Merge pull request #926 from siiddhantt/feature

Feature: Logging token usage info to MongoDB

.gitignore

@@ -75,6 +75,7 @@ target/
 
 # Jupyter Notebook
 .ipynb_checkpoints
+**/*.ipynb
 
 # IPython
 profile_default/
@@ -172,3 +173,4 @@ application/vectors/
 node_modules/
 .vscode/settings.json
 models/
+model/

README.md

@@ -40,7 +40,7 @@ You can find our roadmap [here](https://github.com/orgs/arc53/projects/2). Pleas
 
 | Name                                                                  | Base Model  | Requirements (or similar) |
 | --------------------------------------------------------------------- | ----------- | ------------------------- |
-| [Docsgpt-7b-falcon](https://huggingface.co/Arc53/docsgpt-7b-falcon)   | Falcon-7b   | 1xA10G gpu                |
+| [Docsgpt-7b-mistral](https://huggingface.co/Arc53/docsgpt-7b-mistral)   | Mistral-7b   | 1xA10G gpu                |
 | [Docsgpt-14b](https://huggingface.co/Arc53/docsgpt-14b)               | llama-2-14b | 2xA10 gpu's               |
 | [Docsgpt-40b-falcon](https://huggingface.co/Arc53/docsgpt-40b-falcon) | falcon-40b  | 8xA10G gpu's              |
 
@@ -123,7 +123,7 @@ docker compose -f docker-compose-dev.yaml up -d
 > [!Note]
 > Make sure you have Python 3.10 or 3.11 installed.
 
-1. Export required environment variables or prepare a `.env` file in the `/application` folder:
+1. Export required environment variables or prepare a `.env` file in the project folder:
    - Copy [.env_sample](https://github.com/arc53/DocsGPT/blob/main/application/.env_sample) and create `.env`.
 
 (check out [`application/core/settings.py`](application/core/settings.py) if you want to see more config options.)
@@ -152,11 +152,12 @@ You can use the script below, or download it manually from [here](https://d3dg10
 wget https://d3dg1063dc54p9.cloudfront.net/models/embeddings/mpnet-base-v2.zip
 unzip mpnet-base-v2.zip -d model
 rm mpnet-base-v2.zip
+```
 
-4. Change to the `application/` subdir by the command `cd application/` and install dependencies for the backend:
+4. Install dependencies for the backend:
 
 ```commandline
-pip install -r requirements.txt
+pip install -r application/requirements.txt
 ```
 
 5. Run the app using `flask --app application/app.py run --host=0.0.0.0 --port=7091`.

SECURITY.md

@@ -0,0 +1,14 @@
+# Security Policy
+
+## Supported Versions
+
+Supported Versions:
+
+Currently, we support security patches by committing changes and bumping the version published on Github.
+
+## Reporting a Vulnerability
+
+Found a vulnerability? Please email us:
+
+security@arc53.com
+

application/Dockerfile

@@ -2,15 +2,17 @@ FROM python:3.11-slim-bullseye as builder
 
 # Tiktoken requires Rust toolchain, so build it in a separate stage
 RUN apt-get update && apt-get install -y gcc curl
+RUN apt-get install -y wget unzip
+RUN wget https://d3dg1063dc54p9.cloudfront.net/models/embeddings/mpnet-base-v2.zip
+RUN unzip mpnet-base-v2.zip -d model
+RUN rm mpnet-base-v2.zip
 RUN curl https://sh.rustup.rs -sSf | sh -s -- -y && apt-get install --reinstall libc6-dev -y
 ENV PATH="/root/.cargo/bin:${PATH}"
 RUN pip install --upgrade pip && pip install tiktoken==0.5.2
 COPY requirements.txt .
 RUN pip install -r requirements.txt
-RUN apt-get install -y wget unzip
-RUN wget https://d3dg1063dc54p9.cloudfront.net/models/embeddings/mpnet-base-v2.zip
-RUN unzip mpnet-base-v2.zip -d model
-RUN rm mpnet-base-v2.zip
+
+
 
 FROM python:3.11-slim-bullseye
 

application/api/answer/routes.py

@@ -8,17 +8,14 @@ import traceback
 
 from pymongo import MongoClient
 from bson.objectid import ObjectId
-from transformers import GPT2TokenizerFast
-
 
 
 from application.core.settings import settings
-from application.vectorstore.vector_creator import VectorCreator
 from application.llm.llm_creator import LLMCreator
+from application.retriever.retriever_creator import RetrieverCreator
 from application.error import bad_request
 
 
-
 logger = logging.getLogger(__name__)
 
 mongo = MongoClient(settings.MONGO_URI)
@@ -26,17 +23,23 @@ db = mongo["docsgpt"]
 conversations_collection = db["conversations"]
 vectors_collection = db["vectors"]
 prompts_collection = db["prompts"]
-answer = Blueprint('answer', __name__)
+api_key_collection = db["api_keys"]
+answer = Blueprint("answer", __name__)
 
-if settings.LLM_NAME == "gpt4":
-    gpt_model = 'gpt-4'
+gpt_model = ""
+# to have some kind of default behaviour
+if settings.LLM_NAME == "openai":
+    gpt_model = "gpt-3.5-turbo"
 elif settings.LLM_NAME == "anthropic":
-    gpt_model = 'claude-2'
-else:
-    gpt_model = 'gpt-3.5-turbo'
+    gpt_model = "claude-2"
+
+if settings.MODEL_NAME:  # in case there is particular model name configured
+    gpt_model = settings.MODEL_NAME
 
 # load the prompts
-current_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+current_dir = os.path.dirname(
+    os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+)
 with open(os.path.join(current_dir, "prompts", "chat_combine_default.txt"), "r") as f:
     chat_combine_template = f.read()
 
@@ -47,7 +50,7 @@ with open(os.path.join(current_dir, "prompts", "chat_combine_creative.txt"), "r"
     chat_combine_creative = f.read()
 
 with open(os.path.join(current_dir, "prompts", "chat_combine_strict.txt"), "r") as f:
-    chat_combine_strict = f.read()    
+    chat_combine_strict = f.read()
 
 api_key_set = settings.API_KEY is not None
 embeddings_key_set = settings.EMBEDDINGS_KEY is not None
@@ -58,11 +61,6 @@ async def async_generate(chain, question, chat_history):
     return result
 
 
-def count_tokens(string):
-    tokenizer = GPT2TokenizerFast.from_pretrained('gpt2')
-    return len(tokenizer(string)['input_ids'])
-
-
 def run_async_chain(chain, question, chat_history):
     loop = asyncio.new_event_loop()
     asyncio.set_event_loop(loop)
@@ -75,10 +73,17 @@ def run_async_chain(chain, question, chat_history):
     return result
 
 
+def get_data_from_api_key(api_key):
+    data = api_key_collection.find_one({"key": api_key})
+    if data is None:
+        return bad_request(401, "Invalid API key")
+    return data
+
+
 def get_vectorstore(data):
     if "active_docs" in data:
         if data["active_docs"].split("/")[0] == "default":
-                vectorstore = ""
+            vectorstore = ""
         elif data["active_docs"].split("/")[0] == "local":
             vectorstore = "indexes/" + data["active_docs"]
         else:
@@ -92,83 +97,99 @@ def get_vectorstore(data):
 
 
 def is_azure_configured():
-    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 complete_stream(question, docsearch, chat_history, api_key, prompt_id, conversation_id):
-    llm = LLMCreator.create_llm(settings.LLM_NAME, api_key=api_key)
-
-    if prompt_id == 'default':
-        prompt = chat_combine_template
-    elif prompt_id == 'creative':
-        prompt = chat_combine_creative
-    elif prompt_id == 'strict':
-        prompt = chat_combine_strict
-    else:
-        prompt = prompts_collection.find_one({"_id": ObjectId(prompt_id)})["content"]
-
-    docs = docsearch.search(question, k=2)
-    if settings.LLM_NAME == "llama.cpp":
-        docs = [docs[0]]
-    # join all page_content together with a newline
-    docs_together = "\n".join([doc.page_content for doc in docs])
-    p_chat_combine = prompt.replace("{summaries}", docs_together)
-    messages_combine = [{"role": "system", "content": p_chat_combine}]
-    source_log_docs = []
-    for doc in docs:
-        if doc.metadata:
-            source_log_docs.append({"title": doc.metadata['title'].split('/')[-1], "text": doc.page_content})
-        else:
-            source_log_docs.append({"title": doc.page_content, "text": doc.page_content})
-
-    if len(chat_history) > 1:
-        tokens_current_history = 0
-        # count tokens in history
-        chat_history.reverse()
-        for i in chat_history:
-            if "prompt" in i and "response" in i:
-                tokens_batch = count_tokens(i["prompt"]) + count_tokens(i["response"])
-                if tokens_current_history + tokens_batch < settings.TOKENS_MAX_HISTORY:
-                    tokens_current_history += tokens_batch
-                    messages_combine.append({"role": "user", "content": i["prompt"]})
-                    messages_combine.append({"role": "system", "content": i["response"]})
-    messages_combine.append({"role": "user", "content": question})
-
-    response_full = ""
-    completion = llm.gen_stream(model=gpt_model, engine=settings.AZURE_DEPLOYMENT_NAME,
-                                messages=messages_combine)
-    for line in completion:
-        data = json.dumps({"answer": str(line)})
-        response_full += str(line)
-        yield f"data: {data}\n\n"
-
-    # save conversation to database
-    if conversation_id is not None:
+def save_conversation(conversation_id, question, response, source_log_docs, llm):
+    if conversation_id is not None and conversation_id != "None":
         conversations_collection.update_one(
             {"_id": ObjectId(conversation_id)},
-            {"$push": {"queries": {"prompt": question, "response": response_full, "sources": source_log_docs}}},
+            {
+                "$push": {
+                    "queries": {
+                        "prompt": question,
+                        "response": response,
+                        "sources": source_log_docs,
+                    }
+                }
+            },
         )
 
     else:
         # create new conversation
         # generate summary
-        messages_summary = [{"role": "assistant", "content": "Summarise following conversation in no more than 3 "
-                                                             "words, respond ONLY with the summary, use the same "
-                                                             "language as the system \n\nUser: " + question + "\n\n" +
-                                                             "AI: " +
-                                                             response_full},
-                            {"role": "user", "content": "Summarise following conversation in no more than 3 words, "
-                                                        "respond ONLY with the summary, use the same language as the "
-                                                        "system"}]
+        messages_summary = [
+            {
+                "role": "assistant",
+                "content": "Summarise following conversation in no more than 3 "
+                "words, respond ONLY with the summary, use the same "
+                "language as the system \n\nUser: "
+                + question
+                + "\n\n"
+                + "AI: "
+                + response,
+            },
+            {
+                "role": "user",
+                "content": "Summarise following conversation in no more than 3 words, "
+                "respond ONLY with the summary, use the same language as the "
+                "system",
+            },
+        ]
 
-        completion = llm.gen(model=gpt_model, engine=settings.AZURE_DEPLOYMENT_NAME,
-                             messages=messages_summary, max_tokens=30)
+        completion = llm.gen(model=gpt_model, messages=messages_summary, max_tokens=30)
         conversation_id = conversations_collection.insert_one(
-            {"user": "local",
-             "date": datetime.datetime.utcnow(),
-             "name": completion,
-             "queries": [{"prompt": question, "response": response_full, "sources": source_log_docs}]}
+            {
+                "user": "local",
+                "date": datetime.datetime.utcnow(),
+                "name": completion,
+                "queries": [
+                    {
+                        "prompt": question,
+                        "response": response,
+                        "sources": source_log_docs,
+                    }
+                ],
+            }
         ).inserted_id
+    return conversation_id
+
+
+def get_prompt(prompt_id):
+    if prompt_id == "default":
+        prompt = chat_combine_template
+    elif prompt_id == "creative":
+        prompt = chat_combine_creative
+    elif prompt_id == "strict":
+        prompt = chat_combine_strict
+    else:
+        prompt = prompts_collection.find_one({"_id": ObjectId(prompt_id)})["content"]
+    return prompt
+
+
+def complete_stream(question, retriever, conversation_id, user_api_key):
+
+    response_full = ""
+    source_log_docs = []
+    answer = retriever.gen()
+    for line in answer:
+        if "answer" in line:
+            response_full += str(line["answer"])
+            data = json.dumps(line)
+            yield f"data: {data}\n\n"
+        elif "source" in line:
+            source_log_docs.append(line["source"])
+
+    llm = LLMCreator.create_llm(
+        settings.LLM_NAME, api_key=settings.API_KEY, user_api_key=user_api_key
+    )
+    conversation_id = save_conversation(
+        conversation_id, question, response_full, source_log_docs, llm
+    )
 
     # send data.type = "end" to indicate that the stream has ended as json
     data = json.dumps({"type": "id", "id": str(conversation_id)})
@@ -182,36 +203,68 @@ def stream():
     data = request.get_json()
     # get parameter from url question
     question = data["question"]
-    history = data["history"]
-    # history to json object from string
-    history = json.loads(history)
-    conversation_id = data["conversation_id"]
-    if 'prompt_id' in data:
+    if "history" not in data:
+        history = []
+    else:
+        history = data["history"]
+        history = json.loads(history)
+    if "conversation_id" not in data:
+        conversation_id = None
+    else:
+        conversation_id = data["conversation_id"]
+    if "prompt_id" in data:
         prompt_id = data["prompt_id"]
     else:
-        prompt_id = 'default'
+        prompt_id = "default"
+    if "selectedDocs" in data and data["selectedDocs"] is None:
+        chunks = 0
+    elif "chunks" in data:
+        chunks = int(data["chunks"])
+    else:
+        chunks = 2
+
+    prompt = get_prompt(prompt_id)
 
     # check if active_docs is set
 
-    if not api_key_set:
-        api_key = data["api_key"]
+    if "api_key" in data:
+        data_key = get_data_from_api_key(data["api_key"])
+        source = {"active_docs": data_key["source"]}
+        user_api_key = data["api_key"]
+    elif "active_docs" in data:
+        source = {"active_docs": data["active_docs"]}
+        user_api_key = None
     else:
-        api_key = settings.API_KEY
-    if not embeddings_key_set:
-        embeddings_key = data["embeddings_key"]
+        source = {}
+        user_api_key = None
+
+    if (
+        source["active_docs"].split("/")[0] == "default"
+        or source["active_docs"].split("/")[0] == "local"
+    ):
+        retriever_name = "classic"
     else:
-        embeddings_key = settings.EMBEDDINGS_KEY
-    if "active_docs" in data:
-        vectorstore = get_vectorstore({"active_docs": data["active_docs"]})
-    else:
-        vectorstore = ""
-    docsearch = VectorCreator.create_vectorstore(settings.VECTOR_STORE, vectorstore, embeddings_key)
+        retriever_name = source["active_docs"]
+
+    retriever = RetrieverCreator.create_retriever(
+        retriever_name,
+        question=question,
+        source=source,
+        chat_history=history,
+        prompt=prompt,
+        chunks=chunks,
+        gpt_model=gpt_model,
+        user_api_key=user_api_key,
+    )
 
     return Response(
-        complete_stream(question, docsearch,
-                        chat_history=history, api_key=api_key,
-                        prompt_id=prompt_id,
-                        conversation_id=conversation_id), mimetype="text/event-stream"
+        complete_stream(
+            question=question,
+            retriever=retriever,
+            conversation_id=conversation_id,
+            user_api_key=user_api_key,
+        ),
+        mimetype="text/event-stream",
     )
 
 
@@ -219,121 +272,72 @@ def stream():
 def api_answer():
     data = request.get_json()
     question = data["question"]
-    history = data["history"]
+    if "history" not in data:
+        history = []
+    else:
+        history = data["history"]
     if "conversation_id" not in data:
         conversation_id = None
     else:
         conversation_id = data["conversation_id"]
     print("-" * 5)
-    if not api_key_set:
-        api_key = data["api_key"]
-    else:
-        api_key = settings.API_KEY
-    if not embeddings_key_set:
-        embeddings_key = data["embeddings_key"]
-    else:
-        embeddings_key = settings.EMBEDDINGS_KEY
-    if 'prompt_id' in data:
+    if "prompt_id" in data:
         prompt_id = data["prompt_id"]
     else:
-        prompt_id = 'default'
-
-    if prompt_id == 'default':
-        prompt = chat_combine_template
-    elif prompt_id == 'creative':
-        prompt = chat_combine_creative
-    elif prompt_id == 'strict':
-        prompt = chat_combine_strict
+        prompt_id = "default"
+    if "chunks" in data:
+        chunks = int(data["chunks"])
     else:
-        prompt = prompts_collection.find_one({"_id": ObjectId(prompt_id)})["content"]
+        chunks = 2
+
+    prompt = get_prompt(prompt_id)
 
     # use try and except  to check for exception
     try:
         # check if the vectorstore is set
-        vectorstore = get_vectorstore(data)
-        # loading the index and the store and the prompt template
-        # Note if you have used other embeddings than OpenAI, you need to change the embeddings
-        docsearch = VectorCreator.create_vectorstore(settings.VECTOR_STORE, vectorstore, embeddings_key)
-
-
-        llm = LLMCreator.create_llm(settings.LLM_NAME, api_key=api_key)
-
-
-
-        docs = docsearch.search(question, k=2)
-        # join all page_content together with a newline
-        docs_together = "\n".join([doc.page_content for doc in docs])
-        p_chat_combine = prompt.replace("{summaries}", docs_together)
-        messages_combine = [{"role": "system", "content": p_chat_combine}]
-        source_log_docs = []
-        for doc in docs:
-            if doc.metadata:
-                source_log_docs.append({"title": doc.metadata['title'].split('/')[-1], "text": doc.page_content})
-            else:
-                source_log_docs.append({"title": doc.page_content, "text": doc.page_content})
-        # join all page_content together with a newline
-
-
-        if len(history) > 1:
-            tokens_current_history = 0
-            # count tokens in history
-            history.reverse()
-            for i in history:
-                if "prompt" in i and "response" in i:
-                    tokens_batch = count_tokens(i["prompt"]) + count_tokens(i["response"])
-                    if tokens_current_history + tokens_batch < settings.TOKENS_MAX_HISTORY:
-                        tokens_current_history += tokens_batch
-                        messages_combine.append({"role": "user", "content": i["prompt"]})
-                        messages_combine.append({"role": "system", "content": i["response"]})
-        messages_combine.append({"role": "user", "content": question})
-
-
-        completion = llm.gen(model=gpt_model, engine=settings.AZURE_DEPLOYMENT_NAME,
-                                    messages=messages_combine)
-
-
-        result = {"answer": completion, "sources": source_log_docs}
-        logger.debug(result)
-
-        # generate conversationId
-        if conversation_id is not None:
-            conversations_collection.update_one(
-                {"_id": ObjectId(conversation_id)},
-                {"$push": {"queries": {"prompt": question,
-                                       "response": result["answer"], "sources": result['sources']}}},
-            )
-
+        if "api_key" in data:
+            data_key = get_data_from_api_key(data["api_key"])
+            source = {"active_docs": data_key["source"]}
+            user_api_key = data["api_key"]
         else:
-            # create new conversation
-            # generate summary
-            messages_summary = [
-                {"role": "assistant", "content": "Summarise following conversation in no more than 3 words, "
-                    "respond ONLY with the summary, use the same language as the system \n\n"
-                    "User: " + question + "\n\n" + "AI: " + result["answer"]},
-                {"role": "user", "content": "Summarise following conversation in no more than 3 words, "
-                    "respond ONLY with the summary, use the same language as the system"}
-            ]
+            source = {data}
+            user_api_key = None
 
-            completion = llm.gen(
-                model=gpt_model,
-                engine=settings.AZURE_DEPLOYMENT_NAME,
-                messages=messages_summary,
-                max_tokens=30
-            )
-            conversation_id = conversations_collection.insert_one(
-                {"user": "local",
-                "date": datetime.datetime.utcnow(),
-                "name": completion,
-                "queries": [{"prompt": question, "response": result["answer"], "sources": source_log_docs}]}
-            ).inserted_id
+        if (
+            source["active_docs"].split("/")[0] == "default"
+            or source["active_docs"].split("/")[0] == "local"
+        ):
+            retriever_name = "classic"
+        else:
+            retriever_name = source["active_docs"]
 
-        result["conversation_id"] = str(conversation_id)
+        retriever = RetrieverCreator.create_retriever(
+            retriever_name,
+            question=question,
+            source=source,
+            chat_history=history,
+            prompt=prompt,
+            chunks=chunks,
+            gpt_model=gpt_model,
+            user_api_key=user_api_key,
+        )
+        source_log_docs = []
+        response_full = ""
+        for line in retriever.gen():
+            if "source" in line:
+                source_log_docs.append(line["source"])
+            elif "answer" in line:
+                response_full += line["answer"]
+
+        llm = LLMCreator.create_llm(
+            settings.LLM_NAME, api_key=settings.API_KEY, user_api_key=user_api_key
+        )
+
+        result = {"answer": response_full, "sources": source_log_docs}
+        result["conversation_id"] = save_conversation(
+            conversation_id, question, response_full, source_log_docs, llm
+        )
 
-        # mock result
-        # result = {
-        #     "answer": "The answer is 42",
-        #     "sources": ["https://en.wikipedia.org/wiki/42_(number)", "https://en.wikipedia.org/wiki/42_(number)"]
-        # }
         return result
     except Exception as e:
         # print whole traceback
@@ -348,27 +352,38 @@ def api_search():
     # get parameter from url question
     question = data["question"]
 
-    if not embeddings_key_set:
-        if "embeddings_key" in data:
-            embeddings_key = data["embeddings_key"]
-        else:
-            embeddings_key = settings.EMBEDDINGS_KEY
+    if "api_key" in data:
+        data_key = get_data_from_api_key(data["api_key"])
+        source = {"active_docs": data_key["source"]}
+        user_api_key = data["api_key"]
+    elif "active_docs" in data:
+        source = {"active_docs": data["active_docs"]}
+        user_api_key = None
     else:
-        embeddings_key = settings.EMBEDDINGS_KEY
-    if "active_docs" in data:
-        vectorstore = get_vectorstore({"active_docs": data["active_docs"]})
+        source = {}
+        user_api_key = None
+    if "chunks" in data:
+        chunks = int(data["chunks"])
     else:
-        vectorstore = ""
-    docsearch = VectorCreator.create_vectorstore(settings.VECTOR_STORE, vectorstore, embeddings_key)
+        chunks = 2
 
-    docs = docsearch.search(question, k=2)
-
-    source_log_docs = []
-    for doc in docs:
-        if doc.metadata:
-            source_log_docs.append({"title": doc.metadata['title'].split('/')[-1], "text": doc.page_content})
-        else:
-            source_log_docs.append({"title": doc.page_content, "text": doc.page_content})
-        #yield f"data:{data}\n\n"
-    return source_log_docs
+    if (
+        source["active_docs"].split("/")[0] == "default"
+        or source["active_docs"].split("/")[0] == "local"
+    ):
+        retriever_name = "classic"
+    else:
+        retriever_name = source["active_docs"]
 
+    retriever = RetrieverCreator.create_retriever(
+        retriever_name,
+        question=question,
+        source=source,
+        chat_history=[],
+        prompt="default",
+        chunks=chunks,
+        gpt_model=gpt_model,
+        user_api_key=user_api_key,
+    )
+    docs = retriever.search()
+    return docs

application/api/user/routes.py

@@ -1,11 +1,14 @@
 import os
+import uuid
+import shutil
 from flask import Blueprint, request, jsonify
+from urllib.parse import urlparse
 import requests
 from pymongo import MongoClient
 from bson.objectid import ObjectId
 from werkzeug.utils import secure_filename
 
-from application.api.user.tasks import ingest
+from application.api.user.tasks import ingest, ingest_remote
 
 from application.core.settings import settings
 from application.vectorstore.vector_creator import VectorCreator
@@ -16,6 +19,7 @@ conversations_collection = db["conversations"]
 vectors_collection = db["vectors"]
 prompts_collection = db["prompts"]
 feedback_collection = db["feedback"]
+api_key_collection = db["api_keys"]
 user = Blueprint('user', __name__)
 
 current_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
@@ -36,7 +40,7 @@ def delete_conversation():
 @user.route("/api/get_conversations", methods=["get"])
 def get_conversations():
     # provides a list of conversations
-    conversations = conversations_collection.find().sort("date", -1)
+    conversations = conversations_collection.find().sort("date", -1).limit(30)
     list_conversations = []
     for conversation in conversations:
         list_conversations.append({"id": str(conversation["_id"]), "name": conversation["name"]})
@@ -133,25 +137,64 @@ def upload_file():
         return {"status": "no name"}
     job_name = secure_filename(request.form["name"])
     # check if the post request has the file part
-    if "file" not in request.files:
-        print("No file part")
-        return {"status": "no file"}
-    file = request.files["file"]
-    if file.filename == "":
+    files = request.files.getlist("file")
+        
+    if not files or all(file.filename == '' for file in files):
         return {"status": "no file name"}
 
-    if file:
-        filename = secure_filename(file.filename)
-        # save dir
-        save_dir = os.path.join(current_dir, settings.UPLOAD_FOLDER, user, job_name)
-        # create dir if not exists
-        if not os.path.exists(save_dir):
-            os.makedirs(save_dir)
+    # Directory where files will be saved
+    save_dir = os.path.join(current_dir, settings.UPLOAD_FOLDER, user, job_name)
+    os.makedirs(save_dir, exist_ok=True)
+    
+    if len(files) > 1:
+        # Multiple files; prepare them for zip
+        temp_dir = os.path.join(save_dir, "temp")
+        os.makedirs(temp_dir, exist_ok=True)
+        
+        for file in files:
+            filename = secure_filename(file.filename)
+            file.save(os.path.join(temp_dir, filename))
+        
+        # Use shutil.make_archive to zip the temp directory
+        zip_path = shutil.make_archive(base_name=os.path.join(save_dir, job_name), format='zip', root_dir=temp_dir)
+        final_filename = os.path.basename(zip_path)
+        
+        # Clean up the temporary directory after zipping
+        shutil.rmtree(temp_dir)
+    else:
+        # Single file
+        file = files[0]
+        final_filename = secure_filename(file.filename)
+        file_path = os.path.join(save_dir, final_filename)
+        file.save(file_path)
+    
+    # Call ingest with the single file or zipped file
+    task = ingest.delay(settings.UPLOAD_FOLDER, [".rst", ".md", ".pdf", ".txt", ".docx", 
+    ".csv", ".epub", ".html", ".mdx"],
+    job_name, final_filename, user)
+    
+    return {"status": "ok", "task_id": task.id}
+    
+@user.route("/api/remote", methods=["POST"])
+def upload_remote():
+    """Upload a remote source to get vectorized and indexed."""
+    if "user" not in request.form:
+        return {"status": "no user"}
+    user = secure_filename(request.form["user"])
+    if "source" not in request.form:
+        return {"status": "no source"}
+    source = secure_filename(request.form["source"])
+    if "name" not in request.form:
+        return {"status": "no name"}
+    job_name = secure_filename(request.form["name"])
+    # check if the post request has the file part
+    if "data" not in request.form:
+        print("No data")
+        return {"status": "no data"}
+    source_data = request.form["data"]
 
-        file.save(os.path.join(save_dir, filename))
-        task = ingest.delay(settings.UPLOAD_FOLDER, [".rst", ".md", ".pdf", ".txt", ".docx", 
-        ".csv", ".epub", ".html", ".mdx"],
-         job_name, filename, user)
+    if source_data:
+        task = ingest_remote.delay(source_data=source_data, job_name=job_name, user=user, loader=source)
         # task id
         task_id = task.id
         return {"status": "ok", "task_id": task_id}
@@ -208,6 +251,34 @@ def combined_json():
         for index in data_remote:
             index["location"] = "remote"
             data.append(index)
+    if 'duckduck_search' in settings.RETRIEVERS_ENABLED:
+        data.append(
+            {
+                "name": "DuckDuckGo Search",
+                "language": "en",
+                "version": "",
+                "description": "duckduck_search",
+                "fullName": "DuckDuckGo Search",
+                "date": "duckduck_search",
+                "docLink": "duckduck_search",
+                "model": settings.EMBEDDINGS_NAME,
+                "location": "custom",
+            }
+        )
+    if 'brave_search' in settings.RETRIEVERS_ENABLED:
+        data.append(
+            {
+                "name": "Brave Search",
+                "language": "en",
+                "version": "",
+                "description": "brave_search",
+                "fullName": "Brave Search",
+                "date": "brave_search",
+                "docLink": "brave_search",
+                "model": settings.EMBEDDINGS_NAME,
+                "location": "custom",
+            }
+        )
 
     return jsonify(data)
 
@@ -219,25 +290,32 @@ def check_docs():
     # split docs on / and take first part
     if data["docs"].split("/")[0] == "local":
         return {"status": "exists"}
-    vectorstore = "vectors/" + data["docs"]
+    vectorstore = "vectors/" + secure_filename(data["docs"])
     base_path = "https://raw.githubusercontent.com/arc53/DocsHUB/main/"
     if os.path.exists(vectorstore) or data["docs"] == "default":
         return {"status": "exists"}
     else:
-        r = requests.get(base_path + vectorstore + "index.faiss")
+        file_url = urlparse(base_path + vectorstore + "index.faiss")
+        
+        if (
+            file_url.scheme in ['https'] and 
+            file_url.netloc == 'raw.githubusercontent.com' and 
+            file_url.path.startswith('/arc53/DocsHUB/main/')
+        ):
+            r = requests.get(file_url.geturl())
+            if r.status_code != 200:
+                return {"status": "null"}
+            else:
+                if not os.path.exists(vectorstore):
+                    os.makedirs(vectorstore)
+                with open(vectorstore + "index.faiss", "wb") as f:
+                    f.write(r.content)
 
-        if r.status_code != 200:
-            return {"status": "null"}
+                r = requests.get(base_path + vectorstore + "index.pkl")
+                with open(vectorstore + "index.pkl", "wb") as f:
+                    f.write(r.content)
         else:
-            if not os.path.exists(vectorstore):
-                os.makedirs(vectorstore)
-            with open(vectorstore + "index.faiss", "wb") as f:
-                f.write(r.content)
-
-            # download the store
-            r = requests.get(base_path + vectorstore + "index.pkl")
-            with open(vectorstore + "index.pkl", "wb") as f:
-                f.write(r.content)
+            return {"status": "null"}
 
         return {"status": "loaded"}
 
@@ -317,5 +395,52 @@ def update_prompt_name():
 
 
 
+@user.route("/api/get_api_keys", methods=["GET"])
+def get_api_keys():
+    user = "local"
+    keys = api_key_collection.find({"user": user})
+    list_keys = []
+    for key in keys:
+        list_keys.append({
+            "id": str(key["_id"]),
+            "name": key["name"],
+            "key": key["key"][:4] + "..." + key["key"][-4:],
+            "source": key["source"],
+            "prompt_id": key["prompt_id"],
+            "chunks": key["chunks"]
+        })
+    return jsonify(list_keys)
 
+@user.route("/api/create_api_key", methods=["POST"])
+def create_api_key():
+    data = request.get_json()
+    name = data["name"]
+    source = data["source"]
+    prompt_id = data["prompt_id"]
+    chunks = data["chunks"]
+    key = str(uuid.uuid4())
+    user = "local"
+    resp = api_key_collection.insert_one(
+        {
+            "name": name,
+            "key": key,
+            "source": source,
+            "user": user,
+            "prompt_id": prompt_id,
+            "chunks": chunks
+        }
+    )
+    new_id = str(resp.inserted_id)
+    return {"id": new_id, "key": key}
+
+@user.route("/api/delete_api_key", methods=["POST"])
+def delete_api_key():
+    data = request.get_json()
+    id = data["id"]
+    api_key_collection.delete_one(
+        {
+            "_id": ObjectId(id),
+        }
+    )
+    return {"status": "ok"}
 

application/api/user/tasks.py

@@ -1,7 +1,12 @@
-from application.worker import ingest_worker
+from application.worker import ingest_worker, remote_worker
 from application.celery import celery
 
 @celery.task(bind=True)
 def ingest(self, directory, formats, name_job, filename, user):
     resp = ingest_worker(self, directory, formats, name_job, filename, user)
     return resp
+
+@celery.task(bind=True)
+def ingest_remote(self, source_data, job_name, user, loader):
+    resp = remote_worker(self, source_data, job_name, user, loader)
+    return resp

application/app.py

@@ -40,5 +40,5 @@ def after_request(response):
     return response
 
 if __name__ == "__main__":
-    app.run(debug=True, port=7091)
+    app.run(debug=settings.FLASK_DEBUG_MODE, port=7091)
 

application/core/settings.py

@@ -3,11 +3,13 @@ from typing import Optional
 import os
 
 from pydantic_settings import BaseSettings
+
 current_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
 
 class Settings(BaseSettings):
     LLM_NAME: str = "docsgpt"
+    MODEL_NAME: Optional[str] = None # if LLM_NAME is openai, MODEL_NAME can be gpt-4 or gpt-3.5-turbo
     EMBEDDINGS_NAME: str = "huggingface_sentence-transformers/all-mpnet-base-v2"
     CELERY_BROKER_URL: str = "redis://localhost:6379/0"
     CELERY_RESULT_BACKEND: str = "redis://localhost:6379/1"
@@ -15,7 +17,8 @@ class Settings(BaseSettings):
     MODEL_PATH: str = os.path.join(current_dir, "models/docsgpt-7b-f16.gguf")
     TOKENS_MAX_HISTORY: int = 150
     UPLOAD_FOLDER: str = "inputs"
-    VECTOR_STORE: str = "faiss"  # "faiss" or "elasticsearch"
+    VECTOR_STORE: str = "faiss"  # "faiss" or "elasticsearch" or "qdrant"
+    RETRIEVERS_ENABLED: list = ["classic_rag", "duckduck_search"] # also brave_search
 
     API_URL: str = "http://localhost:7091"  # backend url for celery worker
 
@@ -27,17 +30,39 @@ class Settings(BaseSettings):
     AZURE_EMBEDDINGS_DEPLOYMENT_NAME: Optional[str] = None  # azure deployment name for embeddings
 
     # elasticsearch
-    ELASTIC_CLOUD_ID: Optional[str] = None # cloud id for elasticsearch
-    ELASTIC_USERNAME: Optional[str] = None # username for elasticsearch
-    ELASTIC_PASSWORD: Optional[str] = None # password for elasticsearch
-    ELASTIC_URL: Optional[str] = None # url for elasticsearch
-    ELASTIC_INDEX: Optional[str] = "docsgpt" # index name for elasticsearch
+    ELASTIC_CLOUD_ID: Optional[str] = None  # cloud id for elasticsearch
+    ELASTIC_USERNAME: Optional[str] = None  # username for elasticsearch
+    ELASTIC_PASSWORD: Optional[str] = None  # password for elasticsearch
+    ELASTIC_URL: Optional[str] = None  # url for elasticsearch
+    ELASTIC_INDEX: Optional[str] = "docsgpt"  # index name for elasticsearch
 
     # SageMaker config
-    SAGEMAKER_ENDPOINT: Optional[str] = None # SageMaker endpoint name
-    SAGEMAKER_REGION: Optional[str] = None # SageMaker region name
-    SAGEMAKER_ACCESS_KEY: Optional[str] = None # SageMaker access key
-    SAGEMAKER_SECRET_KEY: Optional[str] = None # SageMaker secret key
+    SAGEMAKER_ENDPOINT: Optional[str] = None  # SageMaker endpoint name
+    SAGEMAKER_REGION: Optional[str] = None  # SageMaker region name
+    SAGEMAKER_ACCESS_KEY: Optional[str] = None  # SageMaker access key
+    SAGEMAKER_SECRET_KEY: Optional[str] = None  # SageMaker secret key
+
+    # prem ai project id
+    PREMAI_PROJECT_ID: Optional[str] = None
+
+    # Qdrant vectorstore config
+    QDRANT_COLLECTION_NAME: Optional[str] = "docsgpt"
+    QDRANT_LOCATION: Optional[str] = None
+    QDRANT_URL: Optional[str] = None
+    QDRANT_PORT: Optional[int] = 6333
+    QDRANT_GRPC_PORT: int = 6334
+    QDRANT_PREFER_GRPC: bool = False
+    QDRANT_HTTPS: Optional[bool] = None
+    QDRANT_API_KEY: Optional[str] = None
+    QDRANT_PREFIX: Optional[str] = None
+    QDRANT_TIMEOUT: Optional[float] = None
+    QDRANT_HOST: Optional[str] = None
+    QDRANT_PATH: Optional[str] = None
+    QDRANT_DISTANCE_FUNC: str = "Cosine"
+
+    BRAVE_SEARCH_API_KEY: Optional[str] = None
+
+    FLASK_DEBUG_MODE: bool = False
 
 
 path = Path(__file__).parent.parent.absolute()

application/llm/anthropic.py

@@ -1,21 +1,29 @@
 from application.llm.base import BaseLLM
 from application.core.settings import settings
 
+
 class AnthropicLLM(BaseLLM):
 
-    def __init__(self, api_key=None):
+    def __init__(self, api_key=None, user_api_key=None, *args, **kwargs):
         from anthropic import Anthropic, HUMAN_PROMPT, AI_PROMPT
-        self.api_key = api_key or settings.ANTHROPIC_API_KEY  # If not provided, use a default from settings
+
+        super().__init__(*args, **kwargs)
+        self.api_key = (
+            api_key or settings.ANTHROPIC_API_KEY
+        )  # If not provided, use a default from settings
+        self.user_api_key = user_api_key
         self.anthropic = Anthropic(api_key=self.api_key)
         self.HUMAN_PROMPT = HUMAN_PROMPT
         self.AI_PROMPT = AI_PROMPT
 
-    def gen(self, model, messages, engine=None, max_tokens=300, stream=False, **kwargs):
-        context = messages[0]['content']
-        user_question = messages[-1]['content']
+    def _raw_gen(
+        self, baseself, model, messages, stream=False, max_tokens=300, **kwargs
+    ):
+        context = messages[0]["content"]
+        user_question = messages[-1]["content"]
         prompt = f"### Context \n {context} \n ### Question \n {user_question}"
         if stream:
-            return self.gen_stream(model, prompt, max_tokens, **kwargs)
+            return self.gen_stream(model, prompt, stream, max_tokens, **kwargs)
 
         completion = self.anthropic.completions.create(
             model=model,
@@ -25,9 +33,11 @@ class AnthropicLLM(BaseLLM):
         )
         return completion.completion
 
-    def gen_stream(self, model, messages, engine=None, max_tokens=300, **kwargs):
-        context = messages[0]['content']
-        user_question = messages[-1]['content']
+    def _raw_gen_stream(
+        self, baseself, model, messages, stream=True, max_tokens=300, **kwargs
+    ):
+        context = messages[0]["content"]
+        user_question = messages[-1]["content"]
         prompt = f"### Context \n {context} \n ### Question \n {user_question}"
         stream_response = self.anthropic.completions.create(
             model=model,
@@ -37,4 +47,4 @@ class AnthropicLLM(BaseLLM):
         )
 
         for completion in stream_response:
-            yield completion.completion
+            yield completion.completion

application/llm/base.py

@@ -1,14 +1,28 @@
 from abc import ABC, abstractmethod
+from application.usage import gen_token_usage, stream_token_usage
 
 
 class BaseLLM(ABC):
     def __init__(self):
-        pass
+        self.token_usage = {"prompt_tokens": 0, "generated_tokens": 0}
+
+    def _apply_decorator(self, method, decorator, *args, **kwargs):
+        return decorator(method, *args, **kwargs)
 
     @abstractmethod
-    def gen(self, *args, **kwargs):
+    def _raw_gen(self, model, messages, stream, *args, **kwargs):
         pass
 
+    def gen(self, model, messages, stream=False, *args, **kwargs):
+        return self._apply_decorator(self._raw_gen, gen_token_usage)(
+            self, model=model, messages=messages, stream=stream, *args, **kwargs
+        )
+
     @abstractmethod
-    def gen_stream(self, *args, **kwargs):
+    def _raw_gen_stream(self, model, messages, stream, *args, **kwargs):
         pass
+
+    def gen_stream(self, model, messages, stream=True, *args, **kwargs):
+        return self._apply_decorator(self._raw_gen_stream, stream_token_usage)(
+            self, model=model, messages=messages, stream=stream, *args, **kwargs
+        )

application/llm/docsgpt_provider.py

@@ -2,48 +2,43 @@ from application.llm.base import BaseLLM
 import json
 import requests
 
+
 class DocsGPTAPILLM(BaseLLM):
 
-    def __init__(self, *args, **kwargs):
-        self.endpoint =  "https://llm.docsgpt.co.uk"
+    def __init__(self, api_key=None, user_api_key=None, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.api_key = api_key
+        self.user_api_key = user_api_key
+        self.endpoint = "https://llm.docsgpt.co.uk"
 
-
-    def gen(self, model, engine, messages, stream=False, **kwargs):
-        context = messages[0]['content']
-        user_question = messages[-1]['content']
+    def _raw_gen(self, baseself, model, messages, stream=False, *args, **kwargs):
+        context = messages[0]["content"]
+        user_question = messages[-1]["content"]
         prompt = f"### Instruction \n {user_question} \n ### Context \n {context} \n ### Answer \n"
 
         response = requests.post(
-            f"{self.endpoint}/answer",
-            json={
-                "prompt": prompt,
-                "max_new_tokens": 30
-            }
+            f"{self.endpoint}/answer", json={"prompt": prompt, "max_new_tokens": 30}
         )
-        response_clean = response.json()['a'].split("###")[0]
+        response_clean = response.json()["a"].replace("###", "")
 
         return response_clean
 
-    def gen_stream(self, model, engine, messages, stream=True, **kwargs):
-        context = messages[0]['content']
-        user_question = messages[-1]['content']
+    def _raw_gen_stream(self, baseself, model, messages, stream=True, *args, **kwargs):
+        context = messages[0]["content"]
+        user_question = messages[-1]["content"]
         prompt = f"### Instruction \n {user_question} \n ### Context \n {context} \n ### Answer \n"
 
         # send prompt to endpoint /stream
         response = requests.post(
             f"{self.endpoint}/stream",
-            json={
-                "prompt": prompt,
-                "max_new_tokens": 256
-            },
-            stream=True
+            json={"prompt": prompt, "max_new_tokens": 256},
+            stream=True,
         )
-    
+
         for line in response.iter_lines():
             if line:
-                #data = json.loads(line)
-                data_str = line.decode('utf-8')
+                # data = json.loads(line)
+                data_str = line.decode("utf-8")
                 if data_str.startswith("data: "):
                     data = json.loads(data_str[6:])
-                    yield data['a']
-                    
+                    yield data["a"]

application/llm/huggingface.py

@@ -1,44 +1,68 @@
 from application.llm.base import BaseLLM
 
+
 class HuggingFaceLLM(BaseLLM):
 
-    def __init__(self, api_key, llm_name='Arc53/DocsGPT-7B',q=False):
+    def __init__(
+        self,
+        api_key=None,
+        user_api_key=None,
+        llm_name="Arc53/DocsGPT-7B",
+        q=False,
+        *args,
+        **kwargs,
+    ):
         global hf
-        
+
         from langchain.llms import HuggingFacePipeline
+
         if q:
             import torch
-            from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline, BitsAndBytesConfig
+            from transformers import (
+                AutoModelForCausalLM,
+                AutoTokenizer,
+                pipeline,
+                BitsAndBytesConfig,
+            )
+
             tokenizer = AutoTokenizer.from_pretrained(llm_name)
             bnb_config = BitsAndBytesConfig(
-                            load_in_4bit=True,
-                            bnb_4bit_use_double_quant=True,
-                            bnb_4bit_quant_type="nf4",
-                            bnb_4bit_compute_dtype=torch.bfloat16
-                        )
-            model = AutoModelForCausalLM.from_pretrained(llm_name,quantization_config=bnb_config)
+                load_in_4bit=True,
+                bnb_4bit_use_double_quant=True,
+                bnb_4bit_quant_type="nf4",
+                bnb_4bit_compute_dtype=torch.bfloat16,
+            )
+            model = AutoModelForCausalLM.from_pretrained(
+                llm_name, quantization_config=bnb_config
+            )
         else:
             from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+
             tokenizer = AutoTokenizer.from_pretrained(llm_name)
             model = AutoModelForCausalLM.from_pretrained(llm_name)
-        
+
+        super().__init__(*args, **kwargs)
+        self.api_key = api_key
+        self.user_api_key = user_api_key
         pipe = pipeline(
-            "text-generation", model=model,
-            tokenizer=tokenizer, max_new_tokens=2000,
-            device_map="auto", eos_token_id=tokenizer.eos_token_id
+            "text-generation",
+            model=model,
+            tokenizer=tokenizer,
+            max_new_tokens=2000,
+            device_map="auto",
+            eos_token_id=tokenizer.eos_token_id,
         )
         hf = HuggingFacePipeline(pipeline=pipe)
 
-    def gen(self, model, engine, messages, stream=False, **kwargs):
-        context = messages[0]['content']
-        user_question = messages[-1]['content']
+    def _raw_gen(self, baseself, model, messages, stream=False, **kwargs):
+        context = messages[0]["content"]
+        user_question = messages[-1]["content"]
         prompt = f"### Instruction \n {user_question} \n ### Context \n {context} \n ### Answer \n"
 
         result = hf(prompt)
 
         return result.content
 
-    def gen_stream(self, model, engine, messages, stream=True, **kwargs):
+    def _raw_gen_stream(self, baseself, model, messages, stream=True, **kwargs):
 
         raise NotImplementedError("HuggingFaceLLM Streaming is not implemented yet.")
-

application/llm/llama_cpp.py

@@ -1,32 +1,45 @@
 from application.llm.base import BaseLLM
 from application.core.settings import settings
 
+
 class LlamaCpp(BaseLLM):
 
-    def __init__(self, api_key, llm_name=settings.MODEL_PATH, **kwargs):
+    def __init__(
+        self,
+        api_key=None,
+        user_api_key=None,
+        llm_name=settings.MODEL_PATH,
+        *args,
+        **kwargs,
+    ):
         global llama
         try:
             from llama_cpp import Llama
         except ImportError:
-            raise ImportError("Please install llama_cpp using pip install llama-cpp-python")
+            raise ImportError(
+                "Please install llama_cpp using pip install llama-cpp-python"
+            )
 
+        super().__init__(*args, **kwargs)
+        self.api_key = api_key
+        self.user_api_key = user_api_key
         llama = Llama(model_path=llm_name, n_ctx=2048)
 
-    def gen(self, model, engine, messages, stream=False, **kwargs):
-        context = messages[0]['content']
-        user_question = messages[-1]['content']
+    def _raw_gen(self, baseself, model, messages, stream=False, **kwargs):
+        context = messages[0]["content"]
+        user_question = messages[-1]["content"]
         prompt = f"### Instruction \n {user_question} \n ### Context \n {context} \n ### Answer \n"
 
         result = llama(prompt, max_tokens=150, echo=False)
 
         # import sys
         # print(result['choices'][0]['text'].split('### Answer \n')[-1], file=sys.stderr)
-        
-        return result['choices'][0]['text'].split('### Answer \n')[-1]
 
-    def gen_stream(self, model, engine, messages, stream=True, **kwargs):
-        context = messages[0]['content']
-        user_question = messages[-1]['content']
+        return result["choices"][0]["text"].split("### Answer \n")[-1]
+
+    def _raw_gen_stream(self, baseself, model, messages, stream=True, **kwargs):
+        context = messages[0]["content"]
+        user_question = messages[-1]["content"]
         prompt = f"### Instruction \n {user_question} \n ### Context \n {context} \n ### Answer \n"
 
         result = llama(prompt, max_tokens=150, echo=False, stream=stream)
@@ -35,5 +48,5 @@ class LlamaCpp(BaseLLM):
         # print(list(result), file=sys.stderr)
 
         for item in result:
-            for choice in item['choices']:
-                yield choice['text']
+            for choice in item["choices"]:
+                yield choice["text"]

application/llm/llm_creator.py

@@ -4,23 +4,24 @@ from application.llm.huggingface import HuggingFaceLLM
 from application.llm.llama_cpp import LlamaCpp
 from application.llm.anthropic import AnthropicLLM
 from application.llm.docsgpt_provider import DocsGPTAPILLM
-
+from application.llm.premai import PremAILLM
 
 
 class LLMCreator:
     llms = {
-        'openai': OpenAILLM,
-        'azure_openai': AzureOpenAILLM,
-        'sagemaker': SagemakerAPILLM,
-        'huggingface': HuggingFaceLLM,
-        'llama.cpp': LlamaCpp,
-        'anthropic': AnthropicLLM,
-        'docsgpt': DocsGPTAPILLM
+        "openai": OpenAILLM,
+        "azure_openai": AzureOpenAILLM,
+        "sagemaker": SagemakerAPILLM,
+        "huggingface": HuggingFaceLLM,
+        "llama.cpp": LlamaCpp,
+        "anthropic": AnthropicLLM,
+        "docsgpt": DocsGPTAPILLM,
+        "premai": PremAILLM,
     }
 
     @classmethod
-    def create_llm(cls, type, *args, **kwargs):
+    def create_llm(cls, type, api_key, user_api_key, *args, **kwargs):
         llm_class = cls.llms.get(type.lower())
         if not llm_class:
             raise ValueError(f"No LLM class found for type {type}")
-        return llm_class(*args, **kwargs)
+        return llm_class(api_key, user_api_key, *args, **kwargs)

application/llm/openai.py

@@ -1,36 +1,53 @@
 from application.llm.base import BaseLLM
 from application.core.settings import settings
 
+
 class OpenAILLM(BaseLLM):
 
-    def __init__(self, api_key):
+    def __init__(self, api_key=None, user_api_key=None, *args, **kwargs):
         global openai
         from openai import OpenAI
-        
+
+        super().__init__(*args, **kwargs)
         self.client = OpenAI(
-                api_key=api_key, 
-            )
+            api_key=api_key,
+        )
         self.api_key = api_key
+        self.user_api_key = user_api_key
 
     def _get_openai(self):
         # Import openai when needed
         import openai
-        
+
         return openai
 
-    def gen(self, model, engine, messages, stream=False, **kwargs):
-        response = self.client.chat.completions.create(model=model,
-            messages=messages,
-            stream=stream,
-            **kwargs)
+    def _raw_gen(
+        self,
+        baseself,
+        model,
+        messages,
+        stream=False,
+        engine=settings.AZURE_DEPLOYMENT_NAME,
+        **kwargs
+    ):
+        response = self.client.chat.completions.create(
+            model=model, messages=messages, stream=stream, **kwargs
+        )
 
         return response.choices[0].message.content
 
-    def gen_stream(self, model, engine, messages, stream=True, **kwargs):
-        response = self.client.chat.completions.create(model=model,
-            messages=messages,
-            stream=stream,
-            **kwargs)
+    def _raw_gen_stream(
+        self,
+        baseself,
+        model,
+        messages,
+        stream=True,
+        engine=settings.AZURE_DEPLOYMENT_NAME,
+        **kwargs
+    ):
+        response = self.client.chat.completions.create(
+            model=model, messages=messages, stream=stream, **kwargs
+        )
 
         for line in response:
             # import sys
@@ -41,14 +58,17 @@ class OpenAILLM(BaseLLM):
 
 class AzureOpenAILLM(OpenAILLM):
 
-    def __init__(self, openai_api_key, openai_api_base, openai_api_version, deployment_name):
+    def __init__(
+        self, openai_api_key, openai_api_base, openai_api_version, deployment_name
+    ):
         super().__init__(openai_api_key)
-        self.api_base = settings.OPENAI_API_BASE,
-        self.api_version = settings.OPENAI_API_VERSION,
-        self.deployment_name = settings.AZURE_DEPLOYMENT_NAME,
+        self.api_base = (settings.OPENAI_API_BASE,)
+        self.api_version = (settings.OPENAI_API_VERSION,)
+        self.deployment_name = (settings.AZURE_DEPLOYMENT_NAME,)
         from openai import AzureOpenAI
+
         self.client = AzureOpenAI(
-            api_key=openai_api_key,  
+            api_key=openai_api_key,
             api_version=settings.OPENAI_API_VERSION,
             api_base=settings.OPENAI_API_BASE,
             deployment_name=settings.AZURE_DEPLOYMENT_NAME,

application/llm/premai.py

@@ -0,0 +1,38 @@
+from application.llm.base import BaseLLM
+from application.core.settings import settings
+
+
+class PremAILLM(BaseLLM):
+
+    def __init__(self, api_key=None, user_api_key=None, *args, **kwargs):
+        from premai import Prem
+
+        super().__init__(*args, **kwargs)
+        self.client = Prem(api_key=api_key)
+        self.api_key = api_key
+        self.user_api_key = user_api_key
+        self.project_id = settings.PREMAI_PROJECT_ID
+
+    def _raw_gen(self, baseself, model, messages, stream=False, **kwargs):
+        response = self.client.chat.completions.create(
+            model=model,
+            project_id=self.project_id,
+            messages=messages,
+            stream=stream,
+            **kwargs
+        )
+
+        return response.choices[0].message["content"]
+
+    def _raw_gen_stream(self, baseself, model, messages, stream=True, **kwargs):
+        response = self.client.chat.completions.create(
+            model=model,
+            project_id=self.project_id,
+            messages=messages,
+            stream=stream,
+            **kwargs
+        )
+
+        for line in response:
+            if line.choices[0].delta["content"] is not None:
+                yield line.choices[0].delta["content"]

application/llm/sagemaker.py

@@ -4,11 +4,10 @@ import json
 import io
 
 
-
 class LineIterator:
     """
-    A helper class for parsing the byte stream input. 
-    
+    A helper class for parsing the byte stream input.
+
     The output of the model will be in the following format:
     ```
     b'{"outputs": [" a"]}\n'
@@ -16,21 +15,21 @@ class LineIterator:
     b'{"outputs": [" problem"]}\n'
     ...
     ```
-    
-    While usually each PayloadPart event from the event stream will contain a byte array 
+
+    While usually each PayloadPart event from the event stream will contain a byte array
     with a full json, this is not guaranteed and some of the json objects may be split across
     PayloadPart events. For example:
     ```
     {'PayloadPart': {'Bytes': b'{"outputs": '}}
     {'PayloadPart': {'Bytes': b'[" problem"]}\n'}}
     ```
-    
+
     This class accounts for this by concatenating bytes written via the 'write' function
     and then exposing a method which will return lines (ending with a '\n' character) within
-    the buffer via the 'scan_lines' function. It maintains the position of the last read 
-    position to ensure that previous bytes are not exposed again. 
+    the buffer via the 'scan_lines' function. It maintains the position of the last read
+    position to ensure that previous bytes are not exposed again.
     """
-    
+
     def __init__(self, stream):
         self.byte_iterator = iter(stream)
         self.buffer = io.BytesIO()
@@ -43,7 +42,7 @@ class LineIterator:
         while True:
             self.buffer.seek(self.read_pos)
             line = self.buffer.readline()
-            if line and line[-1] == ord('\n'):
+            if line and line[-1] == ord("\n"):
                 self.read_pos += len(line)
                 return line[:-1]
             try:
@@ -52,33 +51,35 @@ class LineIterator:
                 if self.read_pos < self.buffer.getbuffer().nbytes:
                     continue
                 raise
-            if 'PayloadPart' not in chunk:
-                print('Unknown event type:' + chunk)
+            if "PayloadPart" not in chunk:
+                print("Unknown event type:" + chunk)
                 continue
             self.buffer.seek(0, io.SEEK_END)
-            self.buffer.write(chunk['PayloadPart']['Bytes'])
+            self.buffer.write(chunk["PayloadPart"]["Bytes"])
+
 
 class SagemakerAPILLM(BaseLLM):
 
-    def __init__(self, *args, **kwargs):
+    def __init__(self, api_key=None, user_api_key=None, *args, **kwargs):
         import boto3
+
         runtime = boto3.client(
-            'runtime.sagemaker',
-            aws_access_key_id='xxx',
-            aws_secret_access_key='xxx',
-            region_name='us-west-2'
+            "runtime.sagemaker",
+            aws_access_key_id="xxx",
+            aws_secret_access_key="xxx",
+            region_name="us-west-2",
         )
 
-        
-        self.endpoint =  settings.SAGEMAKER_ENDPOINT
+        super().__init__(*args, **kwargs)
+        self.api_key = api_key
+        self.user_api_key = user_api_key
+        self.endpoint = settings.SAGEMAKER_ENDPOINT
         self.runtime = runtime
 
-
-    def gen(self, model, engine, messages, stream=False, **kwargs):
-        context = messages[0]['content']
-        user_question = messages[-1]['content']
+    def _raw_gen(self, baseself, model, messages, stream=False, **kwargs):
+        context = messages[0]["content"]
+        user_question = messages[-1]["content"]
         prompt = f"### Instruction \n {user_question} \n ### Context \n {context} \n ### Answer \n"
-    
 
         # Construct payload for endpoint
         payload = {
@@ -89,25 +90,25 @@ class SagemakerAPILLM(BaseLLM):
                 "temperature": 0.1,
                 "max_new_tokens": 30,
                 "repetition_penalty": 1.03,
-                "stop": ["</s>", "###"]
-            }
+                "stop": ["</s>", "###"],
+            },
         }
-        body_bytes = json.dumps(payload).encode('utf-8')
+        body_bytes = json.dumps(payload).encode("utf-8")
 
         # Invoke the endpoint
-        response = self.runtime.invoke_endpoint(EndpointName=self.endpoint,
-                                        ContentType='application/json',
-                                        Body=body_bytes)
-        result = json.loads(response['Body'].read().decode())
+        response = self.runtime.invoke_endpoint(
+            EndpointName=self.endpoint, ContentType="application/json", Body=body_bytes
+        )
+        result = json.loads(response["Body"].read().decode())
         import sys
-        print(result[0]['generated_text'], file=sys.stderr)
-        return result[0]['generated_text'][len(prompt):]
 
-    def gen_stream(self, model, engine, messages, stream=True, **kwargs):
-        context = messages[0]['content']
-        user_question = messages[-1]['content']
+        print(result[0]["generated_text"], file=sys.stderr)
+        return result[0]["generated_text"][len(prompt) :]
+
+    def _raw_gen_stream(self, baseself, model, messages, stream=True, **kwargs):
+        context = messages[0]["content"]
+        user_question = messages[-1]["content"]
         prompt = f"### Instruction \n {user_question} \n ### Context \n {context} \n ### Answer \n"
-    
 
         # Construct payload for endpoint
         payload = {
@@ -118,22 +119,22 @@ class SagemakerAPILLM(BaseLLM):
                 "temperature": 0.1,
                 "max_new_tokens": 512,
                 "repetition_penalty": 1.03,
-                "stop": ["</s>", "###"]
-            }
+                "stop": ["</s>", "###"],
+            },
         }
-        body_bytes = json.dumps(payload).encode('utf-8')
+        body_bytes = json.dumps(payload).encode("utf-8")
 
         # Invoke the endpoint
-        response = self.runtime.invoke_endpoint_with_response_stream(EndpointName=self.endpoint,
-                                        ContentType='application/json',
-                                        Body=body_bytes)
-        #result = json.loads(response['Body'].read().decode())
-        event_stream = response['Body']
-        start_json = b'{'
+        response = self.runtime.invoke_endpoint_with_response_stream(
+            EndpointName=self.endpoint, ContentType="application/json", Body=body_bytes
+        )
+        # result = json.loads(response['Body'].read().decode())
+        event_stream = response["Body"]
+        start_json = b"{"
         for line in LineIterator(event_stream):
-            if line != b'' and start_json in line:
-                #print(line)
-                data = json.loads(line[line.find(start_json):].decode('utf-8'))
-                if data['token']['text'] not in ["</s>", "###"]:
-                    print(data['token']['text'],end='')
-                    yield data['token']['text']
+            if line != b"" and start_json in line:
+                # print(line)
+                data = json.loads(line[line.find(start_json) :].decode("utf-8"))
+                if data["token"]["text"] not in ["</s>", "###"]:
+                    print(data["token"]["text"], end="")
+                    yield data["token"]["text"]

application/parser/file/bulk.py

@@ -147,12 +147,24 @@ class SimpleDirectoryReader(BaseReader):
                 # do standard read
                 with open(input_file, "r", errors=self.errors) as f:
                     data = f.read()
-            if isinstance(data, List):
-                data_list.extend(data)
-            else:
-                data_list.append(str(data))
+            # Prepare metadata for this file
             if self.file_metadata is not None:
-                metadata_list.append(self.file_metadata(str(input_file)))
+                file_metadata = self.file_metadata(str(input_file))
+            else:
+                # Provide a default empty metadata
+                file_metadata = {'title': '', 'store': ''}
+                # TODO: Find a case with no metadata and check if breaks anything 
+
+            if isinstance(data, List):
+                # Extend data_list with each item in the data list
+                data_list.extend([str(d) for d in data])
+                # For each item in the data list, add the file's metadata to metadata_list
+                metadata_list.extend([file_metadata for _ in data])
+            else:
+                # Add the single piece of data to data_list
+                data_list.append(str(data))
+                # Add the file's metadata to metadata_list
+                metadata_list.append(file_metadata)
 
         if concatenate:
             return [Document("\n".join(data_list))]

application/parser/remote/base.py

@@ -0,0 +1,19 @@
+"""Base reader class."""
+from abc import abstractmethod
+from typing import Any, List
+
+from langchain.docstore.document import Document as LCDocument
+from application.parser.schema.base import Document
+
+
+class BaseRemote:
+    """Utilities for loading data from a directory."""
+
+    @abstractmethod
+    def load_data(self, *args: Any, **load_kwargs: Any) -> List[Document]:
+        """Load data from the input directory."""
+
+    def load_langchain_documents(self, **load_kwargs: Any) -> List[LCDocument]:
+        """Load data in LangChain document format."""
+        docs = self.load_data(**load_kwargs)
+        return [d.to_langchain_format() for d in docs]

application/parser/remote/crawler_loader.py

@@ -0,0 +1,59 @@
+import requests
+from urllib.parse import urlparse, urljoin
+from bs4 import BeautifulSoup
+from application.parser.remote.base import BaseRemote
+
+class CrawlerLoader(BaseRemote):
+    def __init__(self, limit=10):
+        from langchain.document_loaders import WebBaseLoader
+        self.loader = WebBaseLoader  # Initialize the document loader
+        self.limit = limit  # Set the limit for the number of pages to scrape
+
+    def load_data(self, inputs):
+        url = inputs
+        # Check if the input is a list and if it is, use the first element
+        if isinstance(url, list) and url:
+            url = url[0]
+
+        # Check if the URL scheme is provided, if not, assume http
+        if not urlparse(url).scheme:
+            url = "http://" + url
+
+        visited_urls = set()  # Keep track of URLs that have been visited
+        base_url = urlparse(url).scheme + "://" + urlparse(url).hostname  # Extract the base URL
+        urls_to_visit = [url]  # List of URLs to be visited, starting with the initial URL
+        loaded_content = []  # Store the loaded content from each URL
+
+        # Continue crawling until there are no more URLs to visit
+        while urls_to_visit:
+            current_url = urls_to_visit.pop(0)  # Get the next URL to visit
+            visited_urls.add(current_url)  # Mark the URL as visited
+
+            # Try to load and process the content from the current URL
+            try:
+                response = requests.get(current_url)  # Fetch the content of the current URL
+                response.raise_for_status()  # Raise an exception for HTTP errors
+                loader = self.loader([current_url])  # Initialize the document loader for the current URL
+                loaded_content.extend(loader.load())  # Load the content and add it to the loaded_content list
+            except Exception as e:
+                # Print an error message if loading or processing fails and continue with the next URL
+                print(f"Error processing URL {current_url}: {e}")
+                continue
+
+            # Parse the HTML content to extract all links
+            soup = BeautifulSoup(response.text, 'html.parser')
+            all_links = [
+                urljoin(current_url, a['href'])
+                for a in soup.find_all('a', href=True)
+                if base_url in urljoin(current_url, a['href'])  # Ensure links are from the same domain
+            ]
+
+            # Add new links to the list of URLs to visit if they haven't been visited yet
+            urls_to_visit.extend([link for link in all_links if link not in visited_urls])
+            urls_to_visit = list(set(urls_to_visit))  # Remove duplicate URLs
+
+            # Stop crawling if the limit of pages to scrape is reached
+            if self.limit is not None and len(visited_urls) >= self.limit:
+                break
+
+        return loaded_content  # Return the loaded content from all visited URLs

application/parser/remote/reddit_loader.py

@@ -0,0 +1,26 @@
+from application.parser.remote.base import BaseRemote
+from langchain_community.document_loaders import RedditPostsLoader
+
+
+class RedditPostsLoaderRemote(BaseRemote):
+    def load_data(self, inputs):
+        data = eval(inputs)
+        client_id = data.get("client_id")
+        client_secret = data.get("client_secret")
+        user_agent = data.get("user_agent")
+        categories = data.get("categories", ["new", "hot"])
+        mode = data.get("mode", "subreddit")
+        search_queries = data.get("search_queries")
+        number_posts = data.get("number_posts", 10)
+        self.loader = RedditPostsLoader(
+            client_id=client_id,
+            client_secret=client_secret,
+            user_agent=user_agent,
+            categories=categories,
+            mode=mode,
+            search_queries=search_queries,
+            number_posts=number_posts,
+        )
+        documents = self.loader.load()
+        print(f"Loaded {len(documents)} documents from Reddit")
+        return documents

application/parser/remote/remote_creator.py

@@ -0,0 +1,20 @@
+from application.parser.remote.sitemap_loader import SitemapLoader
+from application.parser.remote.crawler_loader import CrawlerLoader
+from application.parser.remote.web_loader import WebLoader
+from application.parser.remote.reddit_loader import RedditPostsLoaderRemote
+
+
+class RemoteCreator:
+    loaders = {
+        "url": WebLoader,
+        "sitemap": SitemapLoader,
+        "crawler": CrawlerLoader,
+        "reddit": RedditPostsLoaderRemote,
+    }
+
+    @classmethod
+    def create_loader(cls, type, *args, **kwargs):
+        loader_class = cls.loaders.get(type.lower())
+        if not loader_class:
+            raise ValueError(f"No LLM class found for type {type}")
+        return loader_class(*args, **kwargs)

application/parser/remote/sitemap_loader.py

@@ -0,0 +1,81 @@
+import requests
+import re  # Import regular expression library
+import xml.etree.ElementTree as ET
+from application.parser.remote.base import BaseRemote
+
+class SitemapLoader(BaseRemote):
+    def __init__(self, limit=20):
+        from langchain.document_loaders import WebBaseLoader
+        self.loader = WebBaseLoader
+        self.limit = limit  # Adding limit to control the number of URLs to process
+
+    def load_data(self, inputs):
+        sitemap_url= inputs
+        # Check if the input is a list and if it is, use the first element
+        if isinstance(sitemap_url, list) and sitemap_url:
+            url = sitemap_url[0]
+
+        urls = self._extract_urls(sitemap_url)
+        if not urls:
+            print(f"No URLs found in the sitemap: {sitemap_url}")
+            return []
+
+        # Load content of extracted URLs
+        documents = []
+        processed_urls = 0  # Counter for processed URLs
+        for url in urls:
+            if self.limit is not None and processed_urls >= self.limit:
+                break  # Stop processing if the limit is reached
+
+            try:
+                loader = self.loader([url])
+                documents.extend(loader.load())
+                processed_urls += 1  # Increment the counter after processing each URL
+            except Exception as e:
+                print(f"Error processing URL {url}: {e}")
+                continue
+
+        return documents
+
+    def _extract_urls(self, sitemap_url):
+        try:
+            response = requests.get(sitemap_url)
+            response.raise_for_status()  # Raise an exception for HTTP errors
+        except (requests.exceptions.HTTPError, requests.exceptions.ConnectionError) as e:
+            print(f"Failed to fetch sitemap: {sitemap_url}. Error: {e}")
+            return []
+
+        # Determine if this is a sitemap or a URL
+        if self._is_sitemap(response):
+            # It's a sitemap, so parse it and extract URLs
+            return self._parse_sitemap(response.content)
+        else:
+            # It's not a sitemap, return the URL itself
+            return [sitemap_url]
+
+    def _is_sitemap(self, response):
+        content_type = response.headers.get('Content-Type', '')
+        if 'xml' in content_type or response.url.endswith('.xml'):
+            return True
+
+        if '<sitemapindex' in response.text or '<urlset' in response.text:
+            return True
+
+        return False
+
+    def _parse_sitemap(self, sitemap_content):
+        # Remove namespaces
+        sitemap_content = re.sub(' xmlns="[^"]+"', '', sitemap_content.decode('utf-8'), count=1)
+
+        root = ET.fromstring(sitemap_content)
+
+        urls = []
+        for loc in root.findall('.//url/loc'):
+            urls.append(loc.text)
+
+        # Check for nested sitemaps
+        for sitemap in root.findall('.//sitemap/loc'):
+            nested_sitemap_url = sitemap.text
+            urls.extend(self._extract_urls(nested_sitemap_url))
+
+        return urls

application/parser/remote/telegram.py

@@ -0,0 +1,11 @@
+from langchain.document_loader import TelegramChatApiLoader
+from application.parser.remote.base import BaseRemote
+
+class TelegramChatApiRemote(BaseRemote):
+    def _init_parser(self, *args, **load_kwargs):
+        self.loader = TelegramChatApiLoader(**load_kwargs)
+        return {}
+
+    def parse_file(self, *args, **load_kwargs):
+
+        return 

application/parser/remote/web_loader.py

@@ -0,0 +1,22 @@
+from application.parser.remote.base import BaseRemote
+
+class WebLoader(BaseRemote):
+    def __init__(self):
+        from langchain.document_loaders import WebBaseLoader
+        self.loader = WebBaseLoader
+
+    def load_data(self, inputs):
+        urls = inputs
+
+        if isinstance(urls, str):
+            urls = [urls] # Convert string to list if a single URL is passed
+
+        documents = []
+        for url in urls:
+            try:
+                loader = self.loader([url])  # Process URLs one by one
+                documents.extend(loader.load())
+            except Exception as e:
+                print(f"Error processing URL {url}: {e}")
+                continue  # Continue with the next URL if an error occurs
+        return documents

application/parser/token_func.py

@@ -21,16 +21,18 @@ def group_documents(documents: List[Document], min_tokens: int, max_tokens: int)
     for doc in documents:
         doc_len = len(tiktoken.get_encoding("cl100k_base").encode(doc.text))
 
-        if current_group is None:
-            current_group = Document(text=doc.text, doc_id=doc.doc_id, embedding=doc.embedding,
-                                     extra_info=doc.extra_info)
-        elif len(tiktoken.get_encoding("cl100k_base").encode(
-                current_group.text)) + doc_len < max_tokens and doc_len < min_tokens:
-            current_group.text += " " + doc.text
+        # Check if current group is empty or if the document can be added based on token count and matching metadata
+        if (current_group is None or 
+            (len(tiktoken.get_encoding("cl100k_base").encode(current_group.text)) + doc_len < max_tokens and 
+             doc_len < min_tokens and 
+             current_group.extra_info == doc.extra_info)):
+            if current_group is None:
+                current_group = doc  # Use the document directly to retain its metadata
+            else:
+                current_group.text += " " + doc.text  # Append text to the current group
         else:
             docs.append(current_group)
-            current_group = Document(text=doc.text, doc_id=doc.doc_id, embedding=doc.embedding,
-                                     extra_info=doc.extra_info)
+            current_group = doc  # Start a new group with the current document
 
     if current_group is not None:
         docs.append(current_group)

application/requirements.txt

@@ -3,6 +3,7 @@ boto3==1.34.6
 celery==5.3.6
 dataclasses_json==0.6.3
 docx2txt==0.8
+duckduckgo-search==5.3.0
 EbookLib==0.18
 elasticsearch==8.12.0
 escodegen==1.0.11
@@ -18,9 +19,10 @@ nltk==3.8.1
 openapi3_parser==1.1.16
 pandas==2.2.0
 pydantic_settings==2.1.0
-pymongo==4.6.1
+pymongo==4.6.3
 PyPDF2==3.0.1
 python-dotenv==1.0.1
+qdrant-client==1.8.2
 redis==5.0.1
 Requests==2.31.0
 retry==0.9.2

application/retriever/base.py

@@ -0,0 +1,14 @@
+from abc import ABC, abstractmethod
+
+
+class BaseRetriever(ABC):
+    def __init__(self):
+        pass
+
+    @abstractmethod
+    def gen(self, *args, **kwargs):
+        pass
+
+    @abstractmethod
+    def search(self, *args, **kwargs):
+        pass

application/retriever/brave_search.py

@@ -0,0 +1,95 @@
+import json
+from application.retriever.base import BaseRetriever
+from application.core.settings import settings
+from application.llm.llm_creator import LLMCreator
+from application.utils import count_tokens
+from langchain_community.tools import BraveSearch
+
+
+class BraveRetSearch(BaseRetriever):
+
+    def __init__(
+        self,
+        question,
+        source,
+        chat_history,
+        prompt,
+        chunks=2,
+        gpt_model="docsgpt",
+        user_api_key=None,
+    ):
+        self.question = question
+        self.source = source
+        self.chat_history = chat_history
+        self.prompt = prompt
+        self.chunks = chunks
+        self.gpt_model = gpt_model
+        self.user_api_key = user_api_key
+
+    def _get_data(self):
+        if self.chunks == 0:
+            docs = []
+        else:
+            search = BraveSearch.from_api_key(
+                api_key=settings.BRAVE_SEARCH_API_KEY,
+                search_kwargs={"count": int(self.chunks)},
+            )
+            results = search.run(self.question)
+            results = json.loads(results)
+
+            docs = []
+            for i in results:
+                try:
+                    title = i["title"]
+                    link = i["link"]
+                    snippet = i["snippet"]
+                    docs.append({"text": snippet, "title": title, "link": link})
+                except IndexError:
+                    pass
+        if settings.LLM_NAME == "llama.cpp":
+            docs = [docs[0]]
+
+        return docs
+
+    def gen(self):
+        docs = self._get_data()
+
+        # join all page_content together with a newline
+        docs_together = "\n".join([doc["text"] for doc in docs])
+        p_chat_combine = self.prompt.replace("{summaries}", docs_together)
+        messages_combine = [{"role": "system", "content": p_chat_combine}]
+        for doc in docs:
+            yield {"source": doc}
+
+        if len(self.chat_history) > 1:
+            tokens_current_history = 0
+            # count tokens in history
+            self.chat_history.reverse()
+            for i in self.chat_history:
+                if "prompt" in i and "response" in i:
+                    tokens_batch = count_tokens(i["prompt"]) + count_tokens(
+                        i["response"]
+                    )
+                    if (
+                        tokens_current_history + tokens_batch
+                        < settings.TOKENS_MAX_HISTORY
+                    ):
+                        tokens_current_history += tokens_batch
+                        messages_combine.append(
+                            {"role": "user", "content": i["prompt"]}
+                        )
+                        messages_combine.append(
+                            {"role": "system", "content": i["response"]}
+                        )
+        messages_combine.append({"role": "user", "content": self.question})
+
+        llm = LLMCreator.create_llm(
+            settings.LLM_NAME, api_key=settings.API_KEY, user_api_key=self.user_api_key
+        )
+
+        completion = llm.gen_stream(model=self.gpt_model, messages=messages_combine)
+        for line in completion:
+            yield {"answer": str(line)}
+
+    def search(self):
+        return self._get_data()

application/retriever/classic_rag.py

@@ -0,0 +1,110 @@
+import os
+from application.retriever.base import BaseRetriever
+from application.core.settings import settings
+from application.vectorstore.vector_creator import VectorCreator
+from application.llm.llm_creator import LLMCreator
+
+from application.utils import count_tokens
+
+
+class ClassicRAG(BaseRetriever):
+
+    def __init__(
+        self,
+        question,
+        source,
+        chat_history,
+        prompt,
+        chunks=2,
+        gpt_model="docsgpt",
+        user_api_key=None,
+    ):
+        self.question = question
+        self.vectorstore = self._get_vectorstore(source=source)
+        self.chat_history = chat_history
+        self.prompt = prompt
+        self.chunks = chunks
+        self.gpt_model = gpt_model
+        self.user_api_key = user_api_key
+
+    def _get_vectorstore(self, source):
+        if "active_docs" in source:
+            if source["active_docs"].split("/")[0] == "default":
+                vectorstore = ""
+            elif source["active_docs"].split("/")[0] == "local":
+                vectorstore = "indexes/" + source["active_docs"]
+            else:
+                vectorstore = "vectors/" + source["active_docs"]
+            if source["active_docs"] == "default":
+                vectorstore = ""
+        else:
+            vectorstore = ""
+        vectorstore = os.path.join("application", vectorstore)
+        return vectorstore
+
+    def _get_data(self):
+        if self.chunks == 0:
+            docs = []
+        else:
+            docsearch = VectorCreator.create_vectorstore(
+                settings.VECTOR_STORE, self.vectorstore, settings.EMBEDDINGS_KEY
+            )
+            docs_temp = docsearch.search(self.question, k=self.chunks)
+            docs = [
+                {
+                    "title": (
+                        i.metadata["title"].split("/")[-1]
+                        if i.metadata
+                        else i.page_content
+                    ),
+                    "text": i.page_content,
+                }
+                for i in docs_temp
+            ]
+        if settings.LLM_NAME == "llama.cpp":
+            docs = [docs[0]]
+
+        return docs
+
+    def gen(self):
+        docs = self._get_data()
+
+        # join all page_content together with a newline
+        docs_together = "\n".join([doc["text"] for doc in docs])
+        p_chat_combine = self.prompt.replace("{summaries}", docs_together)
+        messages_combine = [{"role": "system", "content": p_chat_combine}]
+        for doc in docs:
+            yield {"source": doc}
+
+        if len(self.chat_history) > 1:
+            tokens_current_history = 0
+            # count tokens in history
+            self.chat_history.reverse()
+            for i in self.chat_history:
+                if "prompt" in i and "response" in i:
+                    tokens_batch = count_tokens(i["prompt"]) + count_tokens(
+                        i["response"]
+                    )
+                    if (
+                        tokens_current_history + tokens_batch
+                        < settings.TOKENS_MAX_HISTORY
+                    ):
+                        tokens_current_history += tokens_batch
+                        messages_combine.append(
+                            {"role": "user", "content": i["prompt"]}
+                        )
+                        messages_combine.append(
+                            {"role": "system", "content": i["response"]}
+                        )
+        messages_combine.append({"role": "user", "content": self.question})
+
+        llm = LLMCreator.create_llm(
+            settings.LLM_NAME, api_key=settings.API_KEY, user_api_key=self.user_api_key
+        )
+
+        completion = llm.gen_stream(model=self.gpt_model, messages=messages_combine)
+        for line in completion:
+            yield {"answer": str(line)}
+
+    def search(self):
+        return self._get_data()

application/retriever/duckduck_search.py

@@ -0,0 +1,112 @@
+from application.retriever.base import BaseRetriever
+from application.core.settings import settings
+from application.llm.llm_creator import LLMCreator
+from application.utils import count_tokens
+from langchain_community.tools import DuckDuckGoSearchResults
+from langchain_community.utilities import DuckDuckGoSearchAPIWrapper
+
+
+class DuckDuckSearch(BaseRetriever):
+
+    def __init__(
+        self,
+        question,
+        source,
+        chat_history,
+        prompt,
+        chunks=2,
+        gpt_model="docsgpt",
+        user_api_key=None,
+    ):
+        self.question = question
+        self.source = source
+        self.chat_history = chat_history
+        self.prompt = prompt
+        self.chunks = chunks
+        self.gpt_model = gpt_model
+        self.user_api_key = user_api_key
+
+    def _parse_lang_string(self, input_string):
+        result = []
+        current_item = ""
+        inside_brackets = False
+        for char in input_string:
+            if char == "[":
+                inside_brackets = True
+            elif char == "]":
+                inside_brackets = False
+                result.append(current_item)
+                current_item = ""
+            elif inside_brackets:
+                current_item += char
+
+        if inside_brackets:
+            result.append(current_item)
+
+        return result
+
+    def _get_data(self):
+        if self.chunks == 0:
+            docs = []
+        else:
+            wrapper = DuckDuckGoSearchAPIWrapper(max_results=self.chunks)
+            search = DuckDuckGoSearchResults(api_wrapper=wrapper)
+            results = search.run(self.question)
+            results = self._parse_lang_string(results)
+
+            docs = []
+            for i in results:
+                try:
+                    text = i.split("title:")[0]
+                    title = i.split("title:")[1].split("link:")[0]
+                    link = i.split("link:")[1]
+                    docs.append({"text": text, "title": title, "link": link})
+                except IndexError:
+                    pass
+        if settings.LLM_NAME == "llama.cpp":
+            docs = [docs[0]]
+
+        return docs
+
+    def gen(self):
+        docs = self._get_data()
+
+        # join all page_content together with a newline
+        docs_together = "\n".join([doc["text"] for doc in docs])
+        p_chat_combine = self.prompt.replace("{summaries}", docs_together)
+        messages_combine = [{"role": "system", "content": p_chat_combine}]
+        for doc in docs:
+            yield {"source": doc}
+
+        if len(self.chat_history) > 1:
+            tokens_current_history = 0
+            # count tokens in history
+            self.chat_history.reverse()
+            for i in self.chat_history:
+                if "prompt" in i and "response" in i:
+                    tokens_batch = count_tokens(i["prompt"]) + count_tokens(
+                        i["response"]
+                    )
+                    if (
+                        tokens_current_history + tokens_batch
+                        < settings.TOKENS_MAX_HISTORY
+                    ):
+                        tokens_current_history += tokens_batch
+                        messages_combine.append(
+                            {"role": "user", "content": i["prompt"]}
+                        )
+                        messages_combine.append(
+                            {"role": "system", "content": i["response"]}
+                        )
+        messages_combine.append({"role": "user", "content": self.question})
+
+        llm = LLMCreator.create_llm(
+            settings.LLM_NAME, api_key=settings.API_KEY, user_api_key=self.user_api_key
+        )
+
+        completion = llm.gen_stream(model=self.gpt_model, messages=messages_combine)
+        for line in completion:
+            yield {"answer": str(line)}
+
+    def search(self):
+        return self._get_data()

application/retriever/retriever_creator.py

@@ -0,0 +1,19 @@
+from application.retriever.classic_rag import ClassicRAG
+from application.retriever.duckduck_search import DuckDuckSearch
+from application.retriever.brave_search import BraveRetSearch
+
+
+
+class RetrieverCreator:
+    retievers = {
+        'classic': ClassicRAG,
+        'duckduck_search': DuckDuckSearch,
+        'brave_search': BraveRetSearch
+    }
+
+    @classmethod
+    def create_retriever(cls, type, *args, **kwargs):
+        retiever_class = cls.retievers.get(type.lower())
+        if not retiever_class:
+            raise ValueError(f"No retievers class found for type {type}")
+        return retiever_class(*args, **kwargs)

application/usage.py

@@ -0,0 +1,49 @@
+import sys
+from pymongo import MongoClient
+from datetime import datetime
+from application.core.settings import settings
+from application.utils import count_tokens
+
+mongo = MongoClient(settings.MONGO_URI)
+db = mongo["docsgpt"]
+usage_collection = db["token_usage"]
+
+
+def update_token_usage(user_api_key, token_usage):
+    if "pytest" in sys.modules:
+        return
+    usage_data = {
+        "api_key": user_api_key,
+        "prompt_tokens": token_usage["prompt_tokens"],
+        "generated_tokens": token_usage["generated_tokens"],
+        "timestamp": datetime.now(),
+    }
+    usage_collection.insert_one(usage_data)
+
+
+def gen_token_usage(func):
+    def wrapper(self, model, messages, stream, **kwargs):
+        for message in messages:
+            self.token_usage["prompt_tokens"] += count_tokens(message["content"])
+        result = func(self, model, messages, stream, **kwargs)
+        self.token_usage["generated_tokens"] += count_tokens(result)
+        update_token_usage(self.user_api_key, self.token_usage)
+        return result
+
+    return wrapper
+
+
+def stream_token_usage(func):
+    def wrapper(self, model, messages, stream, **kwargs):
+        for message in messages:
+            self.token_usage["prompt_tokens"] += count_tokens(message["content"])
+        batch = []
+        result = func(self, model, messages, stream, **kwargs)
+        for r in result:
+            batch.append(r)
+            yield r
+        for line in batch:
+            self.token_usage["generated_tokens"] += count_tokens(line)
+        update_token_usage(self.user_api_key, self.token_usage)
+
+    return wrapper

application/utils.py

@@ -0,0 +1,6 @@
+from transformers import GPT2TokenizerFast
+
+
+def count_tokens(string):
+    tokenizer = GPT2TokenizerFast.from_pretrained('gpt2')
+    return len(tokenizer(string)['input_ids'])

application/vectorstore/qdrant.py

@@ -0,0 +1,47 @@
+from langchain_community.vectorstores.qdrant import Qdrant
+from application.vectorstore.base import BaseVectorStore
+from application.core.settings import settings
+from qdrant_client import models
+
+
+class QdrantStore(BaseVectorStore):
+    def __init__(self, path: str = "", embeddings_key: str = "embeddings"):
+        self._filter = models.Filter(
+            must=[
+                models.FieldCondition(
+                    key="metadata.store",
+                    match=models.MatchValue(value=path.replace("application/indexes/", "").rstrip("/")),
+                )
+            ]
+        )
+
+        self._docsearch = Qdrant.construct_instance(
+            ["TEXT_TO_OBTAIN_EMBEDDINGS_DIMENSION"],
+            embedding=self._get_embeddings(settings.EMBEDDINGS_NAME, embeddings_key),
+            collection_name=settings.QDRANT_COLLECTION_NAME,
+            location=settings.QDRANT_LOCATION,
+            url=settings.QDRANT_URL,
+            port=settings.QDRANT_PORT,
+            grpc_port=settings.QDRANT_GRPC_PORT,
+            https=settings.QDRANT_HTTPS,
+            prefer_grpc=settings.QDRANT_PREFER_GRPC,
+            api_key=settings.QDRANT_API_KEY,
+            prefix=settings.QDRANT_PREFIX,
+            timeout=settings.QDRANT_TIMEOUT,
+            path=settings.QDRANT_PATH,
+            distance_func=settings.QDRANT_DISTANCE_FUNC,
+        )
+
+    def search(self, *args, **kwargs):
+        return self._docsearch.similarity_search(filter=self._filter, *args, **kwargs)
+
+    def add_texts(self, *args, **kwargs):
+        return self._docsearch.add_texts(*args, **kwargs)
+
+    def save_local(self, *args, **kwargs):
+        pass
+
+    def delete_index(self, *args, **kwargs):
+        return self._docsearch.client.delete(
+            collection_name=settings.QDRANT_COLLECTION_NAME, points_selector=self._filter
+        )

application/vectorstore/vector_creator.py

@@ -1,13 +1,15 @@
 from application.vectorstore.faiss import FaissStore
 from application.vectorstore.elasticsearch import ElasticsearchStore
 from application.vectorstore.mongodb import MongoDBVectorStore
+from application.vectorstore.qdrant import QdrantStore
 
 
 class VectorCreator:
     vectorstores = {
-        'faiss': FaissStore,
-        'elasticsearch':ElasticsearchStore,
-        'mongodb': MongoDBVectorStore,
+        "faiss": FaissStore,
+        "elasticsearch": ElasticsearchStore,
+        "mongodb": MongoDBVectorStore,
+        "qdrant": QdrantStore,
     }
 
     @classmethod
@@ -15,4 +17,4 @@ class VectorCreator:
         vectorstore_class = cls.vectorstores.get(type.lower())
         if not vectorstore_class:
             raise ValueError(f"No vectorstore class found for type {type}")
-        return vectorstore_class(*args, **kwargs)
+        return vectorstore_class(*args, **kwargs)

application/worker.py

@@ -9,28 +9,59 @@ import requests
 
 from application.core.settings import settings
 from application.parser.file.bulk import SimpleDirectoryReader
+from application.parser.remote.remote_creator import RemoteCreator
 from application.parser.open_ai_func import call_openai_api
 from application.parser.schema.base import Document
 from application.parser.token_func import group_split
 
 try:
-    nltk.download('punkt', quiet=True)
-    nltk.download('averaged_perceptron_tagger', quiet=True)
+    nltk.download("punkt", quiet=True)
+    nltk.download("averaged_perceptron_tagger", quiet=True)
 except FileExistsError:
     pass
 
 
 # Define a function to extract metadata from a given filename.
 def metadata_from_filename(title):
-    store = '/'.join(title.split('/')[1:3])
-    return {'title': title, 'store': store}
+    store = "/".join(title.split("/")[1:3])
+    return {"title": title, "store": store}
 
 
 # Define a function to generate a random string of a given length.
 def generate_random_string(length):
-    return ''.join([string.ascii_letters[i % 52] for i in range(length)])
+    return "".join([string.ascii_letters[i % 52] for i in range(length)])
+
+
+current_dir = os.path.dirname(
+    os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+)
+
+def extract_zip_recursive(zip_path, extract_to, current_depth=0, max_depth=5):
+    """
+    Recursively extract zip files with a limit on recursion depth.
+
+    Args:
+        zip_path (str): Path to the zip file to be extracted.
+        extract_to (str): Destination path for extracted files.
+        current_depth (int): Current depth of recursion.
+        max_depth (int): Maximum allowed depth of recursion to prevent infinite loops.
+    """
+    if current_depth > max_depth:
+        print(f"Reached maximum recursion depth of {max_depth}")
+        return
+
+    with zipfile.ZipFile(zip_path, 'r') as zip_ref:
+        zip_ref.extractall(extract_to)
+    os.remove(zip_path)  # Remove the zip file after extracting
+
+    # Check for nested zip files and extract them
+    for root, dirs, files in os.walk(extract_to):
+        for file in files:
+            if file.endswith(".zip"):
+                # If a nested zip file is found, extract it recursively
+                file_path = os.path.join(root, file)
+                extract_zip_recursive(file_path, root, current_depth + 1, max_depth)
 
-current_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
 # Define the main function for ingesting and processing documents.
 def ingest_worker(self, directory, formats, name_job, filename, user):
@@ -61,38 +92,52 @@ def ingest_worker(self, directory, formats, name_job, filename, user):
     token_check = True
     min_tokens = 150
     max_tokens = 1250
-    full_path = directory + '/' + user + '/' + name_job
+    recursion_depth = 2
+    full_path = os.path.join(directory, user, name_job)
     import sys
+
+
     print(full_path, file=sys.stderr)
     # check if API_URL env variable is set
-    file_data = {'name': name_job, 'file': filename, 'user': user}
-    response = requests.get(urljoin(settings.API_URL, "/api/download"), params=file_data)
+    file_data = {"name": name_job, "file": filename, "user": user}
+    response = requests.get(
+        urljoin(settings.API_URL, "/api/download"), params=file_data
+    )
     # check if file is in the response
     print(response, file=sys.stderr)
     file = response.content
 
     if not os.path.exists(full_path):
         os.makedirs(full_path)
-    with open(full_path + '/' + filename, 'wb') as f:
+    with open(os.path.join(full_path, filename), "wb") as f:
         f.write(file)
 
     # check if file is .zip and extract it
-    if filename.endswith('.zip'):
-        with zipfile.ZipFile(full_path + '/' + filename, 'r') as zip_ref:
-            zip_ref.extractall(full_path)
-        os.remove(full_path + '/' + filename)
+    if filename.endswith(".zip"):
+        extract_zip_recursive(os.path.join(full_path, filename), full_path, 0, recursion_depth)
 
-    self.update_state(state='PROGRESS', meta={'current': 1})
+    self.update_state(state="PROGRESS", meta={"current": 1})
 
-    raw_docs = SimpleDirectoryReader(input_dir=full_path, input_files=input_files, recursive=recursive,
-                                     required_exts=formats, num_files_limit=limit,
-                                     exclude_hidden=exclude, file_metadata=metadata_from_filename).load_data()
-    raw_docs = group_split(documents=raw_docs, min_tokens=min_tokens, max_tokens=max_tokens, token_check=token_check)
+    raw_docs = SimpleDirectoryReader(
+        input_dir=full_path,
+        input_files=input_files,
+        recursive=recursive,
+        required_exts=formats,
+        num_files_limit=limit,
+        exclude_hidden=exclude,
+        file_metadata=metadata_from_filename,
+    ).load_data()
+    raw_docs = group_split(
+        documents=raw_docs,
+        min_tokens=min_tokens,
+        max_tokens=max_tokens,
+        token_check=token_check,
+    )
 
     docs = [Document.to_langchain_format(raw_doc) for raw_doc in raw_docs]
 
     call_openai_api(docs, full_path, self)
-    self.update_state(state='PROGRESS', meta={'current': 100})
+    self.update_state(state="PROGRESS", meta={"current": 100})
 
     if sample:
         for i in range(min(5, len(raw_docs))):
@@ -100,24 +145,80 @@ def ingest_worker(self, directory, formats, name_job, filename, user):
 
     # get files from outputs/inputs/index.faiss and outputs/inputs/index.pkl
     # and send them to the server (provide user and name in form)
-    file_data = {'name': name_job, 'user': user}
+    file_data = {"name": name_job, "user": user}
     if settings.VECTOR_STORE == "faiss":
-        files = {'file_faiss': open(full_path + '/index.faiss', 'rb'),
-                'file_pkl': open(full_path + '/index.pkl', 'rb')}
-        response = requests.post(urljoin(settings.API_URL, "/api/upload_index"), files=files, data=file_data)
-        response = requests.get(urljoin(settings.API_URL, "/api/delete_old?path=" + full_path))
+        files = {
+            "file_faiss": open(full_path + "/index.faiss", "rb"),
+            "file_pkl": open(full_path + "/index.pkl", "rb"),
+        }
+        response = requests.post(
+            urljoin(settings.API_URL, "/api/upload_index"), files=files, data=file_data
+        )
+        response = requests.get(
+            urljoin(settings.API_URL, "/api/delete_old?path=" + full_path)
+        )
     else:
-        response = requests.post(urljoin(settings.API_URL, "/api/upload_index"), data=file_data)
+        response = requests.post(
+            urljoin(settings.API_URL, "/api/upload_index"), data=file_data
+        )
 
-    
     # delete local
     shutil.rmtree(full_path)
 
     return {
-        'directory': directory,
-        'formats': formats,
-        'name_job': name_job,
-        'filename': filename,
-        'user': user,
-        'limited': False
+        "directory": directory,
+        "formats": formats,
+        "name_job": name_job,
+        "filename": filename,
+        "user": user,
+        "limited": False,
     }
+
+
+def remote_worker(self, source_data, name_job, user, loader, directory="temp"):
+    # sample = False
+    token_check = True
+    min_tokens = 150
+    max_tokens = 1250
+    full_path = directory + "/" + user + "/" + name_job
+
+    if not os.path.exists(full_path):
+        os.makedirs(full_path)
+
+    self.update_state(state="PROGRESS", meta={"current": 1})
+
+    # source_data {"data": [url]} for url type task just urls
+
+    # Use RemoteCreator to load data from URL
+    remote_loader = RemoteCreator.create_loader(loader)
+    raw_docs = remote_loader.load_data(source_data)
+
+    docs = group_split(
+        documents=raw_docs,
+        min_tokens=min_tokens,
+        max_tokens=max_tokens,
+        token_check=token_check,
+    )
+
+    # docs = [Document.to_langchain_format(raw_doc) for raw_doc in raw_docs]
+
+    call_openai_api(docs, full_path, self)
+    self.update_state(state="PROGRESS", meta={"current": 100})
+
+    # Proceed with uploading and cleaning as in the original function
+    file_data = {"name": name_job, "user": user}
+    if settings.VECTOR_STORE == "faiss":
+        files = {
+            "file_faiss": open(full_path + "/index.faiss", "rb"),
+            "file_pkl": open(full_path + "/index.pkl", "rb"),
+        }
+        requests.post(
+            urljoin(settings.API_URL, "/api/upload_index"), files=files, data=file_data
+        )
+        requests.get(urljoin(settings.API_URL, "/api/delete_old?path=" + full_path))
+    else:
+        requests.post(urljoin(settings.API_URL, "/api/upload_index"), data=file_data)
+
+    shutil.rmtree(full_path)
+
+    return {"urls": source_data, "name_job": name_job, "user": user, "limited": False}

application/wsgi.py

@@ -1,4 +1,5 @@
 from application.app import app
+from application.core.settings import settings
 
 if __name__ == "__main__":
-    app.run(debug=True, port=7091)
+    app.run(debug=settings.FLASK_DEBUG_MODE, port=7091)

docs/next.config.js

@@ -1,9 +1,9 @@
 const withNextra = require('nextra')({
-    theme: 'nextra-theme-docs',
-    themeConfig: './theme.config.jsx'
-  })
+  theme: 'nextra-theme-docs',
+  themeConfig: './theme.config.jsx'
+})
+
+module.exports = withNextra()
    
-  module.exports = withNextra()
-   
-  // If you have other Next.js configurations, you can pass them as the parameter:
-  // module.exports = withNextra({ /* other next.js config */ })
+// If you have other Next.js configurations, you can pass them as the parameter:
+// module.exports = withNextra({ /* other next.js config */ })

docs/package.json

@@ -1,17 +1,17 @@
 {
-"scripts":{
-      "dev": "next dev",
+  "scripts": {
+    "dev": "next dev",
     "build": "next build",
     "start": "next start"
   },
-    "license": "MIT",
+  "license": "MIT",
   "dependencies": {
-    "@vercel/analytics": "^1.0.2",
-    "docsgpt": "^0.2.4",
-    "next": "^13.5.1",
-    "nextra": "^2.12.3",
-    "nextra-theme-docs": "^2.12.3",
+    "@vercel/analytics": "^1.1.1",
+    "docsgpt": "^0.3.7",
+    "next": "^14.0.4",
+    "nextra": "^2.13.2",
+    "nextra-theme-docs": "^2.13.2",
     "react": "^18.2.0",
     "react-dom": "^18.2.0"
   }
-}
+}

docs/pages/Developing/API-docs.md

@@ -227,3 +227,124 @@ JSON response indicating the status of the operation:
 ```json
 { "status": "ok" }
 ```
+
+### 7. /api/get_api_keys
+**Description:**
+
+The endpoint retrieves a list of API keys for the user.
+
+**Request:**
+
+**Method**: `GET`
+
+**Sample JavaScript Fetch Request:**
+```js
+// get_api_keys (GET http://127.0.0.1:5000/api/get_api_keys)
+fetch("http://localhost:5001/api/get_api_keys", {
+      "method": "GET",
+      "headers": {
+            "Content-Type": "application/json; charset=utf-8"
+      },
+})
+.then((res) => res.text())
+.then(console.log.bind(console))
+
+```
+**Response:**
+
+JSON response with a list of created API keys:
+
+```json
+[
+      {
+        "id": "string",
+        "name": "string",
+        "key": "string",
+        "source": "string"
+      },
+      ...
+    ]
+```
+
+### 8. /api/create_api_key
+
+**Description:**
+
+Create a new API key for the user.
+
+**Request:**
+
+**Method**: `POST`
+
+**Headers**: Content-Type should be set to `application/json; charset=utf-8`
+
+**Request Body**: JSON object with the following fields:
+* `name` — A name for the API key.
+* `source` — The source documents that will be used.
+* `prompt_id` — The prompt ID.
+* `chunks` — The number of chunks used to process an answer.
+
+Here is a JavaScript Fetch Request example:
+```js
+// create_api_key (POST http://127.0.0.1:5000/api/create_api_key)
+fetch("http://127.0.0.1:5000/api/create_api_key", {
+      "method": "POST",
+      "headers": {
+            "Content-Type": "application/json; charset=utf-8"
+      },
+      "body": JSON.stringify({"name":"Example Key Name",
+          "source":"Example Source",
+          "prompt_id":"creative",
+          "chunks":"2"})
+})
+.then((res) => res.json())
+.then(console.log.bind(console))
+```
+
+**Response**
+
+In response, you will get a JSON document containing the `id` and `key`:
+```json
+{
+  "id": "string",
+  "key": "string"
+}
+```
+
+### 9. /api/delete_api_key
+
+**Description:**
+
+Delete an API key for the user.
+
+**Request:**
+
+**Method**: `POST`
+
+**Headers**: Content-Type should be set to `application/json; charset=utf-8`
+
+**Request Body**: JSON object with the field:
+* `id` — The unique identifier of the API key to be deleted.
+
+Here is a JavaScript Fetch Request example:
+```js
+// delete_api_key (POST http://127.0.0.1:5000/api/delete_api_key)
+fetch("http://127.0.0.1:5000/api/delete_api_key", {
+      "method": "POST",
+      "headers": {
+            "Content-Type": "application/json; charset=utf-8"
+      },
+      "body": JSON.stringify({"id":"API_KEY_ID"})
+})
+.then((res) => res.json())
+.then(console.log.bind(console))
+```
+
+**Response:**
+
+In response, you will get a JSON document indicating the status of the operation:
+```json
+{
+  "status": "ok"
+}
+```

docs/pages/Extensions/_meta.json

@@ -4,7 +4,11 @@
     "href": "/Extensions/Chatwoot-extension"
   },
   "react-widget": {
-      "title": "🏗️ Widget setup",
-      "href": "/Extensions/react-widget"
-    }
+    "title": "🏗️ Widget setup",
+    "href": "/Extensions/react-widget"
+  },
+  "api-key-guide": {
+    "title": "🔐 API Keys guide",
+    "href": "/Extensions/api-key-guide"
+  }
 }

docs/pages/Extensions/api-key-guide.md

@@ -0,0 +1,30 @@
+## Guide to DocsGPT API Keys
+
+DocsGPT API keys are essential for developers and users who wish to integrate the  DocsGPT models into external applications, such as the our widget. This guide will walk you through the steps of obtaining an API key, starting from uploading your document to understanding the key variables associated with API keys.
+
+### Uploading Your Document
+
+Before creating your first API key, you must upload the document that will be linked to this key. You can upload your document through two methods:
+
+- **GUI Web App Upload:** A user-friendly graphical interface that allows for easy upload and management of documents.
+- **Using `/api/upload` Method:** For users comfortable with API calls, this method provides a direct way to upload documents.
+
+### Obtaining Your API Key
+
+After uploading your document, you can obtain an API key either through the graphical user interface or via an API call:
+
+- **Graphical User Interface:** Navigate to the Settings section of the DocsGPT web app, find the API Keys option, and press 'Create New' to generate your key.
+- **API Call:** Alternatively, you can use the `/api/create_api_key` endpoint to create a new API key. For detailed instructions, visit [DocsGPT API Documentation](https://docs.docsgpt.co.uk/Developing/API-docs#8-apicreate_api_key).
+
+### Understanding Key Variables
+
+Upon creating your API key, you will encounter several key variables. Each serves a specific purpose:
+
+- **Name:** Assign a name to your API key for easy identification.
+- **Source:** Indicates the source document(s) linked to your API key, which DocsGPT will use to generate responses.
+- **ID:** A unique identifier for your API key. You can view this by making a call to `/api/get_api_keys`.
+- **Key:** The API key itself, which will be used in your application to authenticate API requests.
+
+With your API key ready, you can now integrate DocsGPT into your application, such as the DocsGPT Widget or any other software, via `/api/answer` or `/stream` endpoints. The source document is preset with the API key, allowing you to bypass fields like `selectDocs` and `active_docs` during implementation.
+
+Congratulations on taking the first step towards enhancing your applications with DocsGPT! With this guide, you're now equipped to navigate the process of obtaining and understanding DocsGPT API keys.

docs/pages/Extensions/react-widget.md

@@ -10,7 +10,6 @@ First, make sure you have Node.js and npm installed in your project. Then go to
 In the file where you want to use the widget, import it and include the CSS file:
 ```js
 import { DocsGPTWidget } from "docsgpt";
-import "docsgpt/dist/style.css";
 ```
 
 
@@ -20,18 +19,28 @@ Now, you can use the widget in your component like this :
   apiHost="https://your-docsgpt-api.com"
   selectDocs="local/docs.zip"
   apiKey=""
+  avatar = "https://d3dg1063dc54p9.cloudfront.net/cute-docsgpt.png",
+  title = "Get AI assistance",
+  description = "DocsGPT's AI Chatbot is here to help",
+  heroTitle = "Welcome to DocsGPT !",
+  heroDescription="This chatbot is built with DocsGPT and utilises GenAI, 
+  please review important information using sources."
 />
 ```
-DocsGPTWidget takes 3 **props**:
+DocsGPTWidget takes 8 **props** with default fallback values:
 1. `apiHost` — The URL of your DocsGPT API.
 2. `selectDocs` — The documentation source that you want to use for your widget (e.g. `default` or `local/docs1.zip`).
 3. `apiKey` — Usually, it's empty.
+4. `avatar`: Specifies the URL of the avatar or image representing the chatbot.
+5. `title`: Sets the title text displayed in the chatbot interface.
+6. `description`: Provides a brief description of the chatbot's purpose or functionality.
+7. `heroTitle`: Displays a welcome title when users interact with the chatbot.
+8. `heroDescription`: Provide additional introductory text or information about the chatbot's capabilities.
 
 ### How to use DocsGPTWidget with [Nextra](https://nextra.site/) (Next.js + MDX)
 Install your widget as described above and then go to your `pages/` folder and create a new file `_app.js` with the following content:
 ```js
 import { DocsGPTWidget } from "docsgpt";
-import "docsgpt/dist/style.css";
 
 export default function MyApp({ Component, pageProps }) {
     return (

docs/pages/_app.mdx

@@ -1,11 +1,10 @@
 import { DocsGPTWidget } from "docsgpt";
-import "docsgpt/dist/style.css";
 
 export default function MyApp({ Component, pageProps }) {
   return (
     <>
       <Component {...pageProps} />
-        <DocsGPTWidget selectDocs="local/docsgpt-sep.zip/"/>
+        <DocsGPTWidget apiKey="d61a020c-ac8f-4f23-bb98-458e4da3c240" />
     </>
   )
 }

extensions/react-widget/.gitignore

@@ -0,0 +1,3 @@
+node_modules
+dist
+.parcel-cache

extensions/react-widget/.parcelrc

@@ -0,0 +1,10 @@
+{
+  "extends": "@parcel/config-default",
+  "resolvers": ["@parcel/resolver-glob","..."],
+  "transformers": {
+    "*.svg": ["...", "@parcel/transformer-svg-react", "@parcel/transformer-typescript-tsc"]
+},
+  "validators": {
+    "*.{ts,tsx}": ["@parcel/validator-typescript"]
+  }
+}

extensions/react-widget/README.md

@@ -13,7 +13,6 @@ npm install  docsgpt
 
 ```javascript
     import { DocsGPTWidget } from "docsgpt";
-    import "docsgpt/dist/style.css";
 
     const App = () => {
       return <DocsGPTWidget />;
@@ -24,10 +23,18 @@ To link the widget to your api and your documents you can pass parameters to the
 
 ```javascript
     import { DocsGPTWidget } from "docsgpt";
-    import "docsgpt/dist/style.css";
 
     const App = () => {
-      return <DocsGPTWidget apiHost="http://localhost:7001" selectDocs='default' apiKey=''/>;
+      return <DocsGPTWidget 
+             apiHost = 'http://localhost:7001',
+             selectDocs = 'default', 
+             apiKey = '',
+             avatar = 'https://d3dg1063dc54p9.cloudfront.net/cute-docsgpt.png',
+             title = 'Get AI assistance',
+             description = 'DocsGPT\'s AI Chatbot is here to help',
+             heroTitle = 'Welcome to DocsGPT !',
+             heroDescription='This chatbot is built with DocsGPT and utilises GenAI, please review important information using sources.'
+             />;
     };
 ```
 

extensions/react-widget/custom.d.ts

@@ -0,0 +1,9 @@
+declare module "*.svg" {
+    import * as React from "react";
+  
+    const ReactComponent: React.FunctionComponent<
+      React.SVGProps<SVGSVGElement> & { title?: string }
+    >;
+  
+    export default ReactComponent;
+  }

extensions/react-widget/dist/index.d.ts

@@ -1 +0,0 @@
-export { DocsGPTWidget } from "./src/components/DocsGPTWidget";

extensions/react-widget/dist/index.es.js

@@ -1,832 +0,0 @@
-import Ne, { useState as ke, useRef as ur, useEffect as Pe } from "react";
-var ne = { exports: {} }, Y = {};
-/**
- * @license React
- * react-jsx-runtime.development.js
- *
- * Copyright (c) Facebook, Inc. and its affiliates.
- *
- * This source code is licensed under the MIT license found in the
- * LICENSE file in the root directory of this source tree.
- */
-var Ce;
-function cr() {
-  return Ce || (Ce = 1, process.env.NODE_ENV !== "production" && function() {
-    var N = Ne, w = Symbol.for("react.element"), C = Symbol.for("react.portal"), u = Symbol.for("react.fragment"), E = Symbol.for("react.strict_mode"), S = Symbol.for("react.profiler"), T = Symbol.for("react.provider"), b = Symbol.for("react.context"), d = Symbol.for("react.forward_ref"), v = Symbol.for("react.suspense"), m = Symbol.for("react.suspense_list"), h = Symbol.for("react.memo"), x = Symbol.for("react.lazy"), p = Symbol.for("react.offscreen"), R = Symbol.iterator, j = "@@iterator";
-    function J(e) {
-      if (e === null || typeof e != "object")
-        return null;
-      var r = R && e[R] || e[j];
-      return typeof r == "function" ? r : null;
-    }
-    var O = N.__SECRET_INTERNALS_DO_NOT_USE_OR_YOU_WILL_BE_FIRED;
-    function g(e) {
-      {
-        for (var r = arguments.length, t = new Array(r > 1 ? r - 1 : 0), n = 1; n < r; n++)
-          t[n - 1] = arguments[n];
-        B("error", e, t);
-      }
-    }
-    function B(e, r, t) {
-      {
-        var n = O.ReactDebugCurrentFrame, o = n.getStackAddendum();
-        o !== "" && (r += "%s", t = t.concat([o]));
-        var s = t.map(function(i) {
-          return String(i);
-        });
-        s.unshift("Warning: " + r), Function.prototype.apply.call(console[e], console, s);
-      }
-    }
-    var D = !1, z = !1, De = !1, Ae = !1, Fe = !1, ae;
-    ae = Symbol.for("react.module.reference");
-    function Ie(e) {
-      return !!(typeof e == "string" || typeof e == "function" || e === u || e === S || Fe || e === E || e === v || e === m || Ae || e === p || D || z || De || typeof e == "object" && e !== null && (e.$$typeof === x || e.$$typeof === h || e.$$typeof === T || e.$$typeof === b || e.$$typeof === d || // This needs to include all possible module reference object
-      // types supported by any Flight configuration anywhere since
-      // we don't know which Flight build this will end up being used
-      // with.
-      e.$$typeof === ae || e.getModuleId !== void 0));
-    }
-    function $e(e, r, t) {
-      var n = e.displayName;
-      if (n)
-        return n;
-      var o = r.displayName || r.name || "";
-      return o !== "" ? t + "(" + o + ")" : t;
-    }
-    function ie(e) {
-      return e.displayName || "Context";
-    }
-    function k(e) {
-      if (e == null)
-        return null;
-      if (typeof e.tag == "number" && g("Received an unexpected object in getComponentNameFromType(). This is likely a bug in React. Please file an issue."), typeof e == "function")
-        return e.displayName || e.name || null;
-      if (typeof e == "string")
-        return e;
-      switch (e) {
-        case u:
-          return "Fragment";
-        case C:
-          return "Portal";
-        case S:
-          return "Profiler";
-        case E:
-          return "StrictMode";
-        case v:
-          return "Suspense";
-        case m:
-          return "SuspenseList";
-      }
-      if (typeof e == "object")
-        switch (e.$$typeof) {
-          case b:
-            var r = e;
-            return ie(r) + ".Consumer";
-          case T:
-            var t = e;
-            return ie(t._context) + ".Provider";
-          case d:
-            return $e(e, e.render, "ForwardRef");
-          case h:
-            var n = e.displayName || null;
-            return n !== null ? n : k(e.type) || "Memo";
-          case x: {
-            var o = e, s = o._payload, i = o._init;
-            try {
-              return k(i(s));
-            } catch {
-              return null;
-            }
-          }
-        }
-      return null;
-    }
-    var A = Object.assign, $ = 0, oe, se, le, ue, ce, fe, de;
-    function ve() {
-    }
-    ve.__reactDisabledLog = !0;
-    function We() {
-      {
-        if ($ === 0) {
-          oe = console.log, se = console.info, le = console.warn, ue = console.error, ce = console.group, fe = console.groupCollapsed, de = console.groupEnd;
-          var e = {
-            configurable: !0,
-            enumerable: !0,
-            value: ve,
-            writable: !0
-          };
-          Object.defineProperties(console, {
-            info: e,
-            log: e,
-            warn: e,
-            error: e,
-            group: e,
-            groupCollapsed: e,
-            groupEnd: e
-          });
-        }
-        $++;
-      }
-    }
-    function Ye() {
-      {
-        if ($--, $ === 0) {
-          var e = {
-            configurable: !0,
-            enumerable: !0,
-            writable: !0
-          };
-          Object.defineProperties(console, {
-            log: A({}, e, {
-              value: oe
-            }),
-            info: A({}, e, {
-              value: se
-            }),
-            warn: A({}, e, {
-              value: le
-            }),
-            error: A({}, e, {
-              value: ue
-            }),
-            group: A({}, e, {
-              value: ce
-            }),
-            groupCollapsed: A({}, e, {
-              value: fe
-            }),
-            groupEnd: A({}, e, {
-              value: de
-            })
-          });
-        }
-        $ < 0 && g("disabledDepth fell below zero. This is a bug in React. Please file an issue.");
-      }
-    }
-    var H = O.ReactCurrentDispatcher, K;
-    function V(e, r, t) {
-      {
-        if (K === void 0)
-          try {
-            throw Error();
-          } catch (o) {
-            var n = o.stack.trim().match(/\n( *(at )?)/);
-            K = n && n[1] || "";
-          }
-        return `
-` + K + e;
-      }
-    }
-    var X = !1, M;
-    {
-      var Le = typeof WeakMap == "function" ? WeakMap : Map;
-      M = new Le();
-    }
-    function pe(e, r) {
-      if (!e || X)
-        return "";
-      {
-        var t = M.get(e);
-        if (t !== void 0)
-          return t;
-      }
-      var n;
-      X = !0;
-      var o = Error.prepareStackTrace;
-      Error.prepareStackTrace = void 0;
-      var s;
-      s = H.current, H.current = null, We();
-      try {
-        if (r) {
-          var i = function() {
-            throw Error();
-          };
-          if (Object.defineProperty(i.prototype, "props", {
-            set: function() {
-              throw Error();
-            }
-          }), typeof Reflect == "object" && Reflect.construct) {
-            try {
-              Reflect.construct(i, []);
-            } catch (P) {
-              n = P;
-            }
-            Reflect.construct(e, [], i);
-          } else {
-            try {
-              i.call();
-            } catch (P) {
-              n = P;
-            }
-            e.call(i.prototype);
-          }
-        } else {
-          try {
-            throw Error();
-          } catch (P) {
-            n = P;
-          }
-          e();
-        }
-      } catch (P) {
-        if (P && n && typeof P.stack == "string") {
-          for (var a = P.stack.split(`
-`), y = n.stack.split(`
-`), c = a.length - 1, f = y.length - 1; c >= 1 && f >= 0 && a[c] !== y[f]; )
-            f--;
-          for (; c >= 1 && f >= 0; c--, f--)
-            if (a[c] !== y[f]) {
-              if (c !== 1 || f !== 1)
-                do
-                  if (c--, f--, f < 0 || a[c] !== y[f]) {
-                    var _ = `
-` + a[c].replace(" at new ", " at ");
-                    return e.displayName && _.includes("<anonymous>") && (_ = _.replace("<anonymous>", e.displayName)), typeof e == "function" && M.set(e, _), _;
-                  }
-                while (c >= 1 && f >= 0);
-              break;
-            }
-        }
-      } finally {
-        X = !1, H.current = s, Ye(), Error.prepareStackTrace = o;
-      }
-      var I = e ? e.displayName || e.name : "", je = I ? V(I) : "";
-      return typeof e == "function" && M.set(e, je), je;
-    }
-    function Ve(e, r, t) {
-      return pe(e, !1);
-    }
-    function Me(e) {
-      var r = e.prototype;
-      return !!(r && r.isReactComponent);
-    }
-    function U(e, r, t) {
-      if (e == null)
-        return "";
-      if (typeof e == "function")
-        return pe(e, Me(e));
-      if (typeof e == "string")
-        return V(e);
-      switch (e) {
-        case v:
-          return V("Suspense");
-        case m:
-          return V("SuspenseList");
-      }
-      if (typeof e == "object")
-        switch (e.$$typeof) {
-          case d:
-            return Ve(e.render);
-          case h:
-            return U(e.type, r, t);
-          case x: {
-            var n = e, o = n._payload, s = n._init;
-            try {
-              return U(s(o), r, t);
-            } catch {
-            }
-          }
-        }
-      return "";
-    }
-    var G = Object.prototype.hasOwnProperty, he = {}, me = O.ReactDebugCurrentFrame;
-    function q(e) {
-      if (e) {
-        var r = e._owner, t = U(e.type, e._source, r ? r.type : null);
-        me.setExtraStackFrame(t);
-      } else
-        me.setExtraStackFrame(null);
-    }
-    function Ue(e, r, t, n, o) {
-      {
-        var s = Function.call.bind(G);
-        for (var i in e)
-          if (s(e, i)) {
-            var a = void 0;
-            try {
-              if (typeof e[i] != "function") {
-                var y = Error((n || "React class") + ": " + t + " type `" + i + "` is invalid; it must be a function, usually from the `prop-types` package, but received `" + typeof e[i] + "`.This often happens because of typos such as `PropTypes.function` instead of `PropTypes.func`.");
-                throw y.name = "Invariant Violation", y;
-              }
-              a = e[i](r, i, n, t, null, "SECRET_DO_NOT_PASS_THIS_OR_YOU_WILL_BE_FIRED");
-            } catch (c) {
-              a = c;
-            }
-            a && !(a instanceof Error) && (q(o), g("%s: type specification of %s `%s` is invalid; the type checker function must return `null` or an `Error` but returned a %s. You may have forgotten to pass an argument to the type checker creator (arrayOf, instanceOf, objectOf, oneOf, oneOfType, and shape all require an argument).", n || "React class", t, i, typeof a), q(null)), a instanceof Error && !(a.message in he) && (he[a.message] = !0, q(o), g("Failed %s type: %s", t, a.message), q(null));
-          }
-      }
-    }
-    var Ge = Array.isArray;
-    function Z(e) {
-      return Ge(e);
-    }
-    function qe(e) {
-      {
-        var r = typeof Symbol == "function" && Symbol.toStringTag, t = r && e[Symbol.toStringTag] || e.constructor.name || "Object";
-        return t;
-      }
-    }
-    function Je(e) {
-      try {
-        return ge(e), !1;
-      } catch {
-        return !0;
-      }
-    }
-    function ge(e) {
-      return "" + e;
-    }
-    function ye(e) {
-      if (Je(e))
-        return g("The provided key is an unsupported type %s. This value must be coerced to a string before before using it here.", qe(e)), ge(e);
-    }
-    var W = O.ReactCurrentOwner, Be = {
-      key: !0,
-      ref: !0,
-      __self: !0,
-      __source: !0
-    }, be, Ee, Q;
-    Q = {};
-    function ze(e) {
-      if (G.call(e, "ref")) {
-        var r = Object.getOwnPropertyDescriptor(e, "ref").get;
-        if (r && r.isReactWarning)
-          return !1;
-      }
-      return e.ref !== void 0;
-    }
-    function He(e) {
-      if (G.call(e, "key")) {
-        var r = Object.getOwnPropertyDescriptor(e, "key").get;
-        if (r && r.isReactWarning)
-          return !1;
-      }
-      return e.key !== void 0;
-    }
-    function Ke(e, r) {
-      if (typeof e.ref == "string" && W.current && r && W.current.stateNode !== r) {
-        var t = k(W.current.type);
-        Q[t] || (g('Component "%s" contains the string ref "%s". Support for string refs will be removed in a future major release. This case cannot be automatically converted to an arrow function. We ask you to manually fix this case by using useRef() or createRef() instead. Learn more about using refs safely here: https://reactjs.org/link/strict-mode-string-ref', k(W.current.type), e.ref), Q[t] = !0);
-      }
-    }
-    function Xe(e, r) {
-      {
-        var t = function() {
-          be || (be = !0, g("%s: `key` is not a prop. Trying to access it will result in `undefined` being returned. If you need to access the same value within the child component, you should pass it as a different prop. (https://reactjs.org/link/special-props)", r));
-        };
-        t.isReactWarning = !0, Object.defineProperty(e, "key", {
-          get: t,
-          configurable: !0
-        });
-      }
-    }
-    function Ze(e, r) {
-      {
-        var t = function() {
-          Ee || (Ee = !0, g("%s: `ref` is not a prop. Trying to access it will result in `undefined` being returned. If you need to access the same value within the child component, you should pass it as a different prop. (https://reactjs.org/link/special-props)", r));
-        };
-        t.isReactWarning = !0, Object.defineProperty(e, "ref", {
-          get: t,
-          configurable: !0
-        });
-      }
-    }
-    var Qe = function(e, r, t, n, o, s, i) {
-      var a = {
-        // This tag allows us to uniquely identify this as a React Element
-        $$typeof: w,
-        // Built-in properties that belong on the element
-        type: e,
-        key: r,
-        ref: t,
-        props: i,
-        // Record the component responsible for creating this element.
-        _owner: s
-      };
-      return a._store = {}, Object.defineProperty(a._store, "validated", {
-        configurable: !1,
-        enumerable: !1,
-        writable: !0,
-        value: !1
-      }), Object.defineProperty(a, "_self", {
-        configurable: !1,
-        enumerable: !1,
-        writable: !1,
-        value: n
-      }), Object.defineProperty(a, "_source", {
-        configurable: !1,
-        enumerable: !1,
-        writable: !1,
-        value: o
-      }), Object.freeze && (Object.freeze(a.props), Object.freeze(a)), a;
-    };
-    function er(e, r, t, n, o) {
-      {
-        var s, i = {}, a = null, y = null;
-        t !== void 0 && (ye(t), a = "" + t), He(r) && (ye(r.key), a = "" + r.key), ze(r) && (y = r.ref, Ke(r, o));
-        for (s in r)
-          G.call(r, s) && !Be.hasOwnProperty(s) && (i[s] = r[s]);
-        if (e && e.defaultProps) {
-          var c = e.defaultProps;
-          for (s in c)
-            i[s] === void 0 && (i[s] = c[s]);
-        }
-        if (a || y) {
-          var f = typeof e == "function" ? e.displayName || e.name || "Unknown" : e;
-          a && Xe(i, f), y && Ze(i, f);
-        }
-        return Qe(e, a, y, o, n, W.current, i);
-      }
-    }
-    var ee = O.ReactCurrentOwner, xe = O.ReactDebugCurrentFrame;
-    function F(e) {
-      if (e) {
-        var r = e._owner, t = U(e.type, e._source, r ? r.type : null);
-        xe.setExtraStackFrame(t);
-      } else
-        xe.setExtraStackFrame(null);
-    }
-    var re;
-    re = !1;
-    function te(e) {
-      return typeof e == "object" && e !== null && e.$$typeof === w;
-    }
-    function _e() {
-      {
-        if (ee.current) {
-          var e = k(ee.current.type);
-          if (e)
-            return `
-
-Check the render method of \`` + e + "`.";
-        }
-        return "";
-      }
-    }
-    function rr(e) {
-      {
-        if (e !== void 0) {
-          var r = e.fileName.replace(/^.*[\\\/]/, ""), t = e.lineNumber;
-          return `
-
-Check your code at ` + r + ":" + t + ".";
-        }
-        return "";
-      }
-    }
-    var Re = {};
-    function tr(e) {
-      {
-        var r = _e();
-        if (!r) {
-          var t = typeof e == "string" ? e : e.displayName || e.name;
-          t && (r = `
-
-Check the top-level render call using <` + t + ">.");
-        }
-        return r;
-      }
-    }
-    function we(e, r) {
-      {
-        if (!e._store || e._store.validated || e.key != null)
-          return;
-        e._store.validated = !0;
-        var t = tr(r);
-        if (Re[t])
-          return;
-        Re[t] = !0;
-        var n = "";
-        e && e._owner && e._owner !== ee.current && (n = " It was passed a child from " + k(e._owner.type) + "."), F(e), g('Each child in a list should have a unique "key" prop.%s%s See https://reactjs.org/link/warning-keys for more information.', t, n), F(null);
-      }
-    }
-    function Te(e, r) {
-      {
-        if (typeof e != "object")
-          return;
-        if (Z(e))
-          for (var t = 0; t < e.length; t++) {
-            var n = e[t];
-            te(n) && we(n, r);
-          }
-        else if (te(e))
-          e._store && (e._store.validated = !0);
-        else if (e) {
-          var o = J(e);
-          if (typeof o == "function" && o !== e.entries)
-            for (var s = o.call(e), i; !(i = s.next()).done; )
-              te(i.value) && we(i.value, r);
-        }
-      }
-    }
-    function nr(e) {
-      {
-        var r = e.type;
-        if (r == null || typeof r == "string")
-          return;
-        var t;
-        if (typeof r == "function")
-          t = r.propTypes;
-        else if (typeof r == "object" && (r.$$typeof === d || // Note: Memo only checks outer props here.
-        // Inner props are checked in the reconciler.
-        r.$$typeof === h))
-          t = r.propTypes;
-        else
-          return;
-        if (t) {
-          var n = k(r);
-          Ue(t, e.props, "prop", n, e);
-        } else if (r.PropTypes !== void 0 && !re) {
-          re = !0;
-          var o = k(r);
-          g("Component %s declared `PropTypes` instead of `propTypes`. Did you misspell the property assignment?", o || "Unknown");
-        }
-        typeof r.getDefaultProps == "function" && !r.getDefaultProps.isReactClassApproved && g("getDefaultProps is only used on classic React.createClass definitions. Use a static property named `defaultProps` instead.");
-      }
-    }
-    function ar(e) {
-      {
-        for (var r = Object.keys(e.props), t = 0; t < r.length; t++) {
-          var n = r[t];
-          if (n !== "children" && n !== "key") {
-            F(e), g("Invalid prop `%s` supplied to `React.Fragment`. React.Fragment can only have `key` and `children` props.", n), F(null);
-            break;
-          }
-        }
-        e.ref !== null && (F(e), g("Invalid attribute `ref` supplied to `React.Fragment`."), F(null));
-      }
-    }
-    function Se(e, r, t, n, o, s) {
-      {
-        var i = Ie(e);
-        if (!i) {
-          var a = "";
-          (e === void 0 || typeof e == "object" && e !== null && Object.keys(e).length === 0) && (a += " You likely forgot to export your component from the file it's defined in, or you might have mixed up default and named imports.");
-          var y = rr(o);
-          y ? a += y : a += _e();
-          var c;
-          e === null ? c = "null" : Z(e) ? c = "array" : e !== void 0 && e.$$typeof === w ? (c = "<" + (k(e.type) || "Unknown") + " />", a = " Did you accidentally export a JSX literal instead of a component?") : c = typeof e, g("React.jsx: type is invalid -- expected a string (for built-in components) or a class/function (for composite components) but got: %s.%s", c, a);
-        }
-        var f = er(e, r, t, o, s);
-        if (f == null)
-          return f;
-        if (i) {
-          var _ = r.children;
-          if (_ !== void 0)
-            if (n)
-              if (Z(_)) {
-                for (var I = 0; I < _.length; I++)
-                  Te(_[I], e);
-                Object.freeze && Object.freeze(_);
-              } else
-                g("React.jsx: Static children should always be an array. You are likely explicitly calling React.jsxs or React.jsxDEV. Use the Babel transform instead.");
-            else
-              Te(_, e);
-        }
-        return e === u ? ar(f) : nr(f), f;
-      }
-    }
-    function ir(e, r, t) {
-      return Se(e, r, t, !0);
-    }
-    function or(e, r, t) {
-      return Se(e, r, t, !1);
-    }
-    var sr = or, lr = ir;
-    Y.Fragment = u, Y.jsx = sr, Y.jsxs = lr;
-  }()), Y;
-}
-var L = {};
-/**
- * @license React
- * react-jsx-runtime.production.min.js
- *
- * Copyright (c) Facebook, Inc. and its affiliates.
- *
- * This source code is licensed under the MIT license found in the
- * LICENSE file in the root directory of this source tree.
- */
-var Oe;
-function fr() {
-  if (Oe)
-    return L;
-  Oe = 1;
-  var N = Ne, w = Symbol.for("react.element"), C = Symbol.for("react.fragment"), u = Object.prototype.hasOwnProperty, E = N.__SECRET_INTERNALS_DO_NOT_USE_OR_YOU_WILL_BE_FIRED.ReactCurrentOwner, S = { key: !0, ref: !0, __self: !0, __source: !0 };
-  function T(b, d, v) {
-    var m, h = {}, x = null, p = null;
-    v !== void 0 && (x = "" + v), d.key !== void 0 && (x = "" + d.key), d.ref !== void 0 && (p = d.ref);
-    for (m in d)
-      u.call(d, m) && !S.hasOwnProperty(m) && (h[m] = d[m]);
-    if (b && b.defaultProps)
-      for (m in d = b.defaultProps, d)
-        h[m] === void 0 && (h[m] = d[m]);
-    return { $$typeof: w, type: b, key: x, ref: p, props: h, _owner: E.current };
-  }
-  return L.Fragment = C, L.jsx = T, L.jsxs = T, L;
-}
-process.env.NODE_ENV === "production" ? ne.exports = fr() : ne.exports = cr();
-var l = ne.exports;
-function dr({
-  question: N = "",
-  apiKey: w = "",
-  selectedDocs: C = "",
-  history: u = [],
-  conversationId: E = null,
-  apiHost: S = "",
-  onEvent: T = () => {
-    console.log("Event triggered, but no handler provided.");
-  }
-}) {
-  let b = "default";
-  return C && (b = C), new Promise((d, v) => {
-    const m = {
-      question: N,
-      api_key: w,
-      embeddings_key: w,
-      active_docs: b,
-      history: JSON.stringify(u),
-      conversation_id: E,
-      model: "default"
-    };
-    fetch(S + "/stream", {
-      method: "POST",
-      headers: {
-        "Content-Type": "application/json"
-      },
-      body: JSON.stringify(m)
-    }).then((h) => {
-      if (!h.body)
-        throw Error("No response body");
-      const x = h.body.getReader(), p = new TextDecoder("utf-8");
-      let R = 0;
-      const j = ({
-        done: J,
-        value: O
-      }) => {
-        if (J) {
-          console.log(R), d();
-          return;
-        }
-        R += 1;
-        const B = p.decode(O).split(`
-`);
-        for (let D of B) {
-          if (D.trim() == "")
-            continue;
-          D.startsWith("data:") && (D = D.substring(5));
-          const z = new MessageEvent("message", {
-            data: D
-          });
-          T(z);
-        }
-        x.read().then(j).catch(v);
-      };
-      x.read().then(j).catch(v);
-    }).catch((h) => {
-      console.error("Connection failed:", h), v(h);
-    });
-  });
-}
-const pr = ({ apiHost: N = "https://gptcloud.arc53.com", selectDocs: w = "default", apiKey: C = "docsgpt-public" }) => {
-  const [u, E] = ke(() => typeof window < "u" && localStorage.getItem("docsGPTChatState") || "init"), [S, T] = ke(""), b = ur(null);
-  Pe(() => {
-    if (b.current) {
-      const v = b.current;
-      v.scrollTop = v.scrollHeight;
-    }
-  }, [S]), Pe(() => {
-    localStorage.setItem("docsGPTChatState", u);
-  }, [u]);
-  const d = (v) => {
-    T(""), v.preventDefault(), E(
-      "processing"
-      /* Processing */
-    ), setTimeout(() => {
-      E(
-        "answer"
-        /* Answer */
-      );
-    }, 800);
-    const h = v.currentTarget[0].value;
-    dr({
-      question: h,
-      apiKey: C,
-      selectedDocs: w,
-      history: [],
-      conversationId: null,
-      apiHost: N,
-      onEvent: (x) => {
-        const p = JSON.parse(x.data);
-        if (p.type === "end")
-          E(
-            "answer"
-            /* Answer */
-          );
-        else if (p.type === "source") {
-          let R;
-          if (p.metadata && p.metadata.title) {
-            const j = p.metadata.title.split("/");
-            R = {
-              title: j[j.length - 1],
-              text: p.doc
-            };
-          } else
-            R = { title: p.doc, text: p.doc };
-          console.log(R);
-        } else if (p.type === "id")
-          console.log(p.id);
-        else {
-          const R = p.answer;
-          T((j) => j + R);
-        }
-      }
-    });
-  };
-  return /* @__PURE__ */ l.jsx(l.Fragment, { children: /* @__PURE__ */ l.jsxs("div", { className: "dark widget-container", children: [
-    /* @__PURE__ */ l.jsx(
-      "div",
-      {
-        onClick: () => E(
-          "init"
-          /* Init */
-        ),
-        className: `${u !== "minimized" ? "hidden" : ""} cursor-pointer`,
-        children: /* @__PURE__ */ l.jsx("div", { className: "mr-2 mb-2 w-20 h-20 rounded-full overflow-hidden dark:divide-gray-700 border dark:border-gray-700 bg-gradient-to-br from-gray-100/80 via-white to-white dark:from-gray-900/80 dark:via-gray-900 dark:to-gray-900 font-sans shadow backdrop-blur-sm flex items-center justify-center", children: /* @__PURE__ */ l.jsx(
-          "img",
-          {
-            src: "https://d3dg1063dc54p9.cloudfront.net/cute-docsgpt.png",
-            alt: "DocsGPT",
-            className: "cursor-pointer hover:opacity-50 h-14"
-          }
-        ) })
-      }
-    ),
-    /* @__PURE__ */ l.jsxs("div", { className: ` ${u !== "minimized" ? "" : "hidden"} divide-y dark:divide-gray-700 rounded-md border dark:border-gray-700 bg-gradient-to-br from-gray-100/80 via-white to-white dark:from-gray-900/80 dark:via-gray-900 dark:to-gray-900 font-sans shadow backdrop-blur-sm`, style: { width: "18rem", transform: "translateY(0%) translateZ(0px)" }, children: [
-      /* @__PURE__ */ l.jsxs("div", { children: [
-        /* @__PURE__ */ l.jsx(
-          "img",
-          {
-            src: "https://d3dg1063dc54p9.cloudfront.net/exit.svg",
-            alt: "Exit",
-            className: "cursor-pointer hover:opacity-50 h-2 absolute top-0 right-0 m-2 white-filter",
-            onClick: (v) => {
-              v.stopPropagation(), E(
-                "minimized"
-                /* Minimized */
-              );
-            }
-          }
-        ),
-        /* @__PURE__ */ l.jsxs("div", { className: "flex items-center gap-2 p-3", children: [
-          /* @__PURE__ */ l.jsxs("div", { className: `${u === "init" || u === "processing" || u === "typing" ? "" : "hidden"} flex-1`, children: [
-            /* @__PURE__ */ l.jsx("h3", { className: "text-sm font-bold text-gray-700 dark:text-gray-200", children: "Need help with documentation?" }),
-            /* @__PURE__ */ l.jsx("p", { className: "mt-1 text-xs text-gray-400 dark:text-gray-500", children: "DocsGPT AI assistant will help you with docs" })
-          ] }),
-          /* @__PURE__ */ l.jsx("div", { id: "docsgpt-answer", ref: b, className: `${u !== "answer" ? "hidden" : ""}`, children: /* @__PURE__ */ l.jsx("p", { className: "mt-1 text-sm text-gray-600 dark:text-white text-left", children: S }) })
-        ] })
-      ] }),
-      /* @__PURE__ */ l.jsxs("div", { className: "w-full", children: [
-        /* @__PURE__ */ l.jsx(
-          "button",
-          {
-            onClick: () => E(
-              "typing"
-              /* Typing */
-            ),
-            className: `flex w-full justify-center px-5 py-3 text-sm text-gray-800 font-bold dark:text-white transition duration-300 hover:bg-gray-100 rounded-b dark:hover:bg-gray-800/70 ${u !== "init" ? "hidden" : ""}`,
-            children: "Ask DocsGPT"
-          }
-        ),
-        (u === "typing" || u === "answer") && /* @__PURE__ */ l.jsxs(
-          "form",
-          {
-            onSubmit: d,
-            className: "relative w-full m-0",
-            style: { opacity: 1 },
-            children: [
-              /* @__PURE__ */ l.jsx(
-                "input",
-                {
-                  type: "text",
-                  className: "w-full bg-transparent px-5 py-3 pr-8 text-sm text-gray-700 dark:text-white focus:outline-none",
-                  placeholder: "What do you want to do?"
-                }
-              ),
-              /* @__PURE__ */ l.jsx("button", { className: "absolute text-gray-400 dark:text-gray-500 text-sm inset-y-0 right-2 -mx-2 px-2", type: "submit", children: "Submit" })
-            ]
-          }
-        ),
-        /* @__PURE__ */ l.jsxs("p", { className: `${u !== "processing" ? "hidden" : ""} flex w-full justify-center px-5 py-3 text-sm text-gray-800 font-bold dark:text-white transition duration-300 rounded-b`, children: [
-          "Processing",
-          /* @__PURE__ */ l.jsx("span", { className: "dot-animation", children: "." }),
-          /* @__PURE__ */ l.jsx("span", { className: "dot-animation delay-200", children: "." }),
-          /* @__PURE__ */ l.jsx("span", { className: "dot-animation delay-400", children: "." })
-        ] })
-      ] })
-    ] })
-  ] }) });
-};
-export {
-  pr as DocsGPTWidget
-};
-//# sourceMappingURL=index.es.js.map

extensions/react-widget/dist/src/App.d.ts

@@ -1,3 +0,0 @@
-/// <reference types="react" />
-declare function App(): JSX.Element;
-export default App;

extensions/react-widget/dist/src/components/DocsGPTWidget.d.ts

@@ -1,5 +0,0 @@
-export declare const DocsGPTWidget: ({ apiHost, selectDocs, apiKey }: {
-    apiHost?: string | undefined;
-    selectDocs?: string | undefined;
-    apiKey?: string | undefined;
-}) => JSX.Element;

extensions/react-widget/dist/src/components/index.d.ts

@@ -1 +0,0 @@
-export { DocsGPTWidget } from "./DocsGPTWidget";

extensions/react-widget/dist/style.css

@@ -1,762 +0,0 @@
-/*
-! tailwindcss v3.2.4 | MIT License | https://tailwindcss.com
-*//*
-1. Prevent padding and border from affecting element width. (https://github.com/mozdevs/cssremedy/issues/4)
-2. Allow adding a border to an element by just adding a border-width. (https://github.com/tailwindcss/tailwindcss/pull/116)
-*/
-
-*,
-::before,
-::after {
-  box-sizing: border-box; /* 1 */
-  border-width: 0; /* 2 */
-  border-style: solid; /* 2 */
-  border-color: #e5e7eb; /* 2 */
-}
-
-::before,
-::after {
-  --tw-content: '';
-}
-
-/*
-1. Use a consistent sensible line-height in all browsers.
-2. Prevent adjustments of font size after orientation changes in iOS.
-3. Use a more readable tab size.
-4. Use the user's configured `sans` font-family by default.
-5. Use the user's configured `sans` font-feature-settings by default.
-*/
-
-html {
-  line-height: 1.5; /* 1 */
-  -webkit-text-size-adjust: 100%; /* 2 */
-  -moz-tab-size: 4; /* 3 */
-  -o-tab-size: 4;
-     tab-size: 4; /* 3 */
-  font-family: ui-sans-serif, system-ui, -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; /* 4 */
-  font-feature-settings: normal; /* 5 */
-}
-
-/*
-1. Remove the margin in all browsers.
-2. Inherit line-height from `html` so users can set them as a class directly on the `html` element.
-*/
-
-body {
-  margin: 0; /* 1 */
-  line-height: inherit; /* 2 */
-}
-
-/*
-1. Add the correct height in Firefox.
-2. Correct the inheritance of border color in Firefox. (https://bugzilla.mozilla.org/show_bug.cgi?id=190655)
-3. Ensure horizontal rules are visible by default.
-*/
-
-hr {
-  height: 0; /* 1 */
-  color: inherit; /* 2 */
-  border-top-width: 1px; /* 3 */
-}
-
-/*
-Add the correct text decoration in Chrome, Edge, and Safari.
-*/
-
-abbr:where([title]) {
-  -webkit-text-decoration: underline dotted;
-          text-decoration: underline dotted;
-}
-
-/*
-Remove the default font size and weight for headings.
-*/
-
-h1,
-h2,
-h3,
-h4,
-h5,
-h6 {
-  font-size: inherit;
-  font-weight: inherit;
-}
-
-/*
-Reset links to optimize for opt-in styling instead of opt-out.
-*/
-
-a {
-  color: inherit;
-  text-decoration: inherit;
-}
-
-/*
-Add the correct font weight in Edge and Safari.
-*/
-
-b,
-strong {
-  font-weight: bolder;
-}
-
-/*
-1. Use the user's configured `mono` font family by default.
-2. Correct the odd `em` font sizing in all browsers.
-*/
-
-code,
-kbd,
-samp,
-pre {
-  font-family: ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace; /* 1 */
-  font-size: 1em; /* 2 */
-}
-
-/*
-Add the correct font size in all browsers.
-*/
-
-small {
-  font-size: 80%;
-}
-
-/*
-Prevent `sub` and `sup` elements from affecting the line height in all browsers.
-*/
-
-sub,
-sup {
-  font-size: 75%;
-  line-height: 0;
-  position: relative;
-  vertical-align: baseline;
-}
-
-sub {
-  bottom: -0.25em;
-}
-
-sup {
-  top: -0.5em;
-}
-
-/*
-1. Remove text indentation from table contents in Chrome and Safari. (https://bugs.chromium.org/p/chromium/issues/detail?id=999088, https://bugs.webkit.org/show_bug.cgi?id=201297)
-2. Correct table border color inheritance in all Chrome and Safari. (https://bugs.chromium.org/p/chromium/issues/detail?id=935729, https://bugs.webkit.org/show_bug.cgi?id=195016)
-3. Remove gaps between table borders by default.
-*/
-
-table {
-  text-indent: 0; /* 1 */
-  border-color: inherit; /* 2 */
-  border-collapse: collapse; /* 3 */
-}
-
-/*
-1. Change the font styles in all browsers.
-2. Remove the margin in Firefox and Safari.
-3. Remove default padding in all browsers.
-*/
-
-button,
-input,
-optgroup,
-select,
-textarea {
-  font-family: inherit; /* 1 */
-  font-size: 100%; /* 1 */
-  font-weight: inherit; /* 1 */
-  line-height: inherit; /* 1 */
-  color: inherit; /* 1 */
-  margin: 0; /* 2 */
-  padding: 0; /* 3 */
-}
-
-/*
-Remove the inheritance of text transform in Edge and Firefox.
-*/
-
-button,
-select {
-  text-transform: none;
-}
-
-/*
-1. Correct the inability to style clickable types in iOS and Safari.
-2. Remove default button styles.
-*/
-
-button,
-[type='button'],
-[type='reset'],
-[type='submit'] {
-  -webkit-appearance: button; /* 1 */
-  background-color: transparent; /* 2 */
-  background-image: none; /* 2 */
-}
-
-/*
-Use the modern Firefox focus style for all focusable elements.
-*/
-
-:-moz-focusring {
-  outline: auto;
-}
-
-/*
-Remove the additional `:invalid` styles in Firefox. (https://github.com/mozilla/gecko-dev/blob/2f9eacd9d3d995c937b4251a5557d95d494c9be1/layout/style/res/forms.css#L728-L737)
-*/
-
-:-moz-ui-invalid {
-  box-shadow: none;
-}
-
-/*
-Add the correct vertical alignment in Chrome and Firefox.
-*/
-
-progress {
-  vertical-align: baseline;
-}
-
-/*
-Correct the cursor style of increment and decrement buttons in Safari.
-*/
-
-::-webkit-inner-spin-button,
-::-webkit-outer-spin-button {
-  height: auto;
-}
-
-/*
-1. Correct the odd appearance in Chrome and Safari.
-2. Correct the outline style in Safari.
-*/
-
-[type='search'] {
-  -webkit-appearance: textfield; /* 1 */
-  outline-offset: -2px; /* 2 */
-}
-
-/*
-Remove the inner padding in Chrome and Safari on macOS.
-*/
-
-::-webkit-search-decoration {
-  -webkit-appearance: none;
-}
-
-/*
-1. Correct the inability to style clickable types in iOS and Safari.
-2. Change font properties to `inherit` in Safari.
-*/
-
-::-webkit-file-upload-button {
-  -webkit-appearance: button; /* 1 */
-  font: inherit; /* 2 */
-}
-
-/*
-Add the correct display in Chrome and Safari.
-*/
-
-summary {
-  display: list-item;
-}
-
-/*
-Removes the default spacing and border for appropriate elements.
-*/
-
-blockquote,
-dl,
-dd,
-h1,
-h2,
-h3,
-h4,
-h5,
-h6,
-hr,
-figure,
-p,
-pre {
-  margin: 0;
-}
-
-fieldset {
-  margin: 0;
-  padding: 0;
-}
-
-legend {
-  padding: 0;
-}
-
-ol,
-ul,
-menu {
-  list-style: none;
-  margin: 0;
-  padding: 0;
-}
-
-/*
-Prevent resizing textareas horizontally by default.
-*/
-
-textarea {
-  resize: vertical;
-}
-
-/*
-1. Reset the default placeholder opacity in Firefox. (https://github.com/tailwindlabs/tailwindcss/issues/3300)
-2. Set the default placeholder color to the user's configured gray 400 color.
-*/
-
-input::-moz-placeholder, textarea::-moz-placeholder {
-  opacity: 1; /* 1 */
-  color: #9ca3af; /* 2 */
-}
-
-input::placeholder,
-textarea::placeholder {
-  opacity: 1; /* 1 */
-  color: #9ca3af; /* 2 */
-}
-
-/*
-Set the default cursor for buttons.
-*/
-
-button,
-[role="button"] {
-  cursor: pointer;
-}
-
-/*
-Make sure disabled buttons don't get the pointer cursor.
-*/
-:disabled {
-  cursor: default;
-}
-
-/*
-1. Make replaced elements `display: block` by default. (https://github.com/mozdevs/cssremedy/issues/14)
-2. Add `vertical-align: middle` to align replaced elements more sensibly by default. (https://github.com/jensimmons/cssremedy/issues/14#issuecomment-634934210)
-   This can trigger a poorly considered lint error in some tools but is included by design.
-*/
-
-img,
-svg,
-video,
-canvas,
-audio,
-iframe,
-embed,
-object {
-  display: block; /* 1 */
-  vertical-align: middle; /* 2 */
-}
-
-/*
-Constrain images and videos to the parent width and preserve their intrinsic aspect ratio. (https://github.com/mozdevs/cssremedy/issues/14)
-*/
-
-img,
-video {
-  max-width: 100%;
-  height: auto;
-}
-
-/* Make elements with the HTML hidden attribute stay hidden by default */
-[hidden] {
-  display: none;
-}
-
-*, ::before, ::after {
-  --tw-border-spacing-x: 0;
-  --tw-border-spacing-y: 0;
-  --tw-translate-x: 0;
-  --tw-translate-y: 0;
-  --tw-rotate: 0;
-  --tw-skew-x: 0;
-  --tw-skew-y: 0;
-  --tw-scale-x: 1;
-  --tw-scale-y: 1;
-  --tw-pan-x:  ;
-  --tw-pan-y:  ;
-  --tw-pinch-zoom:  ;
-  --tw-scroll-snap-strictness: proximity;
-  --tw-ordinal:  ;
-  --tw-slashed-zero:  ;
-  --tw-numeric-figure:  ;
-  --tw-numeric-spacing:  ;
-  --tw-numeric-fraction:  ;
-  --tw-ring-inset:  ;
-  --tw-ring-offset-width: 0px;
-  --tw-ring-offset-color: #fff;
-  --tw-ring-color: rgb(59 130 246 / 0.5);
-  --tw-ring-offset-shadow: 0 0 #0000;
-  --tw-ring-shadow: 0 0 #0000;
-  --tw-shadow: 0 0 #0000;
-  --tw-shadow-colored: 0 0 #0000;
-  --tw-blur:  ;
-  --tw-brightness:  ;
-  --tw-contrast:  ;
-  --tw-grayscale:  ;
-  --tw-hue-rotate:  ;
-  --tw-invert:  ;
-  --tw-saturate:  ;
-  --tw-sepia:  ;
-  --tw-drop-shadow:  ;
-  --tw-backdrop-blur:  ;
-  --tw-backdrop-brightness:  ;
-  --tw-backdrop-contrast:  ;
-  --tw-backdrop-grayscale:  ;
-  --tw-backdrop-hue-rotate:  ;
-  --tw-backdrop-invert:  ;
-  --tw-backdrop-opacity:  ;
-  --tw-backdrop-saturate:  ;
-  --tw-backdrop-sepia:  ;
-}
-
-::backdrop {
-  --tw-border-spacing-x: 0;
-  --tw-border-spacing-y: 0;
-  --tw-translate-x: 0;
-  --tw-translate-y: 0;
-  --tw-rotate: 0;
-  --tw-skew-x: 0;
-  --tw-skew-y: 0;
-  --tw-scale-x: 1;
-  --tw-scale-y: 1;
-  --tw-pan-x:  ;
-  --tw-pan-y:  ;
-  --tw-pinch-zoom:  ;
-  --tw-scroll-snap-strictness: proximity;
-  --tw-ordinal:  ;
-  --tw-slashed-zero:  ;
-  --tw-numeric-figure:  ;
-  --tw-numeric-spacing:  ;
-  --tw-numeric-fraction:  ;
-  --tw-ring-inset:  ;
-  --tw-ring-offset-width: 0px;
-  --tw-ring-offset-color: #fff;
-  --tw-ring-color: rgb(59 130 246 / 0.5);
-  --tw-ring-offset-shadow: 0 0 #0000;
-  --tw-ring-shadow: 0 0 #0000;
-  --tw-shadow: 0 0 #0000;
-  --tw-shadow-colored: 0 0 #0000;
-  --tw-blur:  ;
-  --tw-brightness:  ;
-  --tw-contrast:  ;
-  --tw-grayscale:  ;
-  --tw-hue-rotate:  ;
-  --tw-invert:  ;
-  --tw-saturate:  ;
-  --tw-sepia:  ;
-  --tw-drop-shadow:  ;
-  --tw-backdrop-blur:  ;
-  --tw-backdrop-brightness:  ;
-  --tw-backdrop-contrast:  ;
-  --tw-backdrop-grayscale:  ;
-  --tw-backdrop-hue-rotate:  ;
-  --tw-backdrop-invert:  ;
-  --tw-backdrop-opacity:  ;
-  --tw-backdrop-saturate:  ;
-  --tw-backdrop-sepia:  ;
-}
-.absolute {
-  position: absolute;
-}
-.relative {
-  position: relative;
-}
-.inset-y-0 {
-  top: 0px;
-  bottom: 0px;
-}
-.top-0 {
-  top: 0px;
-}
-.right-0 {
-  right: 0px;
-}
-.right-2 {
-  right: 0.5rem;
-}
-.m-2 {
-  margin: 0.5rem;
-}
-.m-0 {
-  margin: 0px;
-}
-.-mx-2 {
-  margin-left: -0.5rem;
-  margin-right: -0.5rem;
-}
-.mr-2 {
-  margin-right: 0.5rem;
-}
-.mb-2 {
-  margin-bottom: 0.5rem;
-}
-.mt-1 {
-  margin-top: 0.25rem;
-}
-.flex {
-  display: flex;
-}
-.hidden {
-  display: none;
-}
-.h-20 {
-  height: 5rem;
-}
-.h-14 {
-  height: 3.5rem;
-}
-.h-2 {
-  height: 0.5rem;
-}
-.w-20 {
-  width: 5rem;
-}
-.w-full {
-  width: 100%;
-}
-.flex-1 {
-  flex: 1 1 0%;
-}
-.transform {
-  transform: translate(var(--tw-translate-x), var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y));
-}
-.cursor-pointer {
-  cursor: pointer;
-}
-.items-center {
-  align-items: center;
-}
-.justify-center {
-  justify-content: center;
-}
-.gap-2 {
-  gap: 0.5rem;
-}
-.divide-y > :not([hidden]) ~ :not([hidden]) {
-  --tw-divide-y-reverse: 0;
-  border-top-width: calc(1px * calc(1 - var(--tw-divide-y-reverse)));
-  border-bottom-width: calc(1px * var(--tw-divide-y-reverse));
-}
-.overflow-hidden {
-  overflow: hidden;
-}
-.rounded-full {
-  border-radius: 9999px;
-}
-.rounded-md {
-  border-radius: 0.375rem;
-}
-.rounded-b {
-  border-bottom-right-radius: 0.25rem;
-  border-bottom-left-radius: 0.25rem;
-}
-.border {
-  border-width: 1px;
-}
-.bg-transparent {
-  background-color: transparent;
-}
-.bg-gradient-to-br {
-  background-image: linear-gradient(to bottom right, var(--tw-gradient-stops));
-}
-.from-gray-100\/80 {
-  --tw-gradient-from: rgb(243 244 246 / 0.8);
-  --tw-gradient-to: rgb(243 244 246 / 0);
-  --tw-gradient-stops: var(--tw-gradient-from), var(--tw-gradient-to);
-}
-.via-white {
-  --tw-gradient-to: rgb(255 255 255 / 0);
-  --tw-gradient-stops: var(--tw-gradient-from), #fff, var(--tw-gradient-to);
-}
-.to-white {
-  --tw-gradient-to: #fff;
-}
-.p-3 {
-  padding: 0.75rem;
-}
-.px-5 {
-  padding-left: 1.25rem;
-  padding-right: 1.25rem;
-}
-.py-3 {
-  padding-top: 0.75rem;
-  padding-bottom: 0.75rem;
-}
-.px-2 {
-  padding-left: 0.5rem;
-  padding-right: 0.5rem;
-}
-.pr-8 {
-  padding-right: 2rem;
-}
-.text-left {
-  text-align: left;
-}
-.font-sans {
-  font-family: ui-sans-serif, system-ui, -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji";
-}
-.text-sm {
-  font-size: 0.875rem;
-  line-height: 1.25rem;
-}
-.text-xs {
-  font-size: 0.75rem;
-  line-height: 1rem;
-}
-.font-bold {
-  font-weight: 700;
-}
-.text-gray-700 {
-  --tw-text-opacity: 1;
-  color: rgb(55 65 81 / var(--tw-text-opacity));
-}
-.text-gray-400 {
-  --tw-text-opacity: 1;
-  color: rgb(156 163 175 / var(--tw-text-opacity));
-}
-.text-gray-600 {
-  --tw-text-opacity: 1;
-  color: rgb(75 85 99 / var(--tw-text-opacity));
-}
-.text-gray-800 {
-  --tw-text-opacity: 1;
-  color: rgb(31 41 55 / var(--tw-text-opacity));
-}
-.shadow {
-  --tw-shadow: 0 1px 3px 0 rgb(0 0 0 / 0.1), 0 1px 2px -1px rgb(0 0 0 / 0.1);
-  --tw-shadow-colored: 0 1px 3px 0 var(--tw-shadow-color), 0 1px 2px -1px var(--tw-shadow-color);
-  box-shadow: var(--tw-ring-offset-shadow, 0 0 #0000), var(--tw-ring-shadow, 0 0 #0000), var(--tw-shadow);
-}
-.backdrop-blur-sm {
-  --tw-backdrop-blur: blur(4px);
-  -webkit-backdrop-filter: var(--tw-backdrop-blur) var(--tw-backdrop-brightness) var(--tw-backdrop-contrast) var(--tw-backdrop-grayscale) var(--tw-backdrop-hue-rotate) var(--tw-backdrop-invert) var(--tw-backdrop-opacity) var(--tw-backdrop-saturate) var(--tw-backdrop-sepia);
-          backdrop-filter: var(--tw-backdrop-blur) var(--tw-backdrop-brightness) var(--tw-backdrop-contrast) var(--tw-backdrop-grayscale) var(--tw-backdrop-hue-rotate) var(--tw-backdrop-invert) var(--tw-backdrop-opacity) var(--tw-backdrop-saturate) var(--tw-backdrop-sepia);
-}
-.transition {
-  transition-property: color, background-color, border-color, text-decoration-color, fill, stroke, opacity, box-shadow, transform, filter, -webkit-backdrop-filter;
-  transition-property: color, background-color, border-color, text-decoration-color, fill, stroke, opacity, box-shadow, transform, filter, backdrop-filter;
-  transition-property: color, background-color, border-color, text-decoration-color, fill, stroke, opacity, box-shadow, transform, filter, backdrop-filter, -webkit-backdrop-filter;
-  transition-timing-function: cubic-bezier(0.4, 0, 0.2, 1);
-  transition-duration: 150ms;
-}
-.delay-200 {
-  transition-delay: 200ms;
-}
-.duration-300 {
-  transition-duration: 300ms;
-}
-
-#docsgpt-answer {
-    max-height: 50vh; /* 50% of the viewport height */
-    overflow-y: auto; /* Adds a vertical scrollbar if the content exceeds the container height */
-}
-
-.widget-container {
-  position: fixed;   /* fixed positioning */
-  right: 10px;       /* from the right edge */
-  bottom: 10px;      /* from the bottom edge */
-  z-index: 1000;     /* to ensure it appears on top of other content, if any */
-  display: flex;
-  flex-direction: column;
-  align-items: center;
-}
-
-  @keyframes dotBounce {
-    0%, 80%, 100% {
-      transform: translateY(0);
-    }
-    40% {
-      transform: translateY(-5px);
-    }
-  }
-
-  .dot-animation {
-    display: inline-block;
-    animation: dotBounce 1s infinite ease-in-out;
-  }
-
-  .delay-200 {
-    animation-delay: 200ms;
-  }
-
-  .delay-400 {
-    animation-delay: 400ms;
-  }
-
-  .white-filter {
-    filter: invert(1) brightness(2);
-}
-
-  .hover\:bg-gray-100:hover {
-  --tw-bg-opacity: 1;
-  background-color: rgb(243 244 246 / var(--tw-bg-opacity));
-}
-
-  .hover\:opacity-50:hover {
-  opacity: 0.5;
-}
-
-  .focus\:outline-none:focus {
-  outline: 2px solid transparent;
-  outline-offset: 2px;
-}
-
-  @media (prefers-color-scheme: dark) {
-
-  .dark\:divide-gray-700 > :not([hidden]) ~ :not([hidden]) {
-    --tw-divide-opacity: 1;
-    border-color: rgb(55 65 81 / var(--tw-divide-opacity));
-  }
-
-  .dark\:border-gray-700 {
-    --tw-border-opacity: 1;
-    border-color: rgb(55 65 81 / var(--tw-border-opacity));
-  }
-
-  .dark\:from-gray-900\/80 {
-    --tw-gradient-from: rgb(17 24 39 / 0.8);
-    --tw-gradient-to: rgb(17 24 39 / 0);
-    --tw-gradient-stops: var(--tw-gradient-from), var(--tw-gradient-to);
-  }
-
-  .dark\:via-gray-900 {
-    --tw-gradient-to: rgb(17 24 39 / 0);
-    --tw-gradient-stops: var(--tw-gradient-from), #111827, var(--tw-gradient-to);
-  }
-
-  .dark\:to-gray-900 {
-    --tw-gradient-to: #111827;
-  }
-
-  .dark\:text-gray-200 {
-    --tw-text-opacity: 1;
-    color: rgb(229 231 235 / var(--tw-text-opacity));
-  }
-
-  .dark\:text-gray-500 {
-    --tw-text-opacity: 1;
-    color: rgb(107 114 128 / var(--tw-text-opacity));
-  }
-
-  .dark\:text-white {
-    --tw-text-opacity: 1;
-    color: rgb(255 255 255 / var(--tw-text-opacity));
-  }
-
-  .dark\:hover\:bg-gray-800\/70:hover {
-    background-color: rgb(31 41 55 / 0.7);
-  }
-}

extensions/react-widget/dist/vite.svg

@@ -1 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" class="iconify iconify--logos" width="31.88" height="32" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 257"><defs><linearGradient id="IconifyId1813088fe1fbc01fb466" x1="-.828%" x2="57.636%" y1="7.652%" y2="78.411%"><stop offset="0%" stop-color="#41D1FF"></stop><stop offset="100%" stop-color="#BD34FE"></stop></linearGradient><linearGradient id="IconifyId1813088fe1fbc01fb467" x1="43.376%" x2="50.316%" y1="2.242%" y2="89.03%"><stop offset="0%" stop-color="#FFEA83"></stop><stop offset="8.333%" stop-color="#FFDD35"></stop><stop offset="100%" stop-color="#FFA800"></stop></linearGradient></defs><path fill="url(#IconifyId1813088fe1fbc01fb466)" d="M255.153 37.938L134.897 252.976c-2.483 4.44-8.862 4.466-11.382.048L.875 37.958c-2.746-4.814 1.371-10.646 6.827-9.67l120.385 21.517a6.537 6.537 0 0 0 2.322-.004l117.867-21.483c5.438-.991 9.574 4.796 6.877 9.62Z"></path><path fill="url(#IconifyId1813088fe1fbc01fb467)" d="M185.432.063L96.44 17.501a3.268 3.268 0 0 0-2.634 3.014l-5.474 92.456a3.268 3.268 0 0 0 3.997 3.378l24.777-5.718c2.318-.535 4.413 1.507 3.936 3.838l-7.361 36.047c-.495 2.426 1.782 4.5 4.151 3.78l15.304-4.649c2.372-.72 4.652 1.36 4.15 3.788l-11.698 56.621c-.732 3.542 3.979 5.473 5.943 2.437l1.313-2.028l72.516-144.72c1.215-2.423-.88-5.186-3.54-4.672l-25.505 4.922c-2.396.462-4.435-1.77-3.759-4.114l16.646-57.705c.677-2.35-1.37-4.583-3.769-4.113Z"></path></svg>

extensions/react-widget/index.ts

@@ -1 +0,0 @@
-export { DocsGPTWidget } from "./src/components/DocsGPTWidget";

extensions/react-widget/package.json

@@ -1,47 +1,65 @@
 {
   "name": "docsgpt",
+  "version": "0.3.7",
   "private": false,
-  "version": "0.2.4",
-  "type": "module",
-  "main": "dist/index.umd.js",
-  "module": "dist/index.es.js",
-  "types": "dist/index.d.ts",
-  "exports": {
-    ".": {
-      "import": "./dist/index.es.js",
-      "require": "./dist/index.umd.js",
-      "types": "./dist/index.d.ts"
-    },
-    "./dist/style.css": "./dist/style.css"
-  },
+  "description": "DocsGPT 🦖 is an innovative open-source tool designed to simplify the retrieval of information from project documentation using advanced GPT models 🤖.",
+  "source": "./src/index.html",
+  "main": "dist/main.js",
+  "module": "dist/module.js",
+  "types": "dist/types.d.ts",
   "files": [
-    "/dist"
+    "dist",
+    "package.json"
   ],
-  "publishConfig": {
-    "access": "public"
+  "@parcel/resolver-default": {
+    "packageExports": true
+  },
+  "resolution": {
+    "styled-components": "^5"
   },
   "scripts": {
-    "dev": "vite",
-    "build": "tsc && vite build",
-    "prepare": "npm run build && npm run build-css",
-    "build-css": "postcss src/index.css -o dist/style.css",
-    "preview": "vite preview"
+    "build": "parcel build src/index.ts",
+    "dev": "parcel src/index.html -p 3000",
+    "test": "jest",
+    "lint": "eslint",
+    "check": "tsc --noEmit",
+    "ci": "yarn build && yarn test && yarn lint && yarn check"
   },
   "dependencies": {
-    "postcss-cli": "^10.1.0",
+    "@babel/plugin-transform-flow-strip-types": "^7.23.3",
+    "@bpmn-io/snarkdown": "^2.2.0",
+    "@parcel/resolver-glob": "^2.12.0",
+    "@parcel/transformer-svg-react": "^2.12.0",
+    "@parcel/transformer-typescript-tsc": "^2.12.0",
+    "@parcel/validator-typescript": "^2.12.0",
+    "@radix-ui/react-icons": "^1.3.0",
+    "@types/react": "^18.2.61",
+    "@types/react-dom": "^18.2.19",
+    "class-variance-authority": "^0.7.0",
+    "clsx": "^2.1.0",
+    "dompurify": "^3.0.9",
+    "flow-bin": "^0.229.2",
+    "i": "^0.3.7",
+    "install": "^0.13.0",
+    "npm": "^10.5.0",
+    "parcel": "^2.12.0",
     "react": "^18.2.0",
     "react-dom": "^18.2.0",
-    "tailwindcss": "^3.2.4"
+    "styled-components": "^6.1.8"
   },
   "devDependencies": {
-    "@types/react": "^18.0.26",
-    "@types/react-dom": "^18.0.9",
-    "@vitejs/plugin-react-swc": "^3.5.0",
-    "autoprefixer": "^10.4.13",
-    "postcss": "^8.4.31",
-    "typescript": "^4.9.3",
-    "vite": "^5.0.12",
-    "vite-plugin-dts": "^3.7.0"
+    "@babel/core": "^7.24.0",
+    "@babel/preset-env": "^7.24.0",
+    "@babel/preset-react": "^7.23.3",
+    "@parcel/packager-ts": "^2.12.0",
+    "@parcel/transformer-typescript-types": "^2.12.0",
+    "@types/dompurify": "^3.0.5",
+    "babel-loader": "^8.0.4",
+    "process": "^0.11.10",
+    "typescript": "^5.3.3"
+  },
+  "publishConfig": {
+    "access": "public"
   },
   "repository": {
     "type": "git",

extensions/react-widget/postcss.config.cjs

@@ -1,6 +0,0 @@
-module.exports = {
-  plugins: {
-    tailwindcss: {},
-    autoprefixer: {},
-  },
-}

extensions/react-widget/public/vite.svg

@@ -1 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" class="iconify iconify--logos" width="31.88" height="32" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 257"><defs><linearGradient id="IconifyId1813088fe1fbc01fb466" x1="-.828%" x2="57.636%" y1="7.652%" y2="78.411%"><stop offset="0%" stop-color="#41D1FF"></stop><stop offset="100%" stop-color="#BD34FE"></stop></linearGradient><linearGradient id="IconifyId1813088fe1fbc01fb467" x1="43.376%" x2="50.316%" y1="2.242%" y2="89.03%"><stop offset="0%" stop-color="#FFEA83"></stop><stop offset="8.333%" stop-color="#FFDD35"></stop><stop offset="100%" stop-color="#FFA800"></stop></linearGradient></defs><path fill="url(#IconifyId1813088fe1fbc01fb466)" d="M255.153 37.938L134.897 252.976c-2.483 4.44-8.862 4.466-11.382.048L.875 37.958c-2.746-4.814 1.371-10.646 6.827-9.67l120.385 21.517a6.537 6.537 0 0 0 2.322-.004l117.867-21.483c5.438-.991 9.574 4.796 6.877 9.62Z"></path><path fill="url(#IconifyId1813088fe1fbc01fb467)" d="M185.432.063L96.44 17.501a3.268 3.268 0 0 0-2.634 3.014l-5.474 92.456a3.268 3.268 0 0 0 3.997 3.378l24.777-5.718c2.318-.535 4.413 1.507 3.936 3.838l-7.361 36.047c-.495 2.426 1.782 4.5 4.151 3.78l15.304-4.649c2.372-.72 4.652 1.36 4.15 3.788l-11.698 56.621c-.732 3.542 3.979 5.473 5.943 2.437l1.313-2.028l72.516-144.72c1.215-2.423-.88-5.186-3.54-4.672l-25.505 4.922c-2.396.462-4.435-1.77-3.759-4.114l16.646-57.705c.677-2.35-1.37-4.583-3.769-4.113Z"></path></svg>

extensions/react-widget/src/App.css

@@ -1,5 +0,0 @@
-
-
-
-
-

extensions/react-widget/src/App.tsx

@@ -1,15 +1,11 @@
-import { useState } from "react";
-//import "./App.css";
-import {DocsGPTWidget} from "./components/DocsGPTWidget";
-
-function App() {
-  const [count, setCount] = useState(0);
-
+import React from "react"
+import {DocsGPTWidget} from "./components/DocsGPTWidget"
+const App = () => {
   return (
-    <div className="App">
-      <DocsGPTWidget />
+    <div>
+      <DocsGPTWidget/>
     </div>
-  );
+  )
 }
 
-export default App;
+export default App

extensions/react-widget/src/assets/message.svg

@@ -0,0 +1,7 @@
+<svg width="36" height="36" viewBox="0 0 18 18" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path d="M4.37891 9.44824H7.75821" stroke="white" stroke-width="1.68965" stroke-linecap="round" stroke-linejoin="round"/>
+<path d="M11.1377 9.44824H12.8273" stroke="white" stroke-width="1.68965" stroke-linecap="round" stroke-linejoin="round"/>
+<path d="M4.37891 6.06934H6.06856" stroke="white" stroke-width="1.68965" stroke-linecap="round" stroke-linejoin="round"/>
+<path d="M9.44824 6.06934H12.8276" stroke="white" stroke-width="1.68965" stroke-linecap="round" stroke-linejoin="round"/>
+<path d="M16.2069 11.1379C16.2069 11.5861 16.0289 12.0158 15.712 12.3327C15.3951 12.6496 14.9654 12.8276 14.5172 12.8276H4.37931L1 16.2069V2.68965C1 2.24153 1.17802 1.81176 1.49489 1.49489C1.81176 1.17802 2.24153 1 2.68965 1H14.5172C14.9654 1 15.3951 1.17802 15.712 1.49489C16.0289 1.81176 16.2069 2.24153 16.2069 2.68965V11.1379Z" stroke="white" stroke-width="1.68965" stroke-linecap="round" stroke-linejoin="round"/>
+</svg>

extensions/react-widget/src/assets/react.svg

@@ -1 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" class="iconify iconify--logos" width="35.93" height="32" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 228"><path fill="#00D8FF" d="M210.483 73.824a171.49 171.49 0 0 0-8.24-2.597c.465-1.9.893-3.777 1.273-5.621c6.238-30.281 2.16-54.676-11.769-62.708c-13.355-7.7-35.196.329-57.254 19.526a171.23 171.23 0 0 0-6.375 5.848a155.866 155.866 0 0 0-4.241-3.917C100.759 3.829 77.587-4.822 63.673 3.233C50.33 10.957 46.379 33.89 51.995 62.588a170.974 170.974 0 0 0 1.892 8.48c-3.28.932-6.445 1.924-9.474 2.98C17.309 83.498 0 98.307 0 113.668c0 15.865 18.582 31.778 46.812 41.427a145.52 145.52 0 0 0 6.921 2.165a167.467 167.467 0 0 0-2.01 9.138c-5.354 28.2-1.173 50.591 12.134 58.266c13.744 7.926 36.812-.22 59.273-19.855a145.567 145.567 0 0 0 5.342-4.923a168.064 168.064 0 0 0 6.92 6.314c21.758 18.722 43.246 26.282 56.54 18.586c13.731-7.949 18.194-32.003 12.4-61.268a145.016 145.016 0 0 0-1.535-6.842c1.62-.48 3.21-.974 4.76-1.488c29.348-9.723 48.443-25.443 48.443-41.52c0-15.417-17.868-30.326-45.517-39.844Zm-6.365 70.984c-1.4.463-2.836.91-4.3 1.345c-3.24-10.257-7.612-21.163-12.963-32.432c5.106-11 9.31-21.767 12.459-31.957c2.619.758 5.16 1.557 7.61 2.4c23.69 8.156 38.14 20.213 38.14 29.504c0 9.896-15.606 22.743-40.946 31.14Zm-10.514 20.834c2.562 12.94 2.927 24.64 1.23 33.787c-1.524 8.219-4.59 13.698-8.382 15.893c-8.067 4.67-25.32-1.4-43.927-17.412a156.726 156.726 0 0 1-6.437-5.87c7.214-7.889 14.423-17.06 21.459-27.246c12.376-1.098 24.068-2.894 34.671-5.345a134.17 134.17 0 0 1 1.386 6.193ZM87.276 214.515c-7.882 2.783-14.16 2.863-17.955.675c-8.075-4.657-11.432-22.636-6.853-46.752a156.923 156.923 0 0 1 1.869-8.499c10.486 2.32 22.093 3.988 34.498 4.994c7.084 9.967 14.501 19.128 21.976 27.15a134.668 134.668 0 0 1-4.877 4.492c-9.933 8.682-19.886 14.842-28.658 17.94ZM50.35 144.747c-12.483-4.267-22.792-9.812-29.858-15.863c-6.35-5.437-9.555-10.836-9.555-15.216c0-9.322 13.897-21.212 37.076-29.293c2.813-.98 5.757-1.905 8.812-2.773c3.204 10.42 7.406 21.315 12.477 32.332c-5.137 11.18-9.399 22.249-12.634 32.792a134.718 134.718 0 0 1-6.318-1.979Zm12.378-84.26c-4.811-24.587-1.616-43.134 6.425-47.789c8.564-4.958 27.502 2.111 47.463 19.835a144.318 144.318 0 0 1 3.841 3.545c-7.438 7.987-14.787 17.08-21.808 26.988c-12.04 1.116-23.565 2.908-34.161 5.309a160.342 160.342 0 0 1-1.76-7.887Zm110.427 27.268a347.8 347.8 0 0 0-7.785-12.803c8.168 1.033 15.994 2.404 23.343 4.08c-2.206 7.072-4.956 14.465-8.193 22.045a381.151 381.151 0 0 0-7.365-13.322Zm-45.032-43.861c5.044 5.465 10.096 11.566 15.065 18.186a322.04 322.04 0 0 0-30.257-.006c4.974-6.559 10.069-12.652 15.192-18.18ZM82.802 87.83a323.167 323.167 0 0 0-7.227 13.238c-3.184-7.553-5.909-14.98-8.134-22.152c7.304-1.634 15.093-2.97 23.209-3.984a321.524 321.524 0 0 0-7.848 12.897Zm8.081 65.352c-8.385-.936-16.291-2.203-23.593-3.793c2.26-7.3 5.045-14.885 8.298-22.6a321.187 321.187 0 0 0 7.257 13.246c2.594 4.48 5.28 8.868 8.038 13.147Zm37.542 31.03c-5.184-5.592-10.354-11.779-15.403-18.433c4.902.192 9.899.29 14.978.29c5.218 0 10.376-.117 15.453-.343c-4.985 6.774-10.018 12.97-15.028 18.486Zm52.198-57.817c3.422 7.8 6.306 15.345 8.596 22.52c-7.422 1.694-15.436 3.058-23.88 4.071a382.417 382.417 0 0 0 7.859-13.026a347.403 347.403 0 0 0 7.425-13.565Zm-16.898 8.101a358.557 358.557 0 0 1-12.281 19.815a329.4 329.4 0 0 1-23.444.823c-7.967 0-15.716-.248-23.178-.732a310.202 310.202 0 0 1-12.513-19.846h.001a307.41 307.41 0 0 1-10.923-20.627a310.278 310.278 0 0 1 10.89-20.637l-.001.001a307.318 307.318 0 0 1 12.413-19.761c7.613-.576 15.42-.876 23.31-.876H128c7.926 0 15.743.303 23.354.883a329.357 329.357 0 0 1 12.335 19.695a358.489 358.489 0 0 1 11.036 20.54a329.472 329.472 0 0 1-11 20.722Zm22.56-122.124c8.572 4.944 11.906 24.881 6.52 51.026c-.344 1.668-.73 3.367-1.15 5.09c-10.622-2.452-22.155-4.275-34.23-5.408c-7.034-10.017-14.323-19.124-21.64-27.008a160.789 160.789 0 0 1 5.888-5.4c18.9-16.447 36.564-22.941 44.612-18.3ZM128 90.808c12.625 0 22.86 10.235 22.86 22.86s-10.235 22.86-22.86 22.86s-22.86-10.235-22.86-22.86s10.235-22.86 22.86-22.86Z"></path></svg>

extensions/react-widget/src/components/DocsGPTWidget.tsx

@@ -1,247 +1,459 @@
 "use client";
-import {useEffect, useRef, useState} from 'react'
-//import './style.css'
-
-interface HistoryItem {
-  prompt: string;
-  response: string;
+import { Fragment, useEffect, useRef, useState } from 'react'
+import { PaperPlaneIcon, RocketIcon, ExclamationTriangleIcon, Cross2Icon } from '@radix-ui/react-icons';
+import { MESSAGE_TYPE, Query, Status } from '../types/index';
+import MessageIcon from '../assets/message.svg'
+import { fetchAnswerStreaming } from '../requests/streamingApi';
+import styled, { keyframes, createGlobalStyle } from 'styled-components';
+import snarkdown from '@bpmn-io/snarkdown';
+import { sanitize } from 'dompurify';
+const GlobalStyles = createGlobalStyle`
+.response pre {
+    padding: 8px;
+    width: 90%;
+    font-size: 12px;
+    border-radius: 6px;
+    overflow-x: auto;
+    background-color: #1B1C1F;
 }
-
-interface FetchAnswerStreamingProps {
-  question?: string;
-  apiKey?: string;
-  selectedDocs?: string;
-  history?: HistoryItem[];
-  conversationId?: string | null;
-  apiHost?: string;
-  onEvent?: (event: MessageEvent) => void;
+.response h1{
+  font-size: 20px;
 }
-
-
-enum ChatStates {
-  Init = 'init',
-  Processing = 'processing',
-  Typing = 'typing',
-  Answer = 'answer',
-  Minimized = 'minimized',
+.response h2{
+  font-size: 18px;
 }
-
-function fetchAnswerStreaming({
-  question = '',
-  apiKey = '',
-  selectedDocs = '',
-  history = [],
-  conversationId = null,
-  apiHost = '',
-  onEvent = () => {console.log("Event triggered, but no handler provided.");}
-}: FetchAnswerStreamingProps): Promise<void> {
-  let docPath = 'default';
-  if (selectedDocs) {
-    docPath = selectedDocs;
-  }
-
-  return new Promise<void>((resolve, reject) => {
-    const body = {
-      question: question,
-      api_key: apiKey,
-      embeddings_key: apiKey,
-      active_docs: docPath,
-      history: JSON.stringify(history),
-      conversation_id: conversationId,
-      model: 'default'
-    };
-
-    fetch(apiHost + '/stream', {
-      method: 'POST',
-      headers: {
-        'Content-Type': 'application/json',
-      },
-      body: JSON.stringify(body),
-    })
-      .then((response) => {
-        if (!response.body) throw Error('No response body');
-
-        const reader = response.body.getReader();
-        const decoder = new TextDecoder('utf-8');
-        let counterrr = 0;
-        const processStream = ({
-          done,
-          value,
-        }: ReadableStreamReadResult<Uint8Array>) => {
-          if (done) {
-            console.log(counterrr);
-            resolve();
-            return;
-          }
-
-          counterrr += 1;
-
-          const chunk = decoder.decode(value);
-
-          const lines = chunk.split('\n');
-
-          for (let line of lines) {
-            if (line.trim() == '') {
-              continue;
-            }
-            if (line.startsWith('data:')) {
-              line = line.substring(5);
-            }
-
-            const messageEvent = new MessageEvent('message', {
-              data: line,
-            });
-
-            onEvent(messageEvent); // handle each message
-          }
-
-          reader.read().then(processStream).catch(reject);
-        };
-
-        reader.read().then(processStream).catch(reject);
-      })
-      .catch((error) => {
-        console.error('Connection failed:', error);
-        reject(error);
-      });
-  });
+.response h3{
+  font-size: 16px;
 }
-
-export const DocsGPTWidget = ({ apiHost = 'https://gptcloud.arc53.com', selectDocs = 'default', apiKey = 'docsgpt-public'}) => {
-    // processing states
-    const [chatState, setChatState] = useState<ChatStates>(() => {
-        if (typeof window !== 'undefined') {
-            return localStorage.getItem('docsGPTChatState') as ChatStates || ChatStates.Init;
-        }
-        return ChatStates.Init;
-    });
-
-    const [answer, setAnswer] = useState<string>('');
-
-    //const selectDocs = 'local/1706.03762.pdf/'
-    const answerRef = useRef<HTMLDivElement | null>(null);
-
-    useEffect(() => {
-        if (answerRef.current) {
-            const element = answerRef.current;
-            element.scrollTop = element.scrollHeight;
-        }
-    }, [answer]);
-
-    useEffect(() => {
-        localStorage.setItem('docsGPTChatState', chatState);
-    }, [chatState]);
-
-
-
-    // submit handler
-    const handleSubmit = (e: React.FormEvent<HTMLFormElement>) => {
-        setAnswer('')
-        e.preventDefault()
-        // get question
-        setChatState(ChatStates.Processing)
-        setTimeout(() => {
-            setChatState(ChatStates.Answer)
-        }, 800)
-        const inputElement = e.currentTarget[0] as HTMLInputElement;
-        const questionValue = inputElement.value;
-
-        fetchAnswerStreaming({
-          question: questionValue,
-          apiKey: apiKey,
-          selectedDocs: selectDocs,
-          history: [],
-          conversationId: null,
-          apiHost: apiHost,
-          onEvent: (event) => {
-            const data = JSON.parse(event.data);
-
-            // check if the 'end' event has been received
-            if (data.type === 'end') {
-              setChatState(ChatStates.Answer)
-            } else if (data.type === 'source') {
-              // check if data.metadata exists
-              let result;
-              if (data.metadata && data.metadata.title) {
-                const titleParts = data.metadata.title.split('/');
-                result = {
-                  title: titleParts[titleParts.length - 1],
-                  text: data.doc,
-                };
-              } else {
-                result = { title: data.doc, text: data.doc };
-              }
-              console.log(result)
-
-            } else if (data.type === 'id') {
-              console.log(data.id);
-            } else {
-              const result = data.answer;
-              // set answer by appending answer
-                setAnswer(prevAnswer => prevAnswer + result);
-            }
-          },
-      });
+.response code:not(pre code){
+  border-radius: 6px;
+  padding: 1px 3px 1px 3px;
+  font-size: 12px;
+  display: inline-block;
+  background-color: #646464;
+}
+`;
+const WidgetContainer = styled.div`
+    display: block;
+    position: fixed;
+    right: 10px;
+    bottom: 10px;
+    z-index: 1000;
+    display: flex;
+    flex-direction: column;
+    align-items: center;
+    text-align: left;
+`;
+const StyledContainer = styled.div`
+    display: block;
+    position: relative;
+    bottom: 0;
+    left: 0;
+    width: 352px;
+    height: 407px;
+    max-height: 407px;
+    border-radius: 0.75rem;
+    background-color: #222327;
+    font-family: sans-serif;
+    box-shadow: 0 1px 2px rgba(0, 0, 0, 0.05), 0 2px 4px rgba(0, 0, 0, 0.1);
+    transition: visibility 0.3s, opacity 0.3s;
+`;
+const FloatingButton = styled.div`
+    position: fixed;
+    display: flex;
+    z-index: 500;
+    justify-content: center;
+    align-items: center;
+    bottom: 1rem;
+    right: 1rem;
+    width: 5rem;
+    height: 5rem;
+    border-radius: 9999px;
+    background-image: linear-gradient(to bottom right, #5AF0EC, #E80D9D);
+    box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
+    cursor: pointer;
+    &:hover {
+        transform: scale(1.1);
+        transition: transform 0.2s ease-in-out;
     }
+`;
+const CancelButton = styled.button`
+    cursor: pointer;
+    position: absolute;
+    top: 0;
+    right: 0;
+    margin: 0.5rem;
+    width: 30px;
+    padding: 0;
+    background-color: transparent;
+    border: none;
+    outline: none;
+    color: inherit;
+    transition: opacity 0.3s ease;
+    opacity: 0.6;
+    &:hover {
+        opacity: 1;
+    }
+    .white-filter {
+        filter: invert(100%);
+    }
+`;
 
+const Header = styled.div`
+    display: flex;
+    align-items: center;
+    padding-inline: 0.75rem;
+    padding-top: 1rem;
+    padding-bottom: 0.5rem;
+`;
+
+const IconWrapper = styled.div`
+    padding: 0.5rem;
+`;
+
+const ContentWrapper = styled.div`
+    flex: 1;
+    margin-left: 0.5rem;
+`;
+
+const Title = styled.h3`
+    font-size: 1rem;
+    font-weight: normal;
+    color: #FAFAFA;
+    margin-top: 0;
+    margin-bottom: 0.25rem;
+`;
+
+const Description = styled.p`
+    font-size: 0.85rem;
+    color: #A1A1AA;
+    margin-top: 0;
+`;
+const Conversation = styled.div`
+    height: 16rem;
+    padding-inline: 0.5rem;
+    border-radius: 0.375rem;
+    text-align: left;
+    overflow-y: auto;
+    scrollbar-width: thin;
+    scrollbar-color: #4a4a4a transparent; /* thumb color track color */
+`;
+
+const MessageBubble = styled.div<{ type: MESSAGE_TYPE }>`
+    display: flex;
+    font-size: 16px;
+    justify-content: ${props => props.type === 'QUESTION' ? 'flex-end' : 'flex-start'};
+    margin: 0.5rem;
+`;
+const Message = styled.p<{ type: MESSAGE_TYPE }>`
+    background: ${props => props.type === 'QUESTION' ?
+    'linear-gradient(to bottom right, #8860DB, #6D42C5)' :
+    '#38383b'};
+    color: #ffff;
+    border: none;
+    max-width: 80%;
+    overflow: auto;
+    margin: 4px;
+    display: block;
+    line-height: 1.5;
+    padding: 0.75rem;
+    border-radius: 0.375rem;
+`;
+const ErrorAlert = styled.div`
+  color: #b91c1c;
+  border:0.1px solid #b91c1c;
+  display: flex;
+  padding:4px;
+  margin:0.7rem;
+  opacity: 90%;
+  max-width: 70%;
+  font-weight: 400;
+  border-radius: 0.375rem;
+  justify-content: space-evenly;
+`
+//dot loading animation
+const dotBounce = keyframes`
+  0%, 80%, 100% {
+    transform: translateY(0);
+  }
+  40% {
+    transform: translateY(-5px);
+  }
+`;
+
+const DotAnimation = styled.div`
+  display: inline-block;
+  animation: ${dotBounce} 1s infinite ease-in-out;
+`;
+// delay classes as styled components
+const Delay = styled(DotAnimation) <{ delay: number }>`
+  animation-delay: ${props => props.delay + 'ms'};
+`;
+const PromptContainer = styled.form`
+  background-color: transparent;
+  height: 36px;
+  position: absolute;
+  bottom: 25px;
+  left: 24px;
+  right: 24px;
+  display: flex;
+  justify-content: space-evenly;
+`;
+const StyledInput = styled.input`
+  width: 260px;
+  height: 36px;
+  border: 1px solid #686877;
+  padding-left: 12px;
+  background-color: transparent;
+  font-size: 16px;
+  border-radius: 6px;
+  color: #ffff;
+  outline: none;
+`;
+const StyledButton = styled.button`
+  display: flex;
+  justify-content: center;
+  align-items: center;
+  background-image: linear-gradient(to bottom right, #5AF0EC, #E80D9D);
+  border-radius: 6px;
+  width: 36px;
+  height: 36px;
+  margin-left:8px;
+  padding: 0px;
+  border: none;
+  cursor: pointer;
+  outline: none;
+  &:hover{
+    opacity: 90%;
+  }
+  &:disabled {
+    opacity: 60%;
+  }`;
+const HeroContainer = styled.div`
+  position: absolute;
+  top: 50%;
+  left: 50%;
+  display: flex;
+  justify-content: center;
+  align-items: middle;
+  transform: translate(-50%, -50%);
+  width: 80%;
+  background-image: linear-gradient(to bottom right, #5AF0EC, #ff1bf4);
+  border-radius: 10px;
+  margin: 0 auto;
+  padding: 2px;
+`;
+const HeroWrapper = styled.div`
+  background-color: #222327;
+  border-radius: 10px; 
+  font-weight: normal;
+  padding: 6px;
+  display: flex;
+  justify-content: space-between;
+`
+const HeroTitle = styled.h3`
+  color: #fff;
+  font-size: 17px;
+  margin-bottom: 5px;
+  padding: 2px;
+`;
+const HeroDescription = styled.p`
+  color: #fff;
+  font-size: 14px;
+  line-height: 1.5;
+`;
+const Hero = ({ title, description }: { title: string, description: string }) => {
   return (
     <>
-        <div className="dark widget-container">
-            <div onClick={() => setChatState(ChatStates.Init)}
-                 className={`${chatState !== 'minimized' ? 'hidden' : ''} cursor-pointer`}>
-               <div className="mr-2 mb-2 w-20 h-20 rounded-full overflow-hidden dark:divide-gray-700 border dark:border-gray-700 bg-gradient-to-br from-gray-100/80 via-white to-white dark:from-gray-900/80 dark:via-gray-900 dark:to-gray-900 font-sans shadow backdrop-blur-sm flex items-center justify-center">
-                        <img
-                            src="https://d3dg1063dc54p9.cloudfront.net/cute-docsgpt.png"
-                            alt="DocsGPT"
-                            className="cursor-pointer hover:opacity-50 h-14"
-                        />
-                    </div>
-            </div>
-      <div className={` ${chatState !== 'minimized' ? '' : 'hidden'} divide-y dark:divide-gray-700 rounded-md border dark:border-gray-700 bg-gradient-to-br from-gray-100/80 via-white to-white dark:from-gray-900/80 dark:via-gray-900 dark:to-gray-900 font-sans shadow backdrop-blur-sm`} style={{ width: '18rem', transform: 'translateY(0%) translateZ(0px)' }}>
-        <div>
-          <img
-                        src="https://d3dg1063dc54p9.cloudfront.net/exit.svg"
-                        alt="Exit"
-                        className="cursor-pointer hover:opacity-50 h-2 absolute top-0 right-0 m-2 white-filter"
-                        onClick={(event) => {
-                          event.stopPropagation();
-                          setChatState(ChatStates.Minimized);
-                        }}
-                      />
-          <div className="flex items-center gap-2 p-3">
-            <div  className={`${chatState === 'init' ? '' :
-                                chatState === 'processing' ? '' : 
-                                chatState === 'typing' ? '' :     
-                               'hidden'} flex-1`}>
-              <h3 className="text-sm font-bold text-gray-700 dark:text-gray-200">Need help with documentation?</h3>
-              <p className="mt-1 text-xs text-gray-400 dark:text-gray-500">DocsGPT AI assistant will help you with docs</p>
-            </div>
-            <div id="docsgpt-answer" ref={answerRef} className={`${chatState !== 'answer' ? 'hidden' : ''}`}>
-                <p className="mt-1 text-sm text-gray-600 dark:text-white text-left">{answer}</p>
-            </div>
+      <HeroContainer>
+        <HeroWrapper>
+          <IconWrapper style={{ marginTop: '8px' }}>
+            <RocketIcon color='white' width={20} height={20} />
+          </IconWrapper>
+          <div>
+            <HeroTitle>{title}</HeroTitle>
+            <HeroDescription>
+              {description}
+            </HeroDescription>
           </div>
-        </div>
-        <div className="w-full">
-          <button onClick={() => setChatState(ChatStates.Typing)}
-                  className={`flex w-full justify-center px-5 py-3 text-sm text-gray-800 font-bold dark:text-white transition duration-300 hover:bg-gray-100 rounded-b dark:hover:bg-gray-800/70 ${chatState !== 'init' ? 'hidden' : ''}`}>
-            Ask DocsGPT
-          </button>
-         { (chatState === 'typing' || chatState === 'answer') && (
-            <form
-                onSubmit={handleSubmit}
-                className="relative w-full m-0" style={{ opacity: 1 }}>
-              <input type="text"
-                     className="w-full bg-transparent px-5 py-3 pr-8 text-sm text-gray-700 dark:text-white focus:outline-none" placeholder="What do you want to do?" />
-              <button className="absolute text-gray-400 dark:text-gray-500 text-sm inset-y-0 right-2 -mx-2 px-2" type="submit" >Submit</button>
-            </form>
-          )}
-          <p className={`${chatState !== 'processing' ? 'hidden' : ''} flex w-full justify-center px-5 py-3 text-sm text-gray-800 font-bold dark:text-white transition duration-300 rounded-b`}>
-            Processing<span className="dot-animation">.</span><span className="dot-animation delay-200">.</span><span className="dot-animation delay-400">.</span>
-          </p>
-        </div>
-      </div>
-    </div>
+        </HeroWrapper>
+      </HeroContainer>
+    </>
+  );
+};
+export const DocsGPTWidget = ({
+  apiHost = 'https://gptcloud.arc53.com',
+  selectDocs = 'default',
+  apiKey = '82962c9a-aa77-4152-94e5-a4f84fd44c6a',
+  avatar = 'https://d3dg1063dc54p9.cloudfront.net/cute-docsgpt.png',
+  title = 'Get AI assistance',
+  description = 'DocsGPT\'s AI Chatbot is here to help',
+  heroTitle = 'Welcome to DocsGPT !',
+  heroDescription = 'This chatbot is built with DocsGPT and utilises GenAI, please review important information using sources.'
+}) => {
 
+  const [prompt, setPrompt] = useState('');
+  const [status, setStatus] = useState<Status>('idle');
+  const [queries, setQueries] = useState<Query[]>([])
+  const [conversationId, setConversationId] = useState<string | null>(null)
+  const [open, setOpen] = useState<boolean>(false)
+  const [eventInterrupt, setEventInterrupt] = useState<boolean>(false); //click or scroll by user while autoScrolling
+  const endMessageRef = useRef<HTMLDivElement | null>(null);
+  const handleUserInterrupt = () => {
+    (status === 'loading') && setEventInterrupt(true);
+  }
+  const scrollToBottom = (element: Element | null) => {
+    //recursive function to scroll to the last child of the last child ...
+    // to get to the bottom most element
+    if (!element) return;
+    if (element?.children.length === 0) {
+      element?.scrollIntoView({
+        behavior: 'smooth',
+        block: 'start',
+      });
+    }
+    const lastChild = element?.children?.[element.children.length - 1]
+    lastChild && scrollToBottom(lastChild)
+  };
+
+  useEffect(() => {
+    !eventInterrupt && scrollToBottom(endMessageRef.current);
+  }, [queries.length, queries[queries.length - 1]?.response]);
+
+  async function stream(question: string) {
+    setStatus('loading')
+    try {
+      await fetchAnswerStreaming(
+        {
+          question: question,
+          apiKey: apiKey,
+          apiHost: apiHost,
+          selectedDocs: selectDocs,
+          history: queries,
+          conversationId: conversationId,
+          onEvent: (event: MessageEvent) => {
+            const data = JSON.parse(event.data);
+            // check if the 'end' event has been received
+            if (data.type === 'end') {
+              // set status to 'idle'
+              setStatus('idle');
+
+            } else if (data.type === 'id') {
+              setConversationId(data.id)
+            } else {
+              const result = data.answer;
+              const streamingResponse = queries[queries.length - 1].response ? queries[queries.length - 1].response : '';
+              const updatedQueries = [...queries];
+              updatedQueries[updatedQueries.length - 1].response = streamingResponse + result;
+              setQueries(updatedQueries);
+            }
+          }
+        }
+      );
+    } catch (error) {
+      const updatedQueries = [...queries];
+      updatedQueries[updatedQueries.length - 1].error = 'error'
+      setQueries(updatedQueries);
+      setStatus('idle')
+      //setEventInterrupt(false)
+    }
+
+  }
+  // submit handler
+  const handleSubmit = async (e: React.FormEvent<HTMLFormElement>) => {
+    e.preventDefault()
+    setEventInterrupt(false);
+    queries.push({ prompt })
+    setPrompt('')
+    await stream(prompt)
+  }
+  const handleImageError = (event: React.SyntheticEvent<HTMLImageElement, Event>) => {
+    event.currentTarget.src = "https://d3dg1063dc54p9.cloudfront.net/cute-docsgpt.png";
+  };
+  return (
+    <>
+      <WidgetContainer>
+        <GlobalStyles />
+        {!open && <FloatingButton onClick={() => setOpen(true)} hidden={open}>
+          <MessageIcon style={{ marginTop: '8px' }} />
+        </FloatingButton>}
+        {open && <StyledContainer>
+          <div>
+            <CancelButton onClick={() => setOpen(false)}>
+              <Cross2Icon width={24} height={24} color='white' />
+            </CancelButton>
+            <Header>
+              <IconWrapper>
+                <img style={{ maxWidth: "42px", maxHeight: "42px" }} onError={handleImageError} src={avatar} alt='docs-gpt' />
+              </IconWrapper>
+              <ContentWrapper>
+                <Title>{title}</Title>
+                <Description>{description}</Description>
+              </ContentWrapper>
+            </Header>
+          </div>
+          <Conversation onWheel={handleUserInterrupt} onTouchMove={handleUserInterrupt}>
+            {
+              queries.length > 0 ? queries?.map((query, index) => {
+                return (
+                  <Fragment key={index}>
+                    {
+                      query.prompt && <MessageBubble type='QUESTION'>
+                        <Message
+                          type='QUESTION'
+                          ref={(!(query.response || query.error) && index === queries.length - 1) ? endMessageRef : null}>
+                          {query.prompt}
+                        </Message>
+                      </MessageBubble>
+                    }
+                    {
+                      query.response ? <MessageBubble type='ANSWER'>
+                        <Message
+                          type='ANSWER'
+                          ref={(index === queries.length - 1) ? endMessageRef : null}
+                        >
+                          <div className="response" dangerouslySetInnerHTML={{ __html: sanitize(snarkdown(query.response)) }} />
+                        </Message>
+                      </MessageBubble>
+                        : <div>
+                          {
+                            query.error ? <ErrorAlert>
+                              <IconWrapper>
+                                <ExclamationTriangleIcon style={{ marginTop: '4px' }} width={22} height={22} color='#b91c1c' />
+                              </IconWrapper>
+                              <div>
+                                <h5 style={{ margin: 2 }}>Network Error</h5>
+                                <span style={{ margin: 2, fontSize: '13px' }}>Something went wrong !</span>
+                              </div>
+                            </ErrorAlert>
+                              : <MessageBubble type='ANSWER'>
+                                <Message type='ANSWER' style={{ fontWeight: 600 }}>
+                                  <DotAnimation>.</DotAnimation>
+                                  <Delay delay={200}>.</Delay>
+                                  <Delay delay={400}>.</Delay>
+                                </Message>
+                              </MessageBubble>
+                          }
+                        </div>
+                    }
+                  </Fragment>)
+              })
+                : <Hero title={heroTitle} description={heroDescription} />
+            }
+          </Conversation>
+
+          <PromptContainer
+            onSubmit={handleSubmit}>
+            <StyledInput
+              value={prompt} onChange={(event) => setPrompt(event.target.value)}
+              type='text' placeholder="What do you want to do?" />
+            <StyledButton
+              disabled={prompt.length == 0 || status !== 'idle'}>
+              <PaperPlaneIcon width={15} height={15} color='white' />
+            </StyledButton>
+          </PromptContainer>
+        </StyledContainer>}
+      </WidgetContainer>
     </>
   )
-}
+}

extensions/react-widget/src/components/index.ts

@@ -1 +0,0 @@
-export { DocsGPTWidget } from "./DocsGPTWidget";

extensions/react-widget/src/index.css

@@ -1,44 +0,0 @@
-@tailwind base;
-@tailwind components;
-@tailwind utilities;
-
-#docsgpt-answer {
-    max-height: 50vh; /* 50% of the viewport height */
-    overflow-y: auto; /* Adds a vertical scrollbar if the content exceeds the container height */
-}
-
-.widget-container {
-  position: fixed;   /* fixed positioning */
-  right: 10px;       /* from the right edge */
-  bottom: 10px;      /* from the bottom edge */
-  z-index: 1000;     /* to ensure it appears on top of other content, if any */
-  display: flex;
-  flex-direction: column;
-  align-items: center;
-}
-
-  @keyframes dotBounce {
-    0%, 80%, 100% {
-      transform: translateY(0);
-    }
-    40% {
-      transform: translateY(-5px);
-    }
-  }
-
-  .dot-animation {
-    display: inline-block;
-    animation: dotBounce 1s infinite ease-in-out;
-  }
-
-  .delay-200 {
-    animation-delay: 200ms;
-  }
-
-  .delay-400 {
-    animation-delay: 400ms;
-  }
-
-  .white-filter {
-    filter: invert(1) brightness(2);
-}

extensions/react-widget/src/index.html

@@ -2,12 +2,12 @@
 <html lang="en">
   <head>
     <meta charset="UTF-8" />
-    <link rel="icon" type="image/svg+xml" href="/vite.svg" />
+    <meta http-equiv="X-UA-Compatible" content="IE=edge" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>Vite + React + TS</title>
+    <title>DocsGPT Widget</title>
   </head>
   <body>
-    <div id="root"></div>
-    <script type="module" src="/src/main.tsx"></script>
+    <div id="app"></div>
+    <script type="module" src="main.tsx"></script>
   </body>
 </html>

extensions/react-widget/src/index.ts

@@ -0,0 +1 @@
+export { DocsGPTWidget } from "./components/DocsGPTWidget";

extensions/react-widget/src/main.tsx

@@ -1,10 +1,6 @@
-import React from 'react'
-import ReactDOM from 'react-dom/client'
-import App from './App'
-import './index.css'
+import { createRoot } from 'react-dom/client';
+import App from './App.tsx';
+import React from 'react';
+const root = createRoot(document.getElementById('app') as HTMLElement);
 
-ReactDOM.createRoot(document.getElementById('root') as HTMLElement).render(
-  <React.StrictMode>
-    <App />
-  </React.StrictMode>,
-)
+root.render(<App />);

extensions/react-widget/src/requests/streamingApi.ts

@@ -0,0 +1,92 @@
+interface HistoryItem {
+    prompt: string;
+    response?: string;
+  }
+interface FetchAnswerStreamingProps {
+    question?: string;
+    apiKey?: string;
+    selectedDocs?: string;
+    history?: HistoryItem[];
+    conversationId?: string | null;
+    apiHost?: string;
+    onEvent?: (event: MessageEvent) => void;
+  }
+export function fetchAnswerStreaming({
+    question = '',
+    apiKey = '',
+    selectedDocs = '',
+    history = [],
+    conversationId = null,
+    apiHost = '',
+    onEvent = () => {console.log("Event triggered, but no handler provided.");}
+  }: FetchAnswerStreamingProps): Promise<void> {
+    let docPath = 'default';
+    if (selectedDocs) {
+      docPath = selectedDocs;
+    }
+  
+    return new Promise<void>((resolve, reject) => {
+      const body = {
+        question: question,
+        api_key: apiKey,
+        embeddings_key: apiKey,
+        active_docs: docPath,
+        history: JSON.stringify(history),
+        conversation_id: conversationId,
+        model: 'default'
+      };
+  
+      fetch(apiHost + '/stream', {
+        method: 'POST',
+        headers: {
+          'Content-Type': 'application/json',
+        },
+        body: JSON.stringify(body),
+      })
+        .then((response) => {
+          if (!response.body) throw Error('No response body');
+  
+          const reader = response.body.getReader();
+          const decoder = new TextDecoder('utf-8');
+          let counterrr = 0;
+          const processStream = ({
+            done,
+            value,
+          }: ReadableStreamReadResult<Uint8Array>) => {
+            if (done) {
+              resolve();
+              return;
+            }
+  
+            counterrr += 1;
+  
+            const chunk = decoder.decode(value);
+  
+            const lines = chunk.split('\n');
+  
+            for (let line of lines) {
+              if (line.trim() == '') {
+                continue;
+              }
+              if (line.startsWith('data:')) {
+                line = line.substring(5);
+              }
+  
+              const messageEvent = new MessageEvent('message', {
+                data: line,
+              });
+  
+              onEvent(messageEvent); // handle each message
+            }
+  
+            reader.read().then(processStream).catch(reject);
+          };
+  
+          reader.read().then(processStream).catch(reject);
+        })
+        .catch((error) => {
+          console.error('Connection failed:', error);
+          reject(error);
+        });
+    });
+  }

extensions/react-widget/src/types/index.ts

@@ -0,0 +1,13 @@
+export type MESSAGE_TYPE = 'QUESTION' | 'ANSWER' | 'ERROR';
+export type Status = 'idle' | 'loading' | 'failed';
+export type FEEDBACK = 'LIKE' | 'DISLIKE';
+
+export interface Query {
+  prompt: string;
+  response?: string;
+  feedback?: FEEDBACK;
+  error?: string;
+  sources?: { title: string; text: string }[];
+  conversationId?: string | null;
+  title?: string | null;
+}

extensions/react-widget/src/vite-env.d.ts

@@ -1 +0,0 @@
-/// <reference types="vite/client" />

extensions/react-widget/tailwind.config.cjs

@@ -1,8 +0,0 @@
-/** @type {import('tailwindcss').Config} */
-module.exports = {
-  content: ["./index.html", "./src/**/*.{js,ts,jsx,tsx}"],
-  theme: {
-    extend: {},
-  },
-  plugins: [],
-};

extensions/react-widget/tsconfig.json

@@ -1,23 +1,34 @@
 {
-  "compilerOptions": {
-    "target": "ESNext",
-    "useDefineForClassFields": true,
-    "lib": ["DOM", "DOM.Iterable", "ESNext"],
-    "allowJs": false,
-    "skipLibCheck": true,
-    "esModuleInterop": false,
-    "allowSyntheticDefaultImports": true,
-    "strict": true,
-    "forceConsistentCasingInFileNames": true,
-    "module": "ESNext",
-    "moduleResolution": "Node",
-    "resolveJsonModule": true,
-    "isolatedModules": true,
-    "declaration": true,
-    "typeRoots": ["./dist/index.d.ts", "node_modules/@types"],
-    "noEmit": true,
-    "jsx": "react-jsx"
-  },
-  "include": ["src", "./index.ts"],
-  "references": [{ "path": "./tsconfig.node.json" }]
-}
+    "compilerOptions": {
+      "baseUrl": ".",
+      "paths": {
+        "@/*": ["src/*", "@/*"]
+      },
+      "target": "ES2020",
+      "useDefineForClassFields": true,
+      "lib": ["ES2020", "DOM", "DOM.Iterable"],
+      "module": "ESNext",
+      "skipLibCheck": true,
+  
+      /* Bundler mode */
+      "moduleResolution": "bundler",
+      "allowImportingTsExtensions": true,
+      "resolveJsonModule": true,
+      "isolatedModules": true,
+      "noEmit": true,
+      "jsx": "react-jsx",
+  
+      /* Linting */
+      "strict": true,
+      "noUnusedLocals": false,
+      "noUnusedParameters": true,
+      "noFallthroughCasesInSwitch": true,
+      /* The "typeRoots" configuration specifies the locations where 
+         TypeScript looks for type definitions (.d.ts files) to 
+         include in the compilation process.*/
+         "typeRoots": ["./dist/index.d.ts", "node_modules/@types"]
+        },
+        /* include /index.ts*/
+        "include": ["src/index.ts","custom.d.ts"],
+        "exclude": ["node_modules"],
+  }

extensions/react-widget/tsconfig.node.json

@@ -1,9 +0,0 @@
-{
-  "compilerOptions": {
-    "composite": true,
-    "module": "ESNext",
-    "moduleResolution": "Node",
-    "allowSyntheticDefaultImports": true
-  },
-  "include": ["vite.config.ts"]
-}

extensions/react-widget/vite.config.ts

@@ -1,26 +0,0 @@
-import { defineConfig } from "vite";
-import react from "@vitejs/plugin-react-swc";
-import dts from "vite-plugin-dts";
-import path from "path";
-
-export default defineConfig({
-  build: {
-    lib: {
-      entry: path.resolve(__dirname, "index.ts"),
-      name: "ViteButton",
-      fileName: (format) => `index.${format}.js`,
-    },
-    rollupOptions: {
-      external: ["react", "react-dom"],
-      output: {
-        globals: {
-          react: "React",
-          "react-dom": "ReactDOM",
-        },
-      },
-    },
-    sourcemap: true,
-    emptyOutDir: true,
-  },
-  plugins: [react(), dts()],
-});

frontend/package-lock.json

@@ -44,7 +44,7 @@
         "prettier-plugin-tailwindcss": "^0.2.2",
         "tailwindcss": "^3.2.4",
         "typescript": "^4.9.5",
-        "vite": "^5.0.12",
+        "vite": "^5.0.13",
         "vite-plugin-svgr": "^4.2.0"
       }
     },
@@ -7855,9 +7855,9 @@
       }
     },
     "node_modules/vite": {
-      "version": "5.0.12",
-      "resolved": "https://registry.npmjs.org/vite/-/vite-5.0.12.tgz",
-      "integrity": "sha512-4hsnEkG3q0N4Tzf1+t6NdN9dg/L3BM+q8SWgbSPnJvrgH2kgdyzfVJwbR1ic69/4uMJJ/3dqDZZE5/WwqW8U1w==",
+      "version": "5.0.13",
+      "resolved": "https://registry.npmjs.org/vite/-/vite-5.0.13.tgz",
+      "integrity": "sha512-/9ovhv2M2dGTuA+dY93B9trfyWMDRQw2jdVBhHNP6wr0oF34wG2i/N55801iZIpgUpnHDm4F/FabGQLyc+eOgg==",
       "dev": true,
       "dependencies": {
         "esbuild": "^0.19.3",

frontend/package.json

@@ -55,7 +55,7 @@
     "prettier-plugin-tailwindcss": "^0.2.2",
     "tailwindcss": "^3.2.4",
     "typescript": "^4.9.5",
-    "vite": "^5.0.12",
+    "vite": "^5.0.13",
     "vite-plugin-svgr": "^4.2.0"
   }
 }

frontend/src/About.tsx

@@ -5,7 +5,7 @@ import DocsGPT3 from './assets/cute_docsgpt3.svg';
 export default function About() {
   return (
     <div className="mx-5 grid min-h-screen md:mx-36">
-      <article className="place-items-left mx-auto my-auto flex w-full max-w-6xl flex-col gap-4 rounded-3xl bg-gray-100 dark:bg-gun-metal p-6 text-jet dark:text-bright-gray lg:p-6 xl:p-10">
+      <article className="place-items-left mx-auto my-auto flex w-full max-w-6xl flex-col gap-4 rounded-3xl bg-gray-100 p-6 text-jet dark:bg-gun-metal dark:text-bright-gray lg:p-6 xl:p-10">
         <div className="flex items-center">
           <p className="mr-2 text-3xl">About DocsGPT</p>
           <img className="h14 mb-2" src={DocsGPT3} alt="DocsGPT" />
@@ -31,23 +31,34 @@ export default function About() {
           </p>
           <p className="mt-4 ml-2">
             1. Navigate to{' '}
-            <span className="bg-gray-200 dark:bg-outer-space italic"> /application</span> folder
+            <span className="bg-gray-200 italic dark:bg-outer-space">
+              {' '}
+              /application
+            </span>{' '}
+            folder
           </p>
           <p className="mt-4 ml-2">
             2. Install dependencies from{' '}
-            <span className="bg-gray-200 dark:bg-outer-space italic">
+            <span className="bg-gray-200 italic dark:bg-outer-space">
               pip install -r requirements.txt
             </span>
           </p>
           <p className="mt-4 ml-2">
-            3. Prepare a <span className="bg-gray-200 dark:bg-outer-space italic">.env</span> file.
-            Copy <span className="bg-gray-200 dark:bg-outer-space italic">.env_sample</span> and
-            create <span className="bg-gray-200 dark:bg-outer-space italic">.env</span> with your
-            OpenAI API token
+            3. Prepare a{' '}
+            <span className="bg-gray-200 italic dark:bg-outer-space">.env</span>{' '}
+            file. Copy{' '}
+            <span className="bg-gray-200 italic dark:bg-outer-space">
+              .env_sample
+            </span>{' '}
+            and create{' '}
+            <span className="bg-gray-200 italic dark:bg-outer-space">.env</span>{' '}
+            with your OpenAI API token
           </p>
           <p className="mt-4 ml-2">
             4. Run the app with{' '}
-            <span className="bg-gray-200 dark:bg-outer-space italic">python app.py</span>
+            <span className="bg-gray-200 italic dark:bg-outer-space">
+              python app.py
+            </span>
           </p>
         </div>
 

frontend/src/App.tsx

@@ -5,23 +5,14 @@ import About from './About';
 import PageNotFound from './PageNotFound';
 import { inject } from '@vercel/analytics';
 import { useMediaQuery } from './hooks';
-import { useState,useEffect } from 'react';
-import Setting from './Setting';
+import { useState } from 'react';
+import Setting from './settings';
 
 inject();
 
 export default function App() {
   const { isMobile } = useMediaQuery();
   const [navOpen, setNavOpen] = useState(!isMobile);
-  const selectedTheme = localStorage.getItem('selectedTheme');
-  useEffect(()=>{
-    if (selectedTheme === 'Dark') {
-      document.documentElement.classList.add('dark');
-      document.body.classList.add('dark:bg-raisin-black');
-    } else {
-      document.documentElement.classList.remove('dark');
-    }
-  },[])
   return (
     <div className="min-h-full min-w-full dark:bg-raisin-black">
       <Navigation navOpen={navOpen} setNavOpen={setNavOpen} />

frontend/src/Hero.tsx

@@ -1,20 +1,21 @@
-import { useMediaQuery } from './hooks';
+import { useDarkTheme, useMediaQuery } from './hooks';
 import DocsGPT3 from './assets/cute_docsgpt3.svg';
 
 export default function Hero({ className = '' }: { className?: string }) {
   // const isMobile = window.innerWidth <= 768;
   const { isMobile } = useMediaQuery();
-  const isDarkTheme = document.documentElement.classList.contains('dark');
-  console.log(isDarkTheme)
+  const [isDarkTheme] = useDarkTheme();
   return (
-    <div className={`mt-14 ${isMobile ? 'mb-2' : 'mb-12'}flex flex-col text-black-1000 dark:text-bright-gray`}>
+    <div
+      className={`mt-14 mb-32 flex flex-col text-black-1000 dark:text-bright-gray lg:mt-6`}
+    >
       <div className=" mb-2 flex items-center justify-center sm:mb-10">
         <p className="mr-2 text-4xl font-semibold">DocsGPT</p>
         <img className="mb-2 h-14" src={DocsGPT3} alt="DocsGPT" />
       </div>
       {isMobile ? (
         <p className="mb-3 text-center leading-6">
-          Welcome to <span className="font-bold ">DocsGPT</span>, your technical
+          Welcome to <span className="font-bold">DocsGPT</span>, your technical
           documentation assistant! Start by entering your query in the input
           field below, and we&apos;ll provide you with the most relevant
           answers.
@@ -36,20 +37,22 @@ export default function Hero({ className = '' }: { className?: string }) {
         </>
       )}
       <div
-        className={`sections ${isMobile ? '' : 'mt-1'
-          } flex flex-wrap items-center justify-center gap-2 sm:gap-1 md:gap-0`}
+        className={`mt-0 flex flex-wrap items-center justify-center gap-2 sm:mt-1 sm:gap-4 md:gap-4 lg:gap-0`}
       >
         {/* first */}
-        <div className="h-auto md:h-60 rounded-[50px] bg-gradient-to-l  from-[#6EE7B7]/70 dark:from-[#D16FF8] via-[#3B82F6] dark:via-[#48E6E0] to-[#9333EA]/50 dark:to-[#C85EF6] p-1  md:rounded-tr-none md:rounded-br-none">
+        <div className="h-auto rounded-[50px] bg-gradient-to-l from-[#6EE7B7]/70  via-[#3B82F6] to-[#9333EA]/50 p-1 dark:from-[#D16FF8] dark:via-[#48E6E0] dark:to-[#C85EF6] lg:h-60  lg:rounded-tr-none lg:rounded-br-none">
           <div
-            className={`h-full rounded-[45px] bg-white dark:bg-dark-charcoal p-${isMobile ? '3.5' : '6 py-8'
-              }  md:rounded-tr-none md:rounded-br-none`}
+            className={`h-full rounded-[45px] bg-white dark:bg-dark-charcoal p-${
+              isMobile ? '3.5' : '6 py-8'
+            }  lg:rounded-tr-none lg:rounded-br-none`}
           >
             {/* Add Mobile check here */}
             {isMobile ? (
               <div className="flex justify-center">
                 <img
-                  src={isDarkTheme ? "/message-text-dark.svg" : "/message-text.svg"}
+                  src={
+                    isDarkTheme ? '/message-text-dark.svg' : '/message-text.svg'
+                  }
                   alt="lock"
                   className="h-[24px] w-[24px] "
                 />
@@ -60,7 +63,9 @@ export default function Hero({ className = '' }: { className?: string }) {
             ) : (
               <>
                 <img
-                  src={isDarkTheme ? "/message-text-dark.svg" : "/message-text.svg"}
+                  src={
+                    isDarkTheme ? '/message-text-dark.svg' : '/message-text.svg'
+                  }
                   alt="lock"
                   className="h-[24px] w-[24px]"
                 />
@@ -84,22 +89,31 @@ export default function Hero({ className = '' }: { className?: string }) {
           </div>
         </div>
         {/* second */}
-        <div className="h-auto md:h-60 rounded-[50px] bg-gradient-to-r from-[#6EE7B7]/70 dark:from-[#D16FF8] via-[#3B82F6] dark:via-[#48E6E0] to-[#9333EA]/50 dark:to-[#C85EF6] p-1  md:rounded-none  md:py-1 md:px-0">
+        <div className="h-auto rounded-[50px] bg-gradient-to-r from-[#6EE7B7]/70 via-[#3B82F6] to-[#9333EA]/50 p-1 dark:from-[#D16FF8] dark:via-[#48E6E0] dark:to-[#C85EF6] lg:h-60  lg:rounded-none  lg:py-1 lg:px-0">
           <div
-            className={`h-full rounded-[45px] bg-white dark:bg-dark-charcoal p-${isMobile ? '3.5' : '6 py-6'
-              }  md:rounded-none`}
+            className={`h-full rounded-[45px] bg-white dark:bg-dark-charcoal p-${
+              isMobile ? '3.5' : '6 py-6'
+            }  lg:rounded-none`}
           >
             {/* Add Mobile check here */}
             {isMobile ? (
               <div className="flex justify-center ">
-                <img src={isDarkTheme ? "/lock-dark.svg" : "/lock.svg"} alt="lock" className="h-[24px] w-[24px]" />
+                <img
+                  src={isDarkTheme ? '/lock-dark.svg' : '/lock.svg'}
+                  alt="lock"
+                  className="h-[24px] w-[24px]"
+                />
                 <h2 className="mb-0 pl-1 text-lg font-bold">
                   Secure Data Storage
                 </h2>
               </div>
             ) : (
               <>
-                <img src={isDarkTheme ? "/lock-dark.svg" : "/lock.svg"} alt="lock" className="h-[24px] w-[24px]" />
+                <img
+                  src={isDarkTheme ? '/lock-dark.svg' : '/lock.svg'}
+                  alt="lock"
+                  className="h-[24px] w-[24px]"
+                />
                 <h2 className="mt-2 mb-3 text-lg font-bold">
                   Secure Data Storage
                 </h2>
@@ -120,16 +134,21 @@ export default function Hero({ className = '' }: { className?: string }) {
           </div>
         </div>
         {/* third */}
-        <div className="h-auto md:h-60 rounded-[50px] bg-gradient-to-l  from-[#6EE7B7]/70 dark:from-[#D16FF8] via-[#3B82F6] dark:via-[#48E6E0] to-[#9333EA]/50 dark:to-[#C85EF6] p-1 md:rounded-tl-none md:rounded-bl-none ">
+        <div className="h-auto rounded-[50px] bg-gradient-to-l from-[#6EE7B7]/70  via-[#3B82F6] to-[#9333EA]/50 p-1 dark:from-[#D16FF8] dark:via-[#48E6E0] dark:to-[#C85EF6] lg:h-60 lg:rounded-tl-none lg:rounded-bl-none ">
           <div
-            className={`h-full firefox rounded-[45px] bg-white dark:bg-dark-charcoal p-${isMobile ? '3.5' : '6 px-6 '
-              } lg:rounded-tl-none lg:rounded-bl-none`}
+            className={`firefox h-full rounded-[45px] bg-white dark:bg-dark-charcoal p-${
+              isMobile ? '3.5' : '6 px-6 '
+            } lg:rounded-tl-none lg:rounded-bl-none`}
           >
             {/* Add Mobile check here */}
             {isMobile ? (
               <div className="flex justify-center">
                 <img
-                  src={isDarkTheme ? "message-programming-dark.svg" : "/message-programming.svg"}
+                  src={
+                    isDarkTheme
+                      ? 'message-programming-dark.svg'
+                      : '/message-programming.svg'
+                  }
                   alt="lock"
                   className="h-[24px] w-[24px]"
                 />
@@ -140,7 +159,11 @@ export default function Hero({ className = '' }: { className?: string }) {
             ) : (
               <>
                 <img
-                  src={isDarkTheme ? "/message-programming-dark.svg" : "/message-programming.svg"}
+                  src={
+                    isDarkTheme
+                      ? '/message-programming-dark.svg'
+                      : '/message-programming.svg'
+                  }
                   alt="lock"
                   className="h-[24px] w-[24px]"
                 />

frontend/src/Navigation.tsx

@@ -1,15 +1,13 @@
 import { useEffect, useRef, useState } from 'react';
 import { useDispatch, useSelector } from 'react-redux';
 import { NavLink, useNavigate } from 'react-router-dom';
+import PropTypes from 'prop-types';
 import DocsGPT3 from './assets/cute_docsgpt3.svg';
 import Documentation from './assets/documentation.svg';
 import DocumentationDark from './assets/documentation-dark.svg';
 import Discord from './assets/discord.svg';
 import DiscordDark from './assets/discord-dark.svg';
-
-import Arrow2 from './assets/dropdown-arrow.svg';
 import Expand from './assets/expand.svg';
-import Trash from './assets/trash.svg';
 import Github from './assets/github.svg';
 import GithubDark from './assets/github-dark.svg';
 import Hamburger from './assets/hamburger.svg';
@@ -41,12 +39,28 @@ import Upload from './upload/Upload';
 import { Doc, getConversations } from './preferences/preferenceApi';
 import SelectDocsModal from './preferences/SelectDocsModal';
 import ConversationTile from './conversation/ConversationTile';
+import { useDarkTheme } from './hooks';
+import SourceDropdown from './components/SourceDropdown';
 
 interface NavigationProps {
   navOpen: boolean;
   setNavOpen: React.Dispatch<React.SetStateAction<boolean>>;
 }
-
+const NavImage: React.FC<{
+  Light: string | undefined;
+  Dark: string | undefined;
+}> = ({ Light, Dark }) => {
+  return (
+    <>
+      <img src={Dark} alt="icon" className="ml-2 hidden w-5 dark:block " />
+      <img src={Light} alt="icon" className="ml-2 w-5 dark:hidden " />
+    </>
+  );
+};
+NavImage.propTypes = {
+  Light: PropTypes.string,
+  Dark: PropTypes.string,
+};
 export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
   const dispatch = useDispatch();
   const docs = useSelector(selectSourceDocs);
@@ -54,7 +68,7 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
   const conversations = useSelector(selectConversations);
   const conversationId = useSelector(selectConversationId);
   const { isMobile } = useMediaQuery();
-  const isDarkTheme = document.documentElement.classList.contains('dark');
+  const [isDarkTheme] = useDarkTheme();
   const [isDocsListOpen, setIsDocsListOpen] = useState(false);
 
   const isApiKeySet = useSelector(selectApiKeyStatus);
@@ -70,9 +84,6 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
 
   const navRef = useRef(null);
   const apiHost = import.meta.env.VITE_API_HOST || 'https://docsapi.arc53.com';
-  const embeddingsName =
-    import.meta.env.VITE_EMBEDDINGS_NAME ||
-    'huggingface_sentence-transformers/all-mpnet-base-v2';
 
   const navigate = useNavigate();
 
@@ -81,7 +92,6 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
       fetchConversations();
     }
   }, [conversations, dispatch]);
-
   async function fetchConversations() {
     return await getConversations()
       .then((fetchedConversations) => {
@@ -176,7 +186,6 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
   useEffect(() => {
     setNavOpen(!isMobile);
   }, [isMobile]);
-
   return (
     <>
       {!navOpen && (
@@ -189,15 +198,17 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
           <img
             src={Expand}
             alt="menu toggle"
-            className={`${!navOpen ? 'rotate-180' : 'rotate-0'
-              } m-auto transition-all duration-200`}
+            className={`${
+              !navOpen ? 'rotate-180' : 'rotate-0'
+            } m-auto transition-all duration-200`}
           />
         </button>
       )}
       <div
         ref={navRef}
-        className={`${!navOpen && '-ml-96 md:-ml-[18rem]'
-          } duration-20 fixed top-0 z-20 flex h-full w-72 flex-col border-r-[1px] border-b-0 dark:border-r-purple-taupe bg-white dark:bg-chinese-black transition-all dark:text-white`}
+        className={`${
+          !navOpen && '-ml-96 md:-ml-[18rem]'
+        } duration-20 fixed top-0 z-20 flex h-full w-72 flex-col border-r-[1px] border-b-0 bg-white transition-all dark:border-r-purple-taupe dark:bg-chinese-black dark:text-white`}
       >
         <div
           className={'visible mt-2 flex h-[6vh] w-full justify-between md:h-12'}
@@ -215,8 +226,9 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
             <img
               src={Expand}
               alt="menu toggle"
-              className={`${!navOpen ? 'rotate-180' : 'rotate-0'
-                } m-auto transition-all duration-200`}
+              className={`${
+                !navOpen ? 'rotate-180' : 'rotate-0'
+              } m-auto transition-all duration-200`}
             />
           </button>
         </div>
@@ -231,8 +243,9 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
             );
           }}
           className={({ isActive }) =>
-            `${isActive ? 'bg-gray-3000 dark:bg-transparent' : ''
-            } group sticky mx-4 mt-4 flex cursor-pointer gap-2.5 rounded-3xl border border-silver p-3 hover:border-rainy-gray dark:border-purple-taupe dark:text-white dark:hover:bg-transparent hover:bg-gray-3000`
+            `${
+              isActive ? 'bg-gray-3000 dark:bg-transparent' : ''
+            } group sticky mx-4 mt-4 flex cursor-pointer gap-2.5 rounded-3xl border border-silver p-3 hover:border-rainy-gray hover:bg-gray-3000 dark:border-purple-taupe dark:text-white dark:hover:bg-transparent`
           }
         >
           <img
@@ -244,7 +257,7 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
             New Chat
           </p>
         </NavLink>
-        <div className="mb-auto h-[56vh] overflow-x-hidden dark:text-white overflow-y-scroll">
+        <div className="mb-auto h-[56vh] overflow-y-auto overflow-x-hidden dark:text-white">
           {conversations && (
             <div>
               <p className="ml-6 mt-3 text-sm font-semibold">Chats</p>
@@ -268,96 +281,48 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
         <div className="flex h-auto flex-col justify-end text-eerie-black dark:text-white">
           <div className="flex flex-col-reverse border-b-[1px] dark:border-b-purple-taupe">
             <div className="relative my-4 flex gap-2 px-2">
-              <div
-                className="flex h-12 w-5/6 cursor-pointer justify-between rounded-3xl border-2 dark:border-chinese-silver bg-white dark:bg-chinese-black"
-                onClick={() => setIsDocsListOpen(!isDocsListOpen)}
-              >
-                {selectedDocs && (
-                  <p className="my-3 mx-4 overflow-hidden text-ellipsis whitespace-nowrap">
-                    {selectedDocs.name} {selectedDocs.version}
-                  </p>
-                )}
-                <img
-                  src={Arrow2}
-                  alt="arrow"
-                  className={`${!isDocsListOpen ? 'rotate-0' : 'rotate-180'
-                    } ml-auto mr-3 w-3 transition-all`}
-                />
-              </div>
+              <SourceDropdown
+                options={docs}
+                selectedDocs={selectedDocs}
+                setSelectedDocs={setSelectedDocs}
+                isDocsListOpen={isDocsListOpen}
+                setIsDocsListOpen={setIsDocsListOpen}
+                handleDeleteClick={handleDeleteClick}
+              />
               <img
                 className="mt-2 h-9 w-9 hover:cursor-pointer"
                 src={UploadIcon}
                 onClick={() => setUploadModalState('ACTIVE')}
               ></img>
-              {isDocsListOpen && (
-                <div className="absolute top-12 left-0 right-6 z-10 ml-2 mr-4 max-h-52 overflow-y-scroll bg-white dark:bg-chinese-black shadow-lg">
-                  {docs ? (
-                    docs.map((doc, index) => {
-                      if (doc.model === embeddingsName) {
-                        return (
-                          <div
-                            key={index}
-                            onClick={() => {
-                              dispatch(setSelectedDocs(doc));
-                              setIsDocsListOpen(false);
-                            }}
-                            className="flex h-10 w-full cursor-pointer items-center justify-between border-x-2 border-b-[1px] dark:border-purple-taupe hover:bg-gray-100 dark:hover:bg-purple-taupe"
-                          >
-                            <p className="ml-5 flex-1 overflow-hidden overflow-ellipsis whitespace-nowrap py-3">
-                              {doc.name} {doc.version}
-                            </p>
-                            {doc.location === 'local' && (
-                              <img
-                                src={Trash}
-                                alt="Delete"
-                                className="mr-4 h-4 w-4 cursor-pointer hover:opacity-50"
-                                id={`img-${index}`}
-                                onClick={(event) => {
-                                  event.stopPropagation();
-                                  handleDeleteClick(index, doc);
-                                }}
-                              />
-                            )}
-                          </div>
-                        );
-                      }
-                    })
-                  ) : (
-                    <div className="h-10 w-full cursor-pointer  border-b-[1px] dark:border-b-purple-taupe hover:bg-gray-100">
-                      <p className="ml-5 py-3">No default documentation.</p>
-                    </div>
-                  )}
-                </div>
-              )}
             </div>
             <p className="ml-6 mt-3 text-sm font-semibold">Source Docs</p>
           </div>
-          <div className="flex flex-col gap-2 border-b-[1px] dark:border-b-purple-taupe py-2">
+          <div className="flex flex-col gap-2 border-b-[1px] py-2 dark:border-b-purple-taupe">
             <NavLink
               to="/settings"
               className={({ isActive }) =>
-                `my-auto mx-4 flex h-9 cursor-pointer gap-4 rounded-3xl hover:bg-gray-100 dark:hover:bg-purple-taupe ${isActive ? 'bg-gray-3000 dark:bg-transparent' : ''
+                `my-auto mx-4 flex h-9 cursor-pointer gap-4 rounded-3xl hover:bg-gray-100 dark:hover:bg-purple-taupe ${
+                  isActive ? 'bg-gray-3000 dark:bg-transparent' : ''
                 }`
               }
             >
-              <img
-                src={isDarkTheme ? SettingGearDark : SettingGear}
-                alt="settings"
-                className="ml-2 w-5 opacity-60"
-              />
-              <p className="my-auto text-sm text-eerie-black  dark:text-white">Settings</p>
+              <NavImage Light={SettingGear} Dark={SettingGearDark} />
+              <p className="my-auto text-sm text-eerie-black  dark:text-white">
+                Settings
+              </p>
             </NavLink>
           </div>
 
-          <div className="flex flex-col gap-2 border-b-[1.5px] dark:border-b-purple-taupe py-2">
+          <div className="flex flex-col gap-2 border-b-[1.5px] py-2 dark:border-b-purple-taupe">
             <NavLink
               to="/about"
               className={({ isActive }) =>
-                `my-auto mx-4 flex h-9 cursor-pointer gap-4 rounded-3xl hover:bg-gray-100 dark:hover:bg-purple-taupe ${isActive ? 'bg-gray-3000 dark:bg-purple-taupe' : ''
+                `my-auto mx-4 flex h-9 cursor-pointer gap-4 rounded-3xl hover:bg-gray-100 dark:hover:bg-purple-taupe ${
+                  isActive ? 'bg-gray-3000 dark:bg-purple-taupe' : ''
                 }`
               }
             >
-              <img src={isDarkTheme ? InfoDark : Info} alt="info" className="ml-2 w-5" />
+              <NavImage Light={Info} Dark={InfoDark} />
               <p className="my-auto text-sm">About</p>
             </NavLink>
 
@@ -367,11 +332,7 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
               rel="noreferrer"
               className="my-auto mx-4 flex h-9 cursor-pointer gap-4 rounded-3xl hover:bg-gray-100 dark:hover:bg-purple-taupe"
             >
-              <img
-                src={isDarkTheme ? DocumentationDark : Documentation}
-                alt="documentation"
-                className="ml-2 w-5"
-              />
+              <NavImage Light={Documentation} Dark={DocumentationDark} />
               <p className="my-auto text-sm ">Documentation</p>
             </a>
             <a
@@ -380,32 +341,33 @@ export default function Navigation({ navOpen, setNavOpen }: NavigationProps) {
               rel="noreferrer"
               className="my-auto mx-4 flex h-9 cursor-pointer gap-4 rounded-3xl hover:bg-gray-100 dark:hover:bg-purple-taupe"
             >
-              <img src={isDarkTheme ? DiscordDark : Discord} alt="discord-link" className="ml-2 w-5" />
-              <p className="my-auto text-sm">
-                Visit our Discord
-              </p>
+              <NavImage Light={Discord} Dark={DiscordDark} />
+              {/*  <img src={isDarkTheme ? DiscordDark : Discord} alt="discord-link" className="ml-2 w-5" /> */}
+              <p className="my-auto text-sm">Visit our Discord</p>
             </a>
 
             <a
               href="https://github.com/arc53/DocsGPT"
               target="_blank"
               rel="noreferrer"
-              className="mt-auto mx-4 flex h-9 cursor-pointer gap-4 rounded-3xl hover:bg-gray-100 dark:hover:bg-purple-taupe"
+              className="mx-4 mt-auto flex h-9 cursor-pointer gap-4 rounded-3xl hover:bg-gray-100 dark:hover:bg-purple-taupe"
             >
-              <img src={isDarkTheme ? GithubDark : Github} alt="github-link" className="ml-2 w-5" />
-              <p className="my-auto text-sm">
-                Visit our Github
-              </p>
+              <NavImage Light={Github} Dark={GithubDark} />
+              <p className="my-auto text-sm">Visit our Github</p>
             </a>
           </div>
         </div>
       </div>
-      <div className="fixed z-10 h-16 w-full border-b-2 dark:border-b-purple-taupe bg-gray-50 dark:bg-chinese-black md:hidden">
+      <div className="fixed z-10 h-16 w-full border-b-2 bg-gray-50 dark:border-b-purple-taupe dark:bg-chinese-black md:hidden">
         <button
           className="mt-5 ml-6 h-6 w-6 md:hidden"
           onClick={() => setNavOpen(true)}
         >
-          <img src={isDarkTheme ? HamburgerDark :Hamburger} alt="menu toggle" className="w-7" />
+          <img
+            src={isDarkTheme ? HamburgerDark : Hamburger}
+            alt="menu toggle"
+            className="w-7"
+          />
         </button>
       </div>
       <SelectDocsModal

frontend/src/Setting.tsx

@@ -1,827 +0,0 @@
-import React, { useState, useEffect } from 'react';
-import { useSelector, useDispatch } from 'react-redux';
-import Arrow2 from './assets/dropdown-arrow.svg';
-import ArrowLeft from './assets/arrow-left.svg';
-import ArrowRight from './assets/arrow-right.svg';
-import Trash from './assets/trash.svg';
-import {
-  selectPrompt,
-  setPrompt,
-  selectSourceDocs,
-} from './preferences/preferenceSlice';
-import { Doc } from './preferences/preferenceApi';
-type PromptProps = {
-  prompts: { name: string; id: string; type: string }[];
-  selectedPrompt: { name: string; id: string; type: string };
-  onSelectPrompt: (name: string, id: string, type: string) => void;
-  setPrompts: (prompts: { name: string; id: string; type: string }[]) => void;
-  apiHost: string;
-};
-
-const Setting: React.FC = () => {
-  const tabs = ['General', 'Prompts', 'Documents'];
-  //const tabs = ['General', 'Prompts', 'Documents', 'Widgets'];
-
-  const [activeTab, setActiveTab] = useState('General');
-  const [prompts, setPrompts] = useState<
-    { name: string; id: string; type: string }[]
-  >([]);
-  const selectedPrompt = useSelector(selectPrompt);
-  const [isAddPromptModalOpen, setAddPromptModalOpen] = useState(false);
-  const documents = useSelector(selectSourceDocs);
-  const [isAddDocumentModalOpen, setAddDocumentModalOpen] = useState(false);
-
-  const dispatch = useDispatch();
-
-  const apiHost = import.meta.env.VITE_API_HOST || 'https://docsapi.arc53.com';
-  const [widgetScreenshot, setWidgetScreenshot] = useState<File | null>(null);
-
-  const updateWidgetScreenshot = (screenshot: File | null) => {
-    setWidgetScreenshot(screenshot);
-  };
-
-  useEffect(() => {
-    const fetchPrompts = async () => {
-      try {
-        const response = await fetch(`${apiHost}/api/get_prompts`);
-        if (!response.ok) {
-          throw new Error('Failed to fetch prompts');
-        }
-        const promptsData = await response.json();
-        setPrompts(promptsData);
-      } catch (error) {
-        console.error(error);
-      }
-    };
-
-    fetchPrompts();
-  }, []);
-
-  const onDeletePrompt = (name: string, id: string) => {
-    setPrompts(prompts.filter((prompt) => prompt.id !== id));
-
-    fetch(`${apiHost}/api/delete_prompt`, {
-      method: 'POST',
-      headers: {
-        'Content-Type': 'application/json',
-      },
-      // send id in body only
-      body: JSON.stringify({ id: id }),
-    })
-      .then((response) => {
-        if (!response.ok) {
-          throw new Error('Failed to delete prompt');
-        }
-      })
-      .catch((error) => {
-        console.error(error);
-      });
-  };
-
-  const handleDeleteClick = (index: number, doc: Doc) => {
-    const docPath = 'indexes/' + 'local' + '/' + doc.name;
-
-    fetch(`${apiHost}/api/delete_old?path=${docPath}`, {
-      method: 'GET',
-    })
-      .then(() => {
-        // remove the image element from the DOM
-        const imageElement = document.querySelector(
-          `#img-${index}`,
-        ) as HTMLElement;
-        const parentElement = imageElement.parentNode as HTMLElement;
-        parentElement.parentNode?.removeChild(parentElement);
-      })
-      .catch((error) => console.error(error));
-  };
-
-  return (
-    <div className="p-4 pt-20 md:p-12 wa">
-      <p className="text-2xl font-bold text-eerie-black dark:text-bright-gray">Settings</p>
-      <div className="mt-6 flex flex-row items-center space-x-4 overflow-x-auto md:space-x-8 ">
-        <div className="md:hidden">
-          <button
-            onClick={() => scrollTabs(-1)}
-            className="flex h-8 w-8 items-center justify-center rounded-full border-2 border-purple-30 transition-all hover:bg-gray-100"
-          >
-            <img src={ArrowLeft} alt="left-arrow" className="h-6 w-6" />
-          </button>
-        </div>
-        <div className="flex flex-nowrap space-x-4 overflow-x-auto md:space-x-8">
-          {tabs.map((tab, index) => (
-            <button
-              key={index}
-              onClick={() => setActiveTab(tab)}
-              className={`h-9 rounded-3xl px-4 font-bold ${activeTab === tab
-                  ? 'bg-purple-3000 text-purple-30 dark:bg-dark-charcoal'
-                  : 'text-gray-6000'
-                }`}
-            >
-              {tab}
-            </button>
-          ))}
-        </div>
-        <div className="md:hidden">
-          <button
-            onClick={() => scrollTabs(1)}
-            className="flex h-8 w-8 items-center justify-center rounded-full border-2 border-purple-30 hover:bg-gray-100"
-          >
-            <img src={ArrowRight} alt="right-arrow" className="h-6 w-6" />
-          </button>
-        </div>
-      </div>
-      {renderActiveTab()}
-
-      {/* {activeTab === 'Widgets' && (
-        <Widgets
-          widgetScreenshot={widgetScreenshot}
-          onWidgetScreenshotChange={updateWidgetScreenshot}
-        />
-      )} */}
-    </div>
-  );
-
-  function scrollTabs(direction: number) {
-    const container = document.querySelector('.flex-nowrap');
-    if (container) {
-      container.scrollLeft += direction * 100; // Adjust the scroll amount as needed
-    }
-  }
-
-  function renderActiveTab() {
-    switch (activeTab) {
-      case 'General':
-        return <General />;
-      case 'Prompts':
-        return (
-          <Prompts
-            prompts={prompts}
-            selectedPrompt={selectedPrompt}
-            onSelectPrompt={(name, id, type) =>
-              dispatch(setPrompt({ name: name, id: id, type: type }))
-            }
-            setPrompts={setPrompts}
-            apiHost={apiHost}
-          />
-        );
-      case 'Documents':
-        return (
-          <Documents
-            documents={documents}
-            handleDeleteDocument={handleDeleteClick}
-          />
-        );
-      case 'Widgets':
-        return (
-          <Widgets
-            widgetScreenshot={widgetScreenshot} // Add this line
-            onWidgetScreenshotChange={updateWidgetScreenshot} // Add this line
-          />
-        );
-      default:
-        return null;
-    }
-  }
-};
-
-const General: React.FC = () => {
-  const themes = ['Light', 'Dark'];
-  const languages = ['English'];
-  const [selectedTheme, setSelectedTheme] = useState(localStorage.getItem('selectedTheme') || themes[0]);
-  const [selectedLanguage, setSelectedLanguage] = useState(languages[0]);
-
-  useEffect(() => {
-    if (selectedTheme === 'Dark') {
-      document.documentElement.classList.add('dark');
-      document.documentElement.classList.add('dark:bg-raisin-black');
-    } else {
-      document.documentElement.classList.remove('dark');
-    }
-    localStorage.setItem('selectedTheme', selectedTheme);
-  }, [selectedTheme]);
-
-  return (
-    <div className="mt-[59px]">
-      <div className="mb-4">
-        <p className="font-bold text-jet dark:text-bright-gray">Select Theme</p>
-        <Dropdown
-          options={themes}
-          selectedValue={selectedTheme}
-          onSelect={setSelectedTheme}
-        />
-      </div>
-      <div>
-        <p className="font-bold text-jet dark:text-bright-gray">Select Language</p>
-        <Dropdown
-          options={languages}
-          selectedValue={selectedLanguage}
-          onSelect={setSelectedLanguage}
-        />
-      </div>
-    </div>
-  );
-};
-
-export default Setting;
-
-const Prompts: React.FC<PromptProps> = ({
-  prompts,
-  selectedPrompt,
-  onSelectPrompt,
-  setPrompts,
-  apiHost,
-}) => {
-  const handleSelectPrompt = ({
-    name,
-    id,
-    type,
-  }: {
-    name: string;
-    id: string;
-    type: string;
-  }) => {
-    setNewPromptName(name);
-    onSelectPrompt(name, id, type);
-  };
-  const [newPromptName, setNewPromptName] = useState(selectedPrompt.name);
-  const [newPromptContent, setNewPromptContent] = useState('');
-
-  const handleAddPrompt = async () => {
-    try {
-      const response = await fetch(`${apiHost}/api/create_prompt`, {
-        method: 'POST',
-        headers: {
-          'Content-Type': 'application/json',
-        },
-        body: JSON.stringify({
-          name: newPromptName,
-          content: newPromptContent,
-        }),
-      });
-      if (!response.ok) {
-        throw new Error('Failed to add prompt');
-      }
-      const newPrompt = await response.json();
-      if (setPrompts) {
-        setPrompts([
-          ...prompts,
-          { name: newPromptName, id: newPrompt.id, type: 'private' },
-        ]);
-      }
-      onSelectPrompt(newPromptName, newPrompt.id, newPromptContent);
-      setNewPromptName(newPromptName);
-    } catch (error) {
-      console.error(error);
-    }
-  };
-
-  const handleDeletePrompt = () => {
-    setPrompts(prompts.filter((prompt) => prompt.id !== selectedPrompt.id));
-    console.log('selectedPrompt.id', selectedPrompt.id);
-
-    fetch(`${apiHost}/api/delete_prompt`, {
-      method: 'POST',
-      headers: {
-        'Content-Type': 'application/json',
-      },
-      body: JSON.stringify({ id: selectedPrompt.id }),
-    })
-      .then((response) => {
-        if (!response.ok) {
-          throw new Error('Failed to delete prompt');
-        }
-        // get 1st prompt and set it as selected
-        if (prompts.length > 0) {
-          onSelectPrompt(prompts[0].name, prompts[0].id, prompts[0].type);
-          setNewPromptName(prompts[0].name);
-        }
-      })
-      .catch((error) => {
-        console.error(error);
-      });
-  };
-
-  useEffect(() => {
-    const fetchPromptContent = async () => {
-      console.log('fetching prompt content');
-      try {
-        const response = await fetch(
-          `${apiHost}/api/get_single_prompt?id=${selectedPrompt.id}`,
-          {
-            method: 'GET',
-            headers: {
-              'Content-Type': 'application/json',
-            },
-          },
-        );
-        if (!response.ok) {
-          throw new Error('Failed to fetch prompt content');
-        }
-        const promptContent = await response.json();
-        setNewPromptContent(promptContent.content);
-      } catch (error) {
-        console.error(error);
-      }
-    };
-
-    fetchPromptContent();
-  }, [selectedPrompt]);
-
-  const handleSaveChanges = () => {
-    fetch(`${apiHost}/api/update_prompt`, {
-      method: 'POST',
-      headers: {
-        'Content-Type': 'application/json',
-      },
-      body: JSON.stringify({
-        id: selectedPrompt.id,
-        name: newPromptName,
-        content: newPromptContent,
-      }),
-    })
-      .then((response) => {
-        if (!response.ok) {
-          throw new Error('Failed to update prompt');
-        }
-        onSelectPrompt(newPromptName, selectedPrompt.id, selectedPrompt.type);
-        setNewPromptName(newPromptName);
-      })
-      .catch((error) => {
-        console.error(error);
-      });
-  };
-
-  return (
-    <div className="mt-[59px]">
-      <div className="mb-4">
-        <p className="font-semibold dark:text-bright-gray">Active Prompt</p>
-        <DropdownPrompt
-          options={prompts}
-          selectedValue={selectedPrompt.name}
-          onSelect={handleSelectPrompt}
-        />
-      </div>
-
-      <div className="mb-4">
-        <p className='dark:text-bright-gray'>Prompt name </p>{' '}
-        <p className="mb-2 text-xs italic text-eerie-black dark:text-bright-gray">
-          start by editing name
-        </p>
-        <input
-          type="text"
-          value={newPromptName}
-          placeholder="Active Prompt Name"
-          className="w-full rounded-lg border-2 p-2 dark:border-chinese-silver dark:bg-transparent dark:text-white"
-          onChange={(e) => setNewPromptName(e.target.value)}
-        />
-      </div>
-
-      <div className="mb-4">
-        <p className="mb-2 dark:text-bright-gray">Prompt content</p>
-        <textarea
-          className="h-32 w-full rounded-lg  border-2 p-2 dark:border-chinese-silver dark:text-white dark:bg-transparent"
-          value={newPromptContent}
-          onChange={(e) => setNewPromptContent(e.target.value)}
-          placeholder="Active prompt contents"
-        />
-      </div>
-
-      <div className="flex justify-between">
-        <button
-          className={`rounded-lg bg-green-500 px-4 py-2 font-bold text-white transition-all hover:bg-green-700 ${newPromptName === selectedPrompt.name
-              ? 'cursor-not-allowed opacity-50'
-              : ''
-            }`}
-          onClick={handleAddPrompt}
-          disabled={newPromptName === selectedPrompt.name}
-        >
-          Add New Prompt
-        </button>
-        <button
-          className={`rounded-lg bg-red-500 px-4 py-2 font-bold text-white transition-all hover:bg-red-700 ${selectedPrompt.type === 'public'
-              ? 'cursor-not-allowed opacity-50'
-              : ''
-            }`}
-          onClick={handleDeletePrompt}
-          disabled={selectedPrompt.type === 'public'}
-        >
-          Delete Prompt
-        </button>
-        <button
-          className={`rounded-lg bg-blue-500 px-4 py-2 font-bold text-white transition-all hover:bg-blue-700 ${selectedPrompt.type === 'public'
-              ? 'cursor-not-allowed opacity-50'
-              : ''
-            }`}
-          onClick={handleSaveChanges}
-          disabled={selectedPrompt.type === 'public'}
-        >
-          Save Changes
-        </button>
-      </div>
-    </div>
-  );
-};
-
-function DropdownPrompt({
-  options,
-  selectedValue,
-  onSelect,
-}: {
-  options: { name: string; id: string; type: string }[];
-  selectedValue: string;
-  onSelect: (value: { name: string; id: string; type: string }) => void;
-}) {
-  const [isOpen, setIsOpen] = useState(false);
-
-  return (
-    <div className="relative mt-2 w-32">
-      <button
-        onClick={() => setIsOpen(!isOpen)}
-        className="flex w-full cursor-pointer items-center rounded-xl border-2 dark:border-chinese-silver bg-white p-3 dark:bg-transparent"
-      >
-        <span className="flex-1 overflow-hidden text-ellipsis dark:text-bright-gray">
-          {selectedValue}
-        </span>
-        <img
-          src={Arrow2}
-          alt="arrow"
-          className={`transform ${isOpen ? 'rotate-180' : 'rotate-0'
-            } h-3 w-3 transition-transform`}
-        />
-      </button>
-      {isOpen && (
-        <div className="absolute left-0 right-0 z-50 -mt-3 rounded-b-xl border-2 dark:border-chinese-silver bg-white dark:bg-dark-charcoal  shadow-lg">
-          {options.map((option, index) => (
-            <div
-              key={index}
-              className="flex cursor-pointer items-center justify-between hover:bg-gray-100 dark:hover:bg-purple-taupe dark:text-bright-gray "
-            >
-              <span
-                onClick={() => {
-                  onSelect(option);
-                  setIsOpen(false);
-                }}
-                className="ml-2 flex-1 overflow-hidden overflow-ellipsis whitespace-nowrap py-3"
-              >
-                {option.name}
-              </span>
-            </div>
-          ))}
-        </div>
-      )}
-    </div>
-  );
-}
-
-function Dropdown({
-  options,
-  selectedValue,
-  onSelect,
-  showDelete,
-  onDelete,
-}: {
-  options: string[];
-  selectedValue: string;
-  onSelect: (value: string) => void;
-  showDelete?: boolean; // optional
-  onDelete?: (value: string) => void; // optional
-}) {
-  const [isOpen, setIsOpen] = useState(false);
-
-  return (
-    <div className="relative mt-2 w-32">
-      <button
-        onClick={() => setIsOpen(!isOpen)}
-        className="flex w-full cursor-pointer items-center rounded-xl border-2 dark:border-chinese-silver bg-white p-3 dark:bg-transparent"
-      >
-        <span className="flex-1 overflow-hidden text-ellipsis dark:text-bright-gray">
-          {selectedValue}
-        </span>
-        <img
-          src={Arrow2}
-          alt="arrow"
-          className={`transform ${isOpen ? 'rotate-180' : 'rotate-0'
-            } h-3 w-3 transition-transform`}
-        />
-      </button>
-      {isOpen && (
-        <div className="absolute left-0 right-0 z-50 -mt-3 rounded-b-xl border-2 bg-white dark:border-chinese-silver dark:bg-dark-charcoal shadow-lg">
-          {options.map((option, index) => (
-            <div
-              key={index}
-              className="flex cursor-pointer items-center justify-between hover:bg-gray-100 dark:hover:bg-purple-taupe"
-            >
-              <span
-                onClick={() => {
-                  onSelect(option);
-                  setIsOpen(false);
-                }}
-                className="ml-2 flex-1 overflow-hidden overflow-ellipsis whitespace-nowrap py-3 dark:text-light-gray"
-              >
-                {option}
-              </span>
-              {showDelete && onDelete && (
-                <button onClick={() => onDelete(option)} className="p-2">
-                  {/* Icon or text for delete button */}
-                  Delete
-                </button>
-              )}
-            </div>
-          ))}
-        </div>
-      )}
-    </div>
-  );
-}
-
-type AddPromptModalProps = {
-  newPromptName: string;
-  onNewPromptNameChange: (name: string) => void;
-  onAddPrompt: () => void;
-  onClose: () => void;
-};
-
-const AddPromptModal: React.FC<AddPromptModalProps> = ({
-  newPromptName,
-  onNewPromptNameChange,
-  onAddPrompt,
-  onClose,
-}) => {
-  return (
-    <div className="fixed top-0 left-0 flex h-screen w-screen items-center justify-center bg-gray-900 bg-opacity-50">
-      <div className="rounded-3xl bg-white p-4">
-        <p className="mb-2 text-2xl font-bold text-jet">Add New Prompt</p>
-        <input
-          type="text"
-          placeholder="Enter Prompt Name"
-          value={newPromptName}
-          onChange={(e) => onNewPromptNameChange(e.target.value)}
-          className="mb-4 w-full rounded-3xl border-2 dark:border-chinese-silver p-2"
-        />
-        <button
-          onClick={onAddPrompt}
-          className="rounded-3xl bg-purple-300 px-4 py-2 font-bold text-white transition-all hover:bg-purple-600"
-        >
-          Save
-        </button>
-        <button
-          onClick={onClose}
-          className="mt-4 rounded-3xl px-4 py-2 font-bold text-red-500"
-        >
-          Cancel
-        </button>
-      </div>
-    </div>
-  );
-};
-
-type DocumentsProps = {
-  documents: Doc[] | null;
-  handleDeleteDocument: (index: number, document: Doc) => void;
-};
-
-const Documents: React.FC<DocumentsProps> = ({
-  documents,
-  handleDeleteDocument,
-}) => {
-  return (
-    <div className="mt-8">
-      <div className="flex flex-col">
-        {/* <h2 className="text-xl font-semibold">Documents</h2> */}
-
-        <div className="mt-[27px] overflow-x-auto border dark:border-chinese-silver rounded-xl w-max">
-          <table className="block w-full table-auto content-center justify-center text-center dark:text-bright-gray" >
-            <thead>
-              <tr>
-                <th className="border-r p-4 md:w-[244px]">Document Name</th>
-                <th className="border-r px-4 py-2 w-[244px]">Vector Date</th>
-                <th className="border-r px-4 py-2 w-[244px]">Type</th>
-                <th className="px-4 py-2"></th>
-              </tr>
-            </thead>
-            <tbody>
-              {documents &&
-                documents.map((document, index) => (
-                  <tr key={index}>
-                    <td className="border-r border-t px-4 py-2">{document.name}</td>
-                    <td className="border-r border-t px-4 py-2">{document.date}</td>
-                    <td className="border-r border-t px-4 py-2">
-                      {document.location === 'remote'
-                        ? 'Pre-loaded'
-                        : 'Private'}
-                    </td>
-                    <td className="border-t px-4 py-2">
-                      {document.location !== 'remote' && (
-                        <img
-                          src={Trash}
-                          alt="Delete"
-                          className="h-4 w-4 cursor-pointer hover:opacity-50"
-                          id={`img-${index}`}
-                          onClick={(event) => {
-                            event.stopPropagation();
-                            handleDeleteDocument(index, document);
-                          }}
-                        />
-                      )}
-                    </td>
-                  </tr>
-                ))}
-            </tbody>
-          </table>
-        </div>
-        {/* <button
-          onClick={toggleAddDocumentModal}
-          className="mt-10 w-32 rounded-lg bg-purple-300 px-4 py-2 font-bold text-white transition-all hover:bg-purple-600"
-        >
-          Add New
-        </button> */}
-      </div>
-
-      {/* {isAddDocumentModalOpen && (
-        <AddDocumentModal
-          newDocument={newDocument}
-          onNewDocumentChange={setNewDocument}
-          onAddDocument={addDocument}
-          onClose={toggleAddDocumentModal}
-        />
-      )} */}
-    </div>
-  );
-};
-
-type Document = {
-  name: string;
-  vectorDate: string;
-  vectorLocation: string;
-};
-
-// Modal for adding a new document
-type AddDocumentModalProps = {
-  newDocument: Document;
-  onNewDocumentChange: (document: Document) => void;
-  onAddDocument: () => void;
-  onClose: () => void;
-};
-
-const AddDocumentModal: React.FC<AddDocumentModalProps> = ({
-  newDocument,
-  onNewDocumentChange,
-  onAddDocument,
-  onClose,
-}) => {
-  return (
-    <div className="fixed top-0 left-0 flex h-screen w-screen items-center justify-center bg-gray-900 bg-opacity-50">
-      <div className="w-[50%] rounded-lg bg-white p-4">
-        <p className="mb-2 text-2xl font-bold text-jet">Add New Document</p>
-        <input
-          type="text"
-          placeholder="Document Name"
-          value={newDocument.name}
-          onChange={(e) =>
-            onNewDocumentChange({ ...newDocument, name: e.target.value })
-          }
-          className="mb-4 w-full rounded-lg border-2 p-2"
-        />
-        <input
-          type="text"
-          placeholder="Vector Date"
-          value={newDocument.vectorDate}
-          onChange={(e) =>
-            onNewDocumentChange({ ...newDocument, vectorDate: e.target.value })
-          }
-          className="mb-4 w-full rounded-lg border-2 p-2"
-        />
-        <input
-          type="text"
-          placeholder="Vector Location"
-          value={newDocument.vectorLocation}
-          onChange={(e) =>
-            onNewDocumentChange({
-              ...newDocument,
-              vectorLocation: e.target.value,
-            })
-          }
-          className="mb-4 w-full rounded-lg border-2 p-2"
-        />
-        <button
-          onClick={onAddDocument}
-          className="rounded-lg bg-purple-300 px-4 py-2 font-bold text-white transition-all hover:bg-purple-600"
-        >
-          Save
-        </button>
-        <button
-          onClick={onClose}
-          className="mt-4 rounded-lg px-4 py-2 font-bold text-red-500"
-        >
-          Cancel
-        </button>
-      </div>
-    </div>
-  );
-};
-
-const Widgets: React.FC<{
-  widgetScreenshot: File | null;
-  onWidgetScreenshotChange: (screenshot: File | null) => void;
-}> = ({ widgetScreenshot, onWidgetScreenshotChange }) => {
-  const widgetSources = ['Source 1', 'Source 2', 'Source 3'];
-  const widgetMethods = ['Method 1', 'Method 2', 'Method 3'];
-  const widgetTypes = ['Type 1', 'Type 2', 'Type 3'];
-
-  const [selectedWidgetSource, setSelectedWidgetSource] = useState(
-    widgetSources[0],
-  );
-  const [selectedWidgetMethod, setSelectedWidgetMethod] = useState(
-    widgetMethods[0],
-  );
-  const [selectedWidgetType, setSelectedWidgetType] = useState(widgetTypes[0]);
-
-  // const [widgetScreenshot, setWidgetScreenshot] = useState<File | null>(null);
-  const [widgetCode, setWidgetCode] = useState<string>(''); // Your widget code state
-
-  const handleScreenshotChange = (
-    event: React.ChangeEvent<HTMLInputElement>,
-  ) => {
-    const files = event.target.files;
-
-    if (files && files.length > 0) {
-      const selectedScreenshot = files[0];
-      onWidgetScreenshotChange(selectedScreenshot); // Update the screenshot in the parent component
-    }
-  };
-
-  const handleCopyToClipboard = () => {
-    // Create a new textarea element to select the text
-    const textArea = document.createElement('textarea');
-    textArea.value = widgetCode;
-    document.body.appendChild(textArea);
-
-    // Select and copy the text
-    textArea.select();
-    document.execCommand('copy');
-
-    // Clean up the textarea element
-    document.body.removeChild(textArea);
-  };
-
-  return (
-    <div>
-      <div className="mt-[59px]">
-        <p className="font-bold text-jet">Widget Source</p>
-        <Dropdown
-          options={widgetSources}
-          selectedValue={selectedWidgetSource}
-          onSelect={setSelectedWidgetSource}
-        />
-      </div>
-      <div className="mt-5">
-        <p className="font-bold text-jet">Widget Method</p>
-        <Dropdown
-          options={widgetMethods}
-          selectedValue={selectedWidgetMethod}
-          onSelect={setSelectedWidgetMethod}
-        />
-      </div>
-      <div className="mt-5">
-        <p className="font-bold text-jet">Widget Type</p>
-        <Dropdown
-          options={widgetTypes}
-          selectedValue={selectedWidgetType}
-          onSelect={setSelectedWidgetType}
-        />
-      </div>
-      <div className="mt-6">
-        <p className="font-bold text-jet">Widget Code Snippet</p>
-        <textarea
-          rows={4}
-          value={widgetCode}
-          onChange={(e) => setWidgetCode(e.target.value)}
-          className="mt-3 w-full rounded-lg border-2 p-2"
-        />
-      </div>
-      <div className="mt-1">
-        <button
-          onClick={handleCopyToClipboard}
-          className="rounded-lg bg-blue-400 px-2 py-2 font-bold text-white transition-all hover:bg-blue-600"
-        >
-          Copy
-        </button>
-      </div>
-
-      <div className="mt-4">
-        <p className="text-lg font-semibold">Widget Screenshot</p>
-        <input type="file" accept="image/*" onChange={handleScreenshotChange} />
-      </div>
-
-      {widgetScreenshot && (
-        <div className="mt-4">
-          <img
-            src={URL.createObjectURL(widgetScreenshot)}
-            alt="Widget Screenshot"
-            className="max-w-full rounded-lg border border-gray-300"
-          />
-        </div>
-      )}
-    </div>
-  );
-};

frontend/src/components/Dropdown.tsx

@@ -0,0 +1,135 @@
+import React from 'react';
+import Arrow2 from '../assets/dropdown-arrow.svg';
+import Edit from '../assets/edit.svg';
+import Trash from '../assets/trash.svg';
+
+function Dropdown({
+  options,
+  selectedValue,
+  onSelect,
+  size = 'w-32',
+  rounded = 'xl',
+  showEdit,
+  onEdit,
+  showDelete,
+  onDelete,
+  placeholder,
+}: {
+  options:
+    | string[]
+    | { name: string; id: string; type: string }[]
+    | { label: string; value: string }[];
+  selectedValue: string | { label: string; value: string } | null;
+  onSelect:
+    | ((value: string) => void)
+    | ((value: { name: string; id: string; type: string }) => void)
+    | ((value: { label: string; value: string }) => void);
+  size?: string;
+  rounded?: 'xl' | '3xl';
+  showEdit?: boolean;
+  onEdit?: (value: { name: string; id: string; type: string }) => void;
+  showDelete?: boolean;
+  onDelete?: (value: string) => void;
+  placeholder?: string;
+}) {
+  const [isOpen, setIsOpen] = React.useState(false);
+  return (
+    <div
+      className={[
+        typeof selectedValue === 'string'
+          ? 'relative mt-2'
+          : 'relative align-middle',
+        size,
+      ].join(' ')}
+    >
+      <button
+        onClick={() => setIsOpen(!isOpen)}
+        className={`flex w-full cursor-pointer items-center justify-between border-2 border-silver bg-white px-5 py-3 dark:border-chinese-silver dark:bg-transparent ${
+          isOpen ? `rounded-t-${rounded}` : `rounded-${rounded}`
+        }`}
+      >
+        {typeof selectedValue === 'string' ? (
+          <span className="overflow-hidden text-ellipsis dark:text-bright-gray">
+            {selectedValue}
+          </span>
+        ) : (
+          <span
+            className={`overflow-hidden text-ellipsis dark:text-bright-gray ${
+              !selectedValue && 'text-silver dark:text-gray-400'
+            }`}
+          >
+            {selectedValue
+              ? selectedValue.label
+              : placeholder
+              ? placeholder
+              : 'From URL'}
+          </span>
+        )}
+        <img
+          src={Arrow2}
+          alt="arrow"
+          className={`transform ${
+            isOpen ? 'rotate-180' : 'rotate-0'
+          } h-3 w-3 transition-transform`}
+        />
+      </button>
+      {isOpen && (
+        <div className="absolute left-0 right-0 z-20 -mt-1 max-h-40 overflow-y-auto rounded-b-xl border-2 border-silver bg-white shadow-lg dark:border-chinese-silver dark:bg-dark-charcoal">
+          {options.map((option: any, index) => (
+            <div
+              key={index}
+              className="hover:eerie-black flex cursor-pointer items-center justify-between hover:bg-gray-100 dark:hover:bg-purple-taupe"
+            >
+              <span
+                onClick={() => {
+                  onSelect(option);
+                  setIsOpen(false);
+                }}
+                className="ml-5 flex-1 overflow-hidden overflow-ellipsis whitespace-nowrap py-3 dark:text-light-gray"
+              >
+                {typeof option === 'string'
+                  ? option
+                  : option.name
+                  ? option.name
+                  : option.label}
+              </span>
+              {showEdit && onEdit && (
+                <img
+                  src={Edit}
+                  alt="Edit"
+                  className="mr-4 h-4 w-4 cursor-pointer hover:opacity-50"
+                  onClick={() => {
+                    onEdit({
+                      id: option.id,
+                      name: option.name,
+                      type: option.type,
+                    });
+                    setIsOpen(false);
+                  }}
+                />
+              )}
+              {showDelete && onDelete && (
+                <button
+                  onClick={() => onDelete(option.id)}
+                  disabled={option.type === 'public'}
+                >
+                  <img
+                    src={Trash}
+                    alt="Delete"
+                    className={`mr-2 h-4 w-4 cursor-pointer hover:opacity-50 ${
+                      option.type === 'public'
+                        ? 'cursor-not-allowed opacity-50'
+                        : ''
+                    }`}
+                  />
+                </button>
+              )}
+            </div>
+          ))}
+        </div>
+      )}
+    </div>
+  );
+}
+
+export default Dropdown;

frontend/src/components/SourceDropdown.tsx

@@ -0,0 +1,116 @@
+import Trash from '../assets/trash.svg';
+import Arrow2 from '../assets/dropdown-arrow.svg';
+import { Doc } from '../preferences/preferenceApi';
+import { useDispatch } from 'react-redux';
+
+type Props = {
+  options: Doc[] | null;
+  selectedDocs: Doc | null;
+  setSelectedDocs: any;
+  isDocsListOpen: boolean;
+  setIsDocsListOpen: React.Dispatch<React.SetStateAction<boolean>>;
+  handleDeleteClick: any;
+};
+
+function SourceDropdown({
+  options,
+  setSelectedDocs,
+  selectedDocs,
+  setIsDocsListOpen,
+  isDocsListOpen,
+  handleDeleteClick,
+}: Props) {
+  const dispatch = useDispatch();
+  const embeddingsName =
+    import.meta.env.VITE_EMBEDDINGS_NAME ||
+    'huggingface_sentence-transformers/all-mpnet-base-v2';
+
+  const handleEmptyDocumentSelect = () => {
+    dispatch(setSelectedDocs(null));
+    setIsDocsListOpen(false);
+  };
+
+  return (
+    <div className="relative w-5/6 rounded-3xl">
+      <button
+        onClick={() => setIsDocsListOpen(!isDocsListOpen)}
+        className={`flex w-full cursor-pointer items-center  border-2 bg-white p-3 dark:border-chinese-silver dark:bg-transparent ${
+          isDocsListOpen ? 'rounded-t-3xl' : 'rounded-3xl'
+        }`}
+      >
+        <span className="ml-1 mr-2 flex-1 overflow-hidden text-ellipsis text-left dark:text-bright-gray">
+          <div className="flex flex-row gap-2">
+            <p className="max-w-3/4 truncate whitespace-nowrap">
+              {selectedDocs?.name || ''}
+            </p>
+            <p className="flex flex-col items-center justify-center">
+              {selectedDocs?.version}
+            </p>
+          </div>
+        </span>
+        <img
+          src={Arrow2}
+          alt="arrow"
+          className={`transform ${
+            isDocsListOpen ? 'rotate-180' : 'rotate-0'
+          } h-3 w-3 transition-transform`}
+        />
+      </button>
+      {isDocsListOpen && (
+        <div className="absolute left-0 right-0 z-50 -mt-1 max-h-40 overflow-y-auto rounded-b-xl border-2 bg-white  shadow-lg dark:border-chinese-silver dark:bg-dark-charcoal">
+          {options ? (
+            options.map((option: any, index: number) => {
+              if (option.model === embeddingsName) {
+                return (
+                  <div
+                    key={index}
+                    className="flex cursor-pointer items-center justify-between hover:bg-gray-100 dark:text-bright-gray dark:hover:bg-purple-taupe"
+                    onClick={() => {
+                      dispatch(setSelectedDocs(option));
+                      setIsDocsListOpen(false);
+                    }}
+                  >
+                    <span
+                      onClick={() => {
+                        setIsDocsListOpen(false);
+                      }}
+                      className="ml-4 flex-1 overflow-hidden overflow-ellipsis whitespace-nowrap py-3"
+                    >
+                      {option.name}
+                    </span>
+                    {option.location === 'local' && (
+                      <img
+                        src={Trash}
+                        alt="Delete"
+                        className="mr-4 h-4 w-4 cursor-pointer hover:opacity-50"
+                        id={`img-${index}`}
+                        onClick={(event) => {
+                          event.stopPropagation();
+                          handleDeleteClick(index, option);
+                        }}
+                      />
+                    )}
+                  </div>
+                );
+              }
+            })
+          ) : (
+            <div className="h-10 w-full cursor-pointer  border-b-[1px] hover:bg-gray-100 dark:border-b-purple-taupe dark:hover:bg-purple-taupe">
+              <p className="ml-5 py-3">No default documentation.</p>
+            </div>
+          )}
+          <div
+            className="flex cursor-pointer items-center justify-between hover:bg-gray-100 dark:text-bright-gray dark:hover:bg-purple-taupe"
+            onClick={handleEmptyDocumentSelect}
+          >
+            <span className="ml-4 flex-1 overflow-hidden overflow-ellipsis whitespace-nowrap py-3">
+              Empty
+            </span>
+          </div>
+        </div>
+      )}
+    </div>
+  );
+}
+
+export default SourceDropdown;

frontend/src/conversation/Conversation.tsx

@@ -1,5 +1,6 @@
 import { Fragment, useEffect, useRef, useState } from 'react';
 import { useDispatch, useSelector } from 'react-redux';
+import { useDarkTheme } from '../hooks';
 import Hero from '../Hero';
 import { AppDispatch } from '../store';
 import ConversationBubble from './ConversationBubble';
@@ -11,23 +12,27 @@ import {
   updateQuery,
 } from './conversationSlice';
 import Send from './../assets/send.svg';
-import SendDark from './../assets/send_dark.svg'
+import SendDark from './../assets/send_dark.svg';
 import Spinner from './../assets/spinner.svg';
 import { FEEDBACK, Query } from './conversationModels';
 import { sendFeedback } from './conversationApi';
 import ArrowDown from './../assets/arrow-down.svg';
-
 export default function Conversation() {
   const queries = useSelector(selectQueries);
   const status = useSelector(selectStatus);
   const dispatch = useDispatch<AppDispatch>();
   const endMessageRef = useRef<HTMLDivElement>(null);
   const inputRef = useRef<HTMLDivElement>(null);
-  const isDarkTheme = document.documentElement.classList.contains('dark');
+  const [isDarkTheme] = useDarkTheme();
   const [hasScrolledToLast, setHasScrolledToLast] = useState(true);
+  const fetchStream = useRef<any>(null);
+  const [eventInterrupt, setEventInterrupt] = useState(false);
 
+  const handleUserInterruption = () => {
+    if (!eventInterrupt && status === 'loading') setEventInterrupt(true);
+  };
   useEffect(() => {
-    scrollIntoView();
+    !eventInterrupt && scrollIntoView();
   }, [queries.length, queries[queries.length - 1]]);
 
   useEffect(() => {
@@ -37,6 +42,14 @@ export default function Conversation() {
     }
   }, []);
 
+  useEffect(() => {
+    return () => {
+      if (status !== 'idle') {
+        fetchStream.current && fetchStream.current.abort(); //abort previous stream
+      }
+    };
+  }, [status]);
+
   useEffect(() => {
     const observerCallback: IntersectionObserverCallback = (entries) => {
       entries.forEach((entry) => {
@@ -67,10 +80,10 @@ export default function Conversation() {
   const handleQuestion = (question: string) => {
     question = question.trim();
     if (question === '') return;
+    setEventInterrupt(false);
     dispatch(addQuery({ prompt: question }));
-    dispatch(fetchAnswer({ question }));
+    fetchStream.current = dispatch(fetchAnswer({ question }));
   };
-
   const handleFeedback = (query: Query, feedback: FEEDBACK, index: number) => {
     const prevFeedback = query.feedback;
     dispatch(updateQuery({ index, query: { feedback } }));
@@ -117,12 +130,16 @@ export default function Conversation() {
   };
 
   return (
-    <div className="flex flex-col justify-center p-4 md:flex-row">
+    <div
+      onWheel={handleUserInterruption}
+      onTouchMove={handleUserInterruption}
+      className="flex w-full flex-col justify-center p-4 md:flex-row"
+    >
       {queries.length > 0 && !hasScrolledToLast && (
         <button
           onClick={scrollIntoView}
           aria-label="scroll to bottom"
-          className="fixed bottom-32 right-14 z-10 flex h-7 w-7  items-center justify-center rounded-full border-[0.5px] border-gray-alpha bg-gray-100 dark:bg-purple-taupe bg-opacity-50 md:h-9 md:w-9 md:bg-opacity-100 "
+          className="fixed bottom-32 right-14 z-10 flex h-7 w-7  items-center justify-center rounded-full border-[0.5px] border-gray-alpha bg-gray-100 bg-opacity-50 dark:bg-purple-taupe md:h-9 md:w-9 md:bg-opacity-100 "
         >
           <img
             src={ArrowDown}
@@ -133,12 +150,12 @@ export default function Conversation() {
       )}
 
       {queries.length > 0 && (
-        <div className="mt-20 flex flex-col transition-all md:w-3/4">
+        <div className="mt-20 mb-9 flex flex-col transition-all md:w-3/4">
           {queries.map((query, index) => {
             return (
               <Fragment key={index}>
                 <ConversationBubble
-                  className={'last:mb-27 mb-7'}
+                  className={'mb-7 last:mb-28'}
                   key={`${index}QUESTION`}
                   message={query.prompt}
                   type="QUESTION"
@@ -150,10 +167,8 @@ export default function Conversation() {
           })}
         </div>
       )}
-      {queries.length === 0 && (
-        <Hero className="mt-24 h-[100vh] md:mt-52"></Hero>
-      )}
-      <div className="relative bottom-0 flex w-10/12 flex-col items-end self-center bg-white dark:bg-raisin-black pt-3 md:fixed md:w-[65%]">
+      {queries.length === 0 && <Hero className="mt-24 md:mt-52"></Hero>}
+      <div className="absolute bottom-0 flex w-11/12 flex-col items-end self-center bg-white pt-4 dark:bg-raisin-black md:fixed md:w-[65%]">
         <div className="flex h-full w-full">
           <div
             id="inputbox"
@@ -162,7 +177,7 @@ export default function Conversation() {
             placeholder="Type your message here..."
             contentEditable
             onPaste={handlePaste}
-            className={`border-000000 overflow-x-hidden; max-h-24 min-h-[2.6rem] w-full overflow-y-auto whitespace-pre-wrap rounded-3xl border bg-white dark:bg-transparent dark:text-bright-gray py-2 pl-4 pr-9 text-base leading-7 opacity-100 focus:outline-none`}
+            className={`border-000000 max-h-24 min-h-[2.6rem] w-full overflow-y-auto overflow-x-hidden whitespace-pre-wrap rounded-3xl border bg-white py-2 pl-4 pr-9 text-base leading-7 opacity-100 focus:outline-none dark:bg-raisin-black dark:text-bright-gray`}
             onKeyDown={(e) => {
               if (e.key === 'Enter' && !e.shiftKey) {
                 e.preventDefault();
@@ -193,9 +208,8 @@ export default function Conversation() {
             </div>
           )}
         </div>
-        <p className="text-gray-595959 dark:text-bright-gray w-[100vw] self-center bg-transparent p-5 text-center text-xs md:w-full">
-          This is a chatbot that uses the GPT-3, Faiss and LangChain to answer
-          questions.
+        <p className="text-gray-595959 w-[100vw] self-center bg-white bg-transparent p-5 text-center text-xs dark:bg-raisin-black dark:text-bright-gray md:w-full">
+          DocsGPT uses GenAI, please review critial information using sources.
         </p>
       </div>
     </div>

frontend/src/conversation/ConversationBubble.tsx

@@ -63,9 +63,9 @@ const ConversationBubble = forwardRef<
     bubble = (
       <div
         ref={ref}
-        className={`flex self-start flex-wrap ${className} group flex-col pr-20  dark:text-bright-gray`}
+        className={`flex flex-wrap self-start ${className} group flex-col pr-20  dark:text-bright-gray`}
       >
-        <div className="flex self-start flex-wrap lg:flex-nowrap">
+        <div className="flex flex-wrap self-start lg:flex-nowrap">
           <Avatar
             className="mt-2 h-12 w-12 text-2xl"
             avatar={
@@ -78,10 +78,11 @@ const ConversationBubble = forwardRef<
           />
 
           <div
-            className={`ml-2 lg:max-w-[50vw] md:max-w-[70vw] max-w-[90vw] mr-5 flex rounded-3xl bg-gray-1000 dark:bg-gun-metal p-3.5 ${type === 'ERROR'
-              ? 'flex-row items-center rounded-full border border-transparent bg-[#FFE7E7] p-2 py-5 text-sm font-normal text-red-3000  dark:border-red-2000 dark:text-white'
-              : 'flex-col rounded-3xl'
-              }`}
+            className={`ml-2 mr-5 flex max-w-[90vw] rounded-3xl bg-gray-1000 p-3.5 dark:bg-gun-metal md:max-w-[70vw] lg:max-w-[50vw] ${
+              type === 'ERROR'
+                ? 'flex-row items-center rounded-full border border-transparent bg-[#FFE7E7] p-2 py-5 text-sm font-normal text-red-3000  dark:border-red-2000 dark:text-white'
+                : 'flex-col rounded-3xl'
+            }`}
           >
             {type === 'ERROR' && (
               <img src={Alert} alt="alert" className="mr-2 inline" />
@@ -159,7 +160,10 @@ const ConversationBubble = forwardRef<
             >
               {message}
             </ReactMarkdown>
-            {DisableSourceFE || type === 'ERROR' ? null : (
+            {DisableSourceFE ||
+            type === 'ERROR' ||
+            !sources ||
+            sources.length === 0 ? null : (
               <>
                 <span className="mt-3 h-px w-full bg-[#DEDEDE]"></span>
                 <div className="mt-3 flex w-full flex-row flex-wrap items-center justify-start gap-2">
@@ -168,19 +172,21 @@ const ConversationBubble = forwardRef<
                     {sources?.map((source, index) => (
                       <div
                         key={index}
-                        className={`max-w-fit cursor-pointer rounded-[28px] py-1 px-4 ${openSource === index
-                          ? 'bg-[#007DFF]'
-                          : 'bg-[#D7EBFD] hover:bg-[#BFE1FF]'
-                          }`}
+                        className={`max-w-fit cursor-pointer rounded-[28px] py-1 px-4 ${
+                          openSource === index
+                            ? 'bg-[#007DFF]'
+                            : 'bg-[#D7EBFD] hover:bg-[#BFE1FF]'
+                        }`}
                         onClick={() =>
                           setOpenSource(openSource === index ? null : index)
                         }
                       >
                         <p
-                          className={`truncate text-center text-base font-medium ${openSource === index
-                            ? 'text-white'
-                            : 'text-[#007DFF]'
-                            }`}
+                          className={`truncate text-center text-base font-medium ${
+                            openSource === index
+                              ? 'text-white'
+                              : 'text-[#007DFF]'
+                          }`}
                         >
                           {index + 1}. {source.title.substring(0, 45)}
                         </p>
@@ -191,16 +197,19 @@ const ConversationBubble = forwardRef<
               </>
             )}
           </div>
-          <div className='flex justify-center'>
+          <div className="flex justify-center">
             <div
-              className={`relative mr-5  items-center justify-center lg:invisible block 
-            ${type !== 'ERROR' ? 'group-hover:lg:visible' : ''
-                }`}
+              className={`relative mr-5  block items-center justify-center lg:invisible 
+            ${type !== 'ERROR' ? 'group-hover:lg:visible' : ''}`}
             >
               <div className="absolute left-2 top-4">
                 <div
                   className={`flex items-center justify-center rounded-full p-2 
-                ${isCopyHovered ? 'bg-[#EEEEEE] dark:bg-purple-taupe' : 'bg-[#ffffff] dark:bg-transparent'}`}
+                ${
+                  isCopyHovered
+                    ? 'bg-[#EEEEEE] dark:bg-purple-taupe'
+                    : 'bg-[#ffffff] dark:bg-transparent'
+                }`}
                 >
                   {copied ? (
                     <CheckMark
@@ -222,22 +231,29 @@ const ConversationBubble = forwardRef<
               </div>
             </div>
             <div
-              className={`relative mr-5 flex items-center justify-center ${!isLikeClicked ? 'lg:invisible' : ''
-                } ${feedback === 'LIKE' || type !== 'ERROR'
+              className={`relative mr-5 flex items-center justify-center ${
+                !isLikeClicked ? 'lg:invisible' : ''
+              } ${
+                feedback === 'LIKE' || type !== 'ERROR'
                   ? 'group-hover:lg:visible'
                   : ''
-                }`}
+              }`}
             >
               <div className="absolute left-6 top-4">
                 <div
-                  className={`flex items-center justify-center rounded-full p-2 dark:bg-transparent ${isLikeHovered ? 'bg-[#EEEEEE] dark:bg-purple-taupe' : 'bg-[#ffffff] dark:bg-transparent'}`}
+                  className={`flex items-center justify-center rounded-full p-2 dark:bg-transparent ${
+                    isLikeHovered
+                      ? 'bg-[#EEEEEE] dark:bg-purple-taupe'
+                      : 'bg-[#ffffff] dark:bg-transparent'
+                  }`}
                 >
                   <Like
                     className={`cursor-pointer 
-                  ${isLikeClicked || feedback === 'LIKE'
-                        ? 'fill-white-3000 stroke-purple-30 dark:fill-transparent'
-                        : 'fill-none  stroke-gray-4000'
-                      }`}
+                  ${
+                    isLikeClicked || feedback === 'LIKE'
+                      ? 'fill-white-3000 stroke-purple-30 dark:fill-transparent'
+                      : 'fill-none  stroke-gray-4000'
+                  }`}
                     onClick={() => {
                       handleFeedback?.('LIKE');
                       setIsLikeClicked(true);
@@ -250,22 +266,28 @@ const ConversationBubble = forwardRef<
               </div>
             </div>
             <div
-              className={`mr-13 relative flex items-center justify-center ${!isDislikeClicked ? 'lg:invisible' : ''
-                } ${feedback === 'DISLIKE' || type !== 'ERROR'
+              className={`mr-13 relative flex items-center justify-center ${
+                !isDislikeClicked ? 'lg:invisible' : ''
+              } ${
+                feedback === 'DISLIKE' || type !== 'ERROR'
                   ? 'group-hover:lg:visible'
                   : ''
-                }`}
+              }`}
             >
               <div className="absolute left-10 top-4">
                 <div
-
-                  className={`flex items-center justify-center rounded-full p-2 ${isDislikeHovered ? 'bg-[#EEEEEE] dark:bg-purple-taupe' : 'bg-[#ffffff] dark:bg-transparent'}`}
+                  className={`flex items-center justify-center rounded-full p-2 ${
+                    isDislikeHovered
+                      ? 'bg-[#EEEEEE] dark:bg-purple-taupe'
+                      : 'bg-[#ffffff] dark:bg-transparent'
+                  }`}
                 >
                   <Dislike
-                    className={`cursor-pointer ${isDislikeClicked || feedback === 'DISLIKE'
-                      ? 'fill-white-3000 dark:fill-transparent stroke-red-2000'
-                      : 'fill-none  stroke-gray-4000'
-                      }`}
+                    className={`cursor-pointer ${
+                      isDislikeClicked || feedback === 'DISLIKE'
+                        ? 'fill-white-3000 stroke-red-2000 dark:fill-transparent'
+                        : 'fill-none  stroke-gray-4000'
+                    }`}
                     onClick={() => {
                       handleFeedback?.('DISLIKE');
                       setIsDislikeClicked(true);
@@ -281,12 +303,12 @@ const ConversationBubble = forwardRef<
         </div>
 
         {sources && openSource !== null && sources[openSource] && (
-          <div className="ml-10 mt-12 lg:mt-2 max-w-[300px] sm:max-w-[800px] break-words rounded-xl bg-blue-200 dark:bg-gun-metal p-2">
+          <div className="ml-10 mt-12 max-w-[300px] break-words rounded-xl bg-blue-200 p-2 dark:bg-gun-metal sm:max-w-[800px] lg:mt-2">
             <p className="m-1 w-3/4 truncate text-xs text-gray-500 dark:text-bright-gray">
               Source: {sources[openSource].title}
             </p>
 
-            <div className="m-2 rounded-xl border-2 border-gray-200 dark:border-chinese-silver bg-white dark:bg-dark-charcoal p-2">
+            <div className="m-2 rounded-xl border-2 border-gray-200 bg-white p-2 dark:border-chinese-silver dark:bg-dark-charcoal">
               <p className="text-break text-black dark:text-bright-gray">
                 {sources[openSource].text}
               </p>

frontend/src/conversation/ConversationTile.tsx

@@ -4,7 +4,7 @@ import Edit from '../assets/edit.svg';
 import Exit from '../assets/exit.svg';
 import Message from '../assets/message.svg';
 import MessageDark from '../assets/message-dark.svg';
-
+import { useDarkTheme } from '../hooks';
 import CheckMark2 from '../assets/checkMark2.svg';
 import Trash from '../assets/trash.svg';
 
@@ -29,7 +29,7 @@ export default function ConversationTile({
 }: ConversationTileProps) {
   const conversationId = useSelector(selectConversationId);
   const tileRef = useRef<HTMLInputElement>(null);
-  const isDarkTheme = document.documentElement.classList.contains('dark');
+  const [isDarkTheme] = useDarkTheme();
   const [isEdit, setIsEdit] = useState(false);
   const [conversationName, setConversationsName] = useState('');
   // useOutsideAlerter(
@@ -69,14 +69,21 @@ export default function ConversationTile({
       onClick={() => {
         selectConversation(conversation.id);
       }}
-      className={`my-auto mx-4 mt-4 flex h-9 cursor-pointer items-center justify-between gap-4 rounded-3xl hover:bg-gray-100 dark:hover:bg-purple-taupe ${conversationId === conversation.id ? 'bg-gray-100 dark:bg-purple-taupe' : ''
-        }`}
+      className={`my-auto mx-4 mt-4 flex h-9 cursor-pointer items-center justify-between gap-4 rounded-3xl hover:bg-gray-100 dark:hover:bg-purple-taupe ${
+        conversationId === conversation.id
+          ? 'bg-gray-100 dark:bg-purple-taupe'
+          : ''
+      }`}
     >
       <div
-        className={`flex ${conversationId === conversation.id ? 'w-[75%]' : 'w-[95%]'
-          } gap-4`}
+        className={`flex ${
+          conversationId === conversation.id ? 'w-[75%]' : 'w-[95%]'
+        } gap-4`}
       >
-        <img src={isDarkTheme ? MessageDark : Message} className="ml-4 w-5 dark:text-white" />
+        <img
+          src={isDarkTheme ? MessageDark : Message}
+          className="ml-4 w-5 dark:text-white"
+        />
         {isEdit ? (
           <input
             autoFocus
@@ -96,23 +103,24 @@ export default function ConversationTile({
           <img
             src={isEdit ? CheckMark2 : Edit}
             alt="Edit"
-            className="mr-2 h-4 w-4 cursor-pointer hover:opacity-50 text-white"
+            className="mr-2 h-4 w-4 cursor-pointer text-white hover:opacity-50"
             id={`img-${conversation.id}`}
             onClick={(event) => {
               event.stopPropagation();
               isEdit
                 ? handleSaveConversation({
-                  id: conversationId,
-                  name: conversationName,
-                })
+                    id: conversationId,
+                    name: conversationName,
+                  })
                 : handleEditConversation();
             }}
           />
           <img
             src={isEdit ? Exit : Trash}
             alt="Exit"
-            className={`mr-4 ${isEdit ? 'h-3 w-3' : 'h-4 w-4'
-              }mt-px  cursor-pointer hover:opacity-50`}
+            className={`mr-4 ${
+              isEdit ? 'h-3 w-3' : 'h-4 w-4'
+            }mt-px  cursor-pointer hover:opacity-50`}
             id={`img-${conversation.id}`}
             onClick={(event) => {
               event.stopPropagation();

frontend/src/conversation/conversationApi.ts

@@ -3,49 +3,59 @@ import { Doc } from '../preferences/preferenceApi';
 
 const apiHost = import.meta.env.VITE_API_HOST || 'https://docsapi.arc53.com';
 
+function getDocPath(selectedDocs: Doc | null): string {
+  let docPath = 'default';
+
+  if (selectedDocs) {
+    let namePath = selectedDocs.name;
+    if (selectedDocs.language === namePath) {
+      namePath = '.project';
+    }
+    if (selectedDocs.location === 'local') {
+      docPath = 'local' + '/' + selectedDocs.name + '/';
+    } else if (selectedDocs.location === 'remote') {
+      docPath =
+        selectedDocs.language +
+        '/' +
+        namePath +
+        '/' +
+        selectedDocs.version +
+        '/' +
+        selectedDocs.model +
+        '/';
+    } else if (selectedDocs.location === 'custom') {
+      docPath = selectedDocs.docLink;
+    }
+  }
+
+  return docPath;
+}
 export function fetchAnswerApi(
   question: string,
-  apiKey: string,
-  selectedDocs: Doc,
+  signal: AbortSignal,
+  selectedDocs: Doc | null,
   history: Array<any> = [],
   conversationId: string | null,
   promptId: string | null,
+  chunks: string,
 ): Promise<
   | {
-    result: any;
-    answer: any;
-    sources: any;
-    conversationId: any;
-    query: string;
-  }
+      result: any;
+      answer: any;
+      sources: any;
+      conversationId: any;
+      query: string;
+    }
   | {
-    result: any;
-    answer: any;
-    sources: any;
-    query: string;
-    conversationId: any;
-    title: any;
-  }
+      result: any;
+      answer: any;
+      sources: any;
+      query: string;
+      conversationId: any;
+      title: any;
+    }
 > {
-  let namePath = selectedDocs.name;
-  if (selectedDocs.language === namePath) {
-    namePath = '.project';
-  }
-
-  let docPath = 'default';
-  if (selectedDocs.location === 'local') {
-    docPath = 'local' + '/' + selectedDocs.name + '/';
-  } else if (selectedDocs.location === 'remote') {
-    docPath =
-      selectedDocs.language +
-      '/' +
-      namePath +
-      '/' +
-      selectedDocs.version +
-      '/' +
-      selectedDocs.model +
-      '/';
-  }
+  const docPath = getDocPath(selectedDocs);
   //in history array remove all keys except prompt and response
   history = history.map((item) => {
     return { prompt: item.prompt, response: item.response };
@@ -58,13 +68,13 @@ export function fetchAnswerApi(
     },
     body: JSON.stringify({
       question: question,
-      api_key: apiKey,
-      embeddings_key: apiKey,
       history: history,
       active_docs: docPath,
       conversation_id: conversationId,
       prompt_id: promptId,
+      chunks: chunks,
     }),
+    signal,
   })
     .then((response) => {
       if (response.ok) {
@@ -87,32 +97,15 @@ export function fetchAnswerApi(
 
 export function fetchAnswerSteaming(
   question: string,
-  apiKey: string,
-  selectedDocs: Doc,
+  signal: AbortSignal,
+  selectedDocs: Doc | null,
   history: Array<any> = [],
   conversationId: string | null,
   promptId: string | null,
+  chunks: string,
   onEvent: (event: MessageEvent) => void,
 ): Promise<Answer> {
-  let namePath = selectedDocs.name;
-  if (selectedDocs.language === namePath) {
-    namePath = '.project';
-  }
-
-  let docPath = 'default';
-  if (selectedDocs.location === 'local') {
-    docPath = 'local' + '/' + selectedDocs.name + '/';
-  } else if (selectedDocs.location === 'remote') {
-    docPath =
-      selectedDocs.language +
-      '/' +
-      namePath +
-      '/' +
-      selectedDocs.version +
-      '/' +
-      selectedDocs.model +
-      '/';
-  }
+  const docPath = getDocPath(selectedDocs);
 
   history = history.map((item) => {
     return { prompt: item.prompt, response: item.response };
@@ -121,12 +114,11 @@ export function fetchAnswerSteaming(
   return new Promise<Answer>((resolve, reject) => {
     const body = {
       question: question,
-      api_key: apiKey,
-      embeddings_key: apiKey,
       active_docs: docPath,
       history: JSON.stringify(history),
       conversation_id: conversationId,
       prompt_id: promptId,
+      chunks: chunks,
     };
     fetch(apiHost + '/stream', {
       method: 'POST',
@@ -134,6 +126,7 @@ export function fetchAnswerSteaming(
         'Content-Type': 'application/json',
       },
       body: JSON.stringify(body),
+      signal,
     })
       .then((response) => {
         if (!response.body) throw Error('No response body');
@@ -184,55 +177,32 @@ export function fetchAnswerSteaming(
 }
 export function searchEndpoint(
   question: string,
-  apiKey: string,
-  selectedDocs: Doc,
+  selectedDocs: Doc | null,
   conversation_id: string | null,
   history: Array<any> = [],
+  chunks: string,
 ) {
-  /*
-  "active_docs": "default",
-  "question": "Summarise",
-  "conversation_id": null,
-  "history": "[]" */
-  let namePath = selectedDocs.name;
-  if (selectedDocs.language === namePath) {
-    namePath = '.project';
-  }
-
-  let docPath = 'default';
-  if (selectedDocs.location === 'local') {
-    docPath = 'local' + '/' + selectedDocs.name + '/';
-  } else if (selectedDocs.location === 'remote') {
-    docPath =
-      selectedDocs.language +
-      '/' +
-      namePath +
-      '/' +
-      selectedDocs.version +
-      '/' +
-      selectedDocs.model +
-      '/';
-  }
+  const docPath = getDocPath(selectedDocs);
 
   const body = {
     question: question,
     active_docs: docPath,
     conversation_id,
-    history
+    history,
+    chunks: chunks,
   };
   return fetch(`${apiHost}/api/search`, {
     method: 'POST',
     headers: {
       'Content-Type': 'application/json',
     },
-    body: JSON.stringify(
-      body
-    ),
-  }).then((response) => response.json())
+    body: JSON.stringify(body),
+  })
+    .then((response) => response.json())
     .then((data) => {
       return data;
     })
-    .catch(err => console.log(err))
+    .catch((err) => console.log(err));
 }
 export function sendFeedback(
   prompt: string,

frontend/src/conversation/conversationSlice.ts

@@ -16,21 +16,22 @@ const API_STREAMING = import.meta.env.VITE_API_STREAMING === 'true';
 
 export const fetchAnswer = createAsyncThunk<Answer, { question: string }>(
   'fetchAnswer',
-  async ({ question }, { dispatch, getState }) => {
+  async ({ question }, { dispatch, getState, signal }) => {
     const state = getState() as RootState;
     if (state.preference) {
       if (API_STREAMING) {
         await fetchAnswerSteaming(
           question,
-          state.preference.apiKey,
+          signal,
           state.preference.selectedDocs!,
           state.conversation.queries,
           state.conversation.conversationId,
           state.preference.prompt.id,
+          state.preference.chunks,
+
           (event) => {
             const data = JSON.parse(event.data);
 
-
             // check if the 'end' event has been received
             if (data.type === 'end') {
               // set status to 'idle'
@@ -43,13 +44,14 @@ export const fetchAnswer = createAsyncThunk<Answer, { question: string }>(
                   console.error('Failed to fetch conversations: ', error);
                 });
 
-              searchEndpoint( //search for sources post streaming
+              searchEndpoint(
+                //search for sources post streaming
                 question,
-                state.preference.apiKey,
                 state.preference.selectedDocs!,
                 state.conversation.conversationId,
-                state.conversation.queries
-              ).then(sources => {
+                state.conversation.queries,
+                state.preference.chunks,
+              ).then((sources) => {
                 //dispatch streaming sources
                 dispatch(
                   updateStreamingSource({
@@ -78,11 +80,12 @@ export const fetchAnswer = createAsyncThunk<Answer, { question: string }>(
       } else {
         const answer = await fetchAnswerApi(
           question,
-          state.preference.apiKey,
+          signal,
           state.preference.selectedDocs!,
           state.conversation.queries,
           state.conversation.conversationId,
           state.preference.prompt.id,
+          state.preference.chunks,
         );
         if (answer) {
           let sourcesPrepped = [];
@@ -165,7 +168,6 @@ export const conversationSlice = createSlice({
       state,
       action: PayloadAction<{ index: number; query: Partial<Query> }>,
     ) {
-
       const { index, query } = action.payload;
       if (!state.queries[index].sources) {
         state.queries[index].sources = query?.sources;
@@ -193,6 +195,10 @@ export const conversationSlice = createSlice({
         state.status = 'loading';
       })
       .addCase(fetchAnswer.rejected, (state, action) => {
+        if (action.meta.aborted) {
+          state.status = 'idle';
+          return state;
+        }
         state.status = 'failed';
         state.queries[state.queries.length - 1].error =
           'Something went wrong. Please try again later.';

frontend/src/hooks/index.ts

@@ -64,3 +64,39 @@ export function useMediaQuery() {
 
   return { isMobile, isDesktop, isDarkMode };
 }
+
+export function useDarkTheme() {
+  const [isDarkTheme, setIsDarkTheme] = useState<boolean>(
+    localStorage.getItem('selectedTheme') === 'Dark' || false,
+  );
+
+  useEffect(() => {
+    // Check if dark mode preference exists in local storage
+    const savedMode: string | null = localStorage.getItem('selectedTheme');
+
+    // Set dark mode based on local storage preference
+    if (savedMode === 'Dark') {
+      setIsDarkTheme(true);
+      document.documentElement.classList.add('dark');
+      document.documentElement.classList.add('dark:bg-raisin-black');
+    } else {
+      // If no preference found, set to default (light mode)
+      setIsDarkTheme(false);
+      document.documentElement.classList.remove('dark');
+    }
+  }, []);
+  useEffect(() => {
+    localStorage.setItem('selectedTheme', isDarkTheme ? 'Dark' : 'Light');
+    if (isDarkTheme) {
+      document.documentElement.classList.add('dark');
+      document.documentElement.classList.add('dark:bg-raisin-black');
+    } else {
+      document.documentElement.classList.remove('dark');
+    }
+  }, [isDarkTheme]);
+  //method to toggle theme
+  const toggleTheme: any = () => {
+    setIsDarkTheme(!isDarkTheme);
+  };
+  return [isDarkTheme, toggleTheme];
+}