConfig[section].showNewAgentButton && (
+          <button
+            className="bg-purple-30 hover:bg-violets-are-blue rounded-full px-4 py-2 text-sm text-white"
+            onClick={() => navigate('/agents/new')}
+          >
+            New Agent
+          </button>
+        )}
+      </div>
+      <div>
+        {loading ? (
+          <div className="flex h-72 w-full items-center justify-center">
+            <Spinner />
+          </div>
+        ) : agents && agents.length > 0 ? (
+          <div className="grid grid-cols-1 gap-4 sm:flex sm:flex-wrap">
+            {agents.map((agent, idx) => (
+              <AgentCard
+                key={agent.id}
+                agent={agent}
+                agents={agents}
+                updateAgents={updateAgents}
+                section={section}
+              />
+            ))}
+          </div>
+        ) : (
+          <div className="flex h-72 w-full flex-col items-center justify-center gap-3 text-base text-[#18181B] dark:text-[#E0E0E0]">
+            <p>{sectionConfig[section].emptyStateDescription}</p>
+            {sectionConfig[section].showNewAgentButton && (
+              <button
+                className="bg-purple-30 hover:bg-violets-are-blue ml-2 rounded-full px-4 py-2 text-sm text-white"
+                onClick={() => navigate('/agents/new')}
+              >
+                New Agent
+              </button>
+            )}
+          </div>
+        )}
+      </div>
+    </div>
+  );
+}
+
+function AgentCard({
+  agent,
+  agents,
+  updateAgents,
+  section,
+}: {
+  agent: Agent;
+  agents: Agent[];
+  updateAgents?: (agents: Agent[]) => void;
+  section: keyof typeof sectionConfig;
+}) {
+  const navigate = useNavigate();
+  const dispatch = useDispatch();
+  const token = useSelector(selectToken);
+
+  const [isMenuOpen, setIsMenuOpen] = useState<boolean>(false);
+  const [deleteConfirmation, setDeleteConfirmation] =
+    useState<ActiveState>('INACTIVE');
+
+  const menuRef = useRef<HTMLDivElement>(null);
+
+  const togglePin = async () => {
+    try {
+      const response = await userService.togglePinAgent(agent.id ?? '', token);
+      if (!response.ok) throw new Error('Failed to pin agent');
+      const updatedAgents = agents.map((prevAgent) => {
+        if (prevAgent.id === agent.id)
+          return { ...prevAgent, pinned: !prevAgent.pinned };
+        return prevAgent;
+      });
+      updateAgents?.(updatedAgents);
+    } catch (error) {
+      console.error('Error:', error);
+    }
+  };
+
+  const handleHideSharedAgent = async () => {
+    try {
+      const response = await userService.removeSharedAgent(
+        agent.id ?? '',
+        token,
+      );
+      if (!response.ok) throw new Error('Failed to hide shared agent');
+      const updatedAgents = agents.filter(
+        (prevAgent) => prevAgent.id !== agent.id,
+      );
+      updateAgents?.(updatedAgents);
+    } catch (error) {
+      console.error('Error:', error);
+    }
+  };
+
+  const menuOptionsConfig: Record<string, MenuOption[]> = {
+    user: [
+      {
+        icon: Monitoring,
+        label: 'Logs',
+        onClick: (e: SyntheticEvent) => {
+          e.stopPropagation();
+          navigate(`/agents/logs/${agent.id}`);
+        },
+        variant: 'primary',
+        iconWidth: 14,
+        iconHeight: 14,
+      },
+      {
+        icon: Edit,
+        label: 'Edit',
+        onClick: (e: SyntheticEvent) => {
+          e.stopPropagation();
+          navigate(`/agents/edit/${agent.id}`);
+        },
+        variant: 'primary',
+        iconWidth: 14,
+        iconHeight: 14,
+      },
+      ...(agent.status === 'published'
+        ? [
+            {
+              icon: agent.pinned ? UnPin : Pin,
+              label: agent.pinned ? 'Unpin' : 'Pin agent',
+              onClick: (e: SyntheticEvent) => {
+                e.stopPropagation();
+                togglePin();
+              },
+              variant: 'primary' as const,
+              iconWidth: 18,
+              iconHeight: 18,
+            },
+          ]
+        : []),
+      {
+        icon: Trash,
+        label: 'Delete',
+        onClick: (e: SyntheticEvent) => {
+          e.stopPropagation();
+          setDeleteConfirmation('ACTIVE');
+        },
+        variant: 'danger',
+        iconWidth: 13,
+        iconHeight: 13,
+      },
+    ],
+    shared: [
+      {
+        icon: Link,
+        label: 'Open',
+        onClick: (e: SyntheticEvent) => {
+          e.stopPropagation();
+          navigate(`/agents/shared/${agent.shared_token}`);
+        },
+        variant: 'primary',
+        iconWidth: 12,
+        iconHeight: 12,
+      },
+      {
+        icon: agent.pinned ? UnPin : Pin,
+        label: agent.pinned ? 'Unpin' : 'Pin agent',
+        onClick: (e: SyntheticEvent) => {
+          e.stopPropagation();
+          togglePin();
+        },
+        variant: 'primary',
+        iconWidth: 18,
+        iconHeight: 18,
+      },
+      {
+        icon: Trash,
+        label: 'Remove',
+        onClick: (e: SyntheticEvent) => {
+          e.stopPropagation();
+          handleHideSharedAgent();
+        },
+        variant: 'danger',
+        iconWidth: 13,
+        iconHeight: 13,
+      },
+    ],
+  };
+
+  const menuOptions = menuOptionsConfig[section] || [];
+
+  const handleClick = () => {
+    if (section === 'user') {
+      if (agent.status === 'published') {
+        dispatch(setSelectedAgent(agent));
+        navigate(`/`);
+      }
+    }
+    if (section === 'shared') {
+      navigate(`/agents/shared/${agent.shared_token}`);
+    }
+  };
+
+  const handleDelete = async (agentId: string) => {
+    const response = await userService.deleteAgent(agentId, token);
+    if (!response.ok) throw new Error('Failed to delete agent');
+    const data = await response.json();
+    dispatch(setAgents(agents.filter((prevAgent) => prevAgent.id !== data.id)));
+  };
+  return (
+    <div
+      className={`relative flex h-44 w-full flex-col justify-between rounded-[1.2rem] bg-[#F6F6F6] px-6 py-5 hover:bg-[#ECECEC] md:w-48 dark:bg-[#383838] dark:hover:bg-[#383838]/80 ${agent.status === 'published' && 'cursor-pointer'}`}
+      onClick={(e) => {
+        e.stopPropagation();
+        handleClick();
+      }}
+    >
+      <div
+        ref={menuRef}
+        onClick={(e) => {
+          e.stopPropagation();
+          setIsMenuOpen(true);
+        }}
+        className="absolute top-4 right-4 z-10 cursor-pointer"
+      >
+        <img src={ThreeDots} alt={'use-agent'} className="h-[19px] w-[19px]" />
+        <ContextMenu
+          isOpen={isMenuOpen}
+          setIsOpen={setIsMenuOpen}
+          options={menuOptions}
+          anchorRef={menuRef}
+          position="bottom-right"
+          offset={{ x: 0, y: 0 }}
+        />
+      </div>
+      <div className="w-full">
+        <div className="flex w-full items-center gap-1 px-1">
+          <img
+            src={agent.image && agent.image.trim() !== '' ? agent.image : Robot}
+            alt={`${agent.name}`}
+            className="h-7 w-7 rounded-full object-contain"
+          />
+          {agent.status === 'draft' && (
+            <p className="text-xs text-black opacity-50 dark:text-[#E0E0E0]">{`(Draft)`}</p>
+          )}
+        </div>
+        <div className="mt-2">
+          <p
+            title={agent.name}
+            className="truncate px-1 text-[13px] leading-relaxed font-semibold text-[#020617] capitalize dark:text-[#E0E0E0]"
+          >
+            {agent.name}
+          </p>
+          <p className="dark:text-sonic-silver-light mt-1 h-20 overflow-auto px-1 text-[12px] leading-relaxed text-[#64748B]">
+            {agent.description}
+          </p>
+        </div>
+      </div>
+      <ConfirmationModal
+        message="Are you sure you want to delete this agent?"
+        modalState={deleteConfirmation}
+        setModalState={setDeleteConfirmation}
+        submitLabel="Delete"
+        handleSubmit={() => {
+          handleDelete(agent.id || '');
+          setDeleteConfirmation('INACTIVE');
+        }}
+        cancelLabel="Cancel"
+        variant="danger"
+      />
+    </div>
+  );
+}

frontend/src/agents/types/index.ts

@@ -10,7 +10,6 @@ export type Agent = {
   description: string;
   image: string;
   source: string;
-  sources?: string[];
   chunks: string;
   retriever: string;
   prompt_id: string;
@@ -28,8 +27,4 @@ export type Agent = {
   updated_at?: string;
   last_used_at?: string;
   json_schema?: object;
-  limited_token_mode?: boolean;
-  token_limit?: number;
-  limited_request_mode?: boolean;
-  request_limit?: number;
 };