mirror of
https://github.com/arc53/DocsGPT.git
synced 2025-11-29 08:33:20 +00:00
Merge branch 'main' of https://github.com/arc53/DocsGPT into dependabot/npm_and_yarn/frontend/tailwindcss-4.1.10
This commit is contained in:
ManishMadan2882
@@ -8,7 +8,7 @@ logger = logging.getLogger(__name__)
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class ClassicAgent(BaseAgent):
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"""A simplified classic agent with clear execution flow.
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"""A simplified agent with clear execution flow.
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Usage:
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1. Processes a query through retrieval
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@@ -25,27 +25,35 @@ class BraveSearchTool(Tool):
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else:
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raise ValueError(f"Unknown action: {action_name}")
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def _web_search(self, query, country="ALL", search_lang="en", count=10,
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offset=0, safesearch="off", freshness=None,
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result_filter=None, extra_snippets=False, summary=False):
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def _web_search(
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self,
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query,
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country="ALL",
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search_lang="en",
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count=10,
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offset=0,
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safesearch="off",
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freshness=None,
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result_filter=None,
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extra_snippets=False,
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summary=False,
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):
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"""
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Performs a web search using the Brave Search API.
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"""
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print(f"Performing Brave web search for: {query}")
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url = f"{self.base_url}/web/search"
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# Build query parameters
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params = {
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"q": query,
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"country": country,
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"search_lang": search_lang,
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"count": min(count, 20),
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"offset": min(offset, 9),
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"safesearch": safesearch
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"safesearch": safesearch,
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}
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# Add optional parameters only if they have values
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if freshness:
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params["freshness"] = freshness
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if result_filter:
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@@ -54,68 +62,69 @@ class BraveSearchTool(Tool):
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params["extra_snippets"] = 1
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if summary:
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params["summary"] = 1
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# Set up headers
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headers = {
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"Accept": "application/json",
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"Accept-Encoding": "gzip",
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"X-Subscription-Token": self.token
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"X-Subscription-Token": self.token,
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}
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# Make the request
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response = requests.get(url, params=params, headers=headers)
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if response.status_code == 200:
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return {
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"status_code": response.status_code,
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"results": response.json(),
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"message": "Search completed successfully."
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"message": "Search completed successfully.",
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}
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else:
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return {
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"status_code": response.status_code,
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"message": f"Search failed with status code: {response.status_code}."
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"message": f"Search failed with status code: {response.status_code}.",
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}
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def _image_search(self, query, country="ALL", search_lang="en", count=5,
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safesearch="off", spellcheck=False):
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def _image_search(
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self,
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query,
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country="ALL",
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search_lang="en",
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count=5,
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safesearch="off",
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spellcheck=False,
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):
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"""
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Performs an image search using the Brave Search API.
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"""
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print(f"Performing Brave image search for: {query}")
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url = f"{self.base_url}/images/search"
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# Build query parameters
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params = {
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"q": query,
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"country": country,
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"search_lang": search_lang,
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"count": min(count, 100), # API max is 100
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"safesearch": safesearch,
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"spellcheck": 1 if spellcheck else 0
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"spellcheck": 1 if spellcheck else 0,
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}
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# Set up headers
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headers = {
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"Accept": "application/json",
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"Accept-Encoding": "gzip",
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"X-Subscription-Token": self.token
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"X-Subscription-Token": self.token,
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}
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# Make the request
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response = requests.get(url, params=params, headers=headers)
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if response.status_code == 200:
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return {
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"status_code": response.status_code,
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"results": response.json(),
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"message": "Image search completed successfully."
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"message": "Image search completed successfully.",
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}
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else:
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return {
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"status_code": response.status_code,
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"message": f"Image search failed with status code: {response.status_code}."
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"message": f"Image search failed with status code: {response.status_code}.",
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}
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def get_actions_metadata(self):
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@@ -130,42 +139,14 @@ class BraveSearchTool(Tool):
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"type": "string",
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"description": "The search query (max 400 characters, 50 words)",
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},
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# "country": {
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# "type": "string",
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# "description": "The 2-character country code (default: US)",
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# },
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"search_lang": {
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"type": "string",
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"description": "The search language preference (default: en)",
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},
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# "count": {
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# "type": "integer",
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# "description": "Number of results to return (max 20, default: 10)",
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# },
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# "offset": {
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# "type": "integer",
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# "description": "Pagination offset (max 9, default: 0)",
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# },
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# "safesearch": {
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# "type": "string",
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# "description": "Filter level for adult content (off, moderate, strict)",
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# },
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"freshness": {
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"type": "string",
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"description": "Time filter for results (pd: last 24h, pw: last week, pm: last month, py: last year)",
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},
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# "result_filter": {
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# "type": "string",
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# "description": "Comma-delimited list of result types to include",
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# },
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# "extra_snippets": {
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# "type": "boolean",
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# "description": "Get additional excerpts from result pages",
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# },
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# "summary": {
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# "type": "boolean",
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# "description": "Enable summary generation in search results",
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# }
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},
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"required": ["query"],
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"additionalProperties": False,
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@@ -181,37 +162,21 @@ class BraveSearchTool(Tool):
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"type": "string",
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"description": "The search query (max 400 characters, 50 words)",
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},
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# "country": {
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# "type": "string",
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# "description": "The 2-character country code (default: US)",
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# },
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# "search_lang": {
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# "type": "string",
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# "description": "The search language preference (default: en)",
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# },
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"count": {
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"type": "integer",
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"description": "Number of results to return (max 100, default: 5)",
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},
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# "safesearch": {
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# "type": "string",
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# "description": "Filter level for adult content (off, strict). Default: strict",
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# },
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# "spellcheck": {
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# "type": "boolean",
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# "description": "Whether to spellcheck provided query (default: true)",
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# }
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},
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"required": ["query"],
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"additionalProperties": False,
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},
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}
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},
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]
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def get_config_requirements(self):
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return {
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"token": {
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"type": "string",
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"description": "Brave Search API key for authentication"
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"type": "string",
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"description": "Brave Search API key for authentication",
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},
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}
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}
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114
application/agents/tools/duckduckgo.py
Normal file
114
application/agents/tools/duckduckgo.py
Normal file
@@ -0,0 +1,114 @@
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from application.agents.tools.base import Tool
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from duckduckgo_search import DDGS
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class DuckDuckGoSearchTool(Tool):
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"""
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DuckDuckGo Search
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A tool for performing web and image searches using DuckDuckGo.
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"""
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def __init__(self, config):
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self.config = config
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def execute_action(self, action_name, **kwargs):
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actions = {
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"ddg_web_search": self._web_search,
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"ddg_image_search": self._image_search,
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}
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if action_name in actions:
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return actions[action_name](**kwargs)
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else:
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raise ValueError(f"Unknown action: {action_name}")
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||||
def _web_search(
|
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self,
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query,
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max_results=5,
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):
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print(f"Performing DuckDuckGo web search for: {query}")
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try:
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results = DDGS().text(
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query,
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max_results=max_results,
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)
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return {
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"status_code": 200,
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"results": results,
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"message": "Web search completed successfully.",
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}
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except Exception as e:
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return {
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"status_code": 500,
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"message": f"Web search failed: {str(e)}",
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}
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def _image_search(
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self,
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query,
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max_results=5,
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):
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print(f"Performing DuckDuckGo image search for: {query}")
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try:
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results = DDGS().images(
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keywords=query,
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max_results=max_results,
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)
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return {
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"status_code": 200,
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"results": results,
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"message": "Image search completed successfully.",
|
||||
}
|
||||
except Exception as e:
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return {
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"status_code": 500,
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"message": f"Image search failed: {str(e)}",
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}
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def get_actions_metadata(self):
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return [
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{
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"name": "ddg_web_search",
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"description": "Perform a web search using DuckDuckGo.",
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"parameters": {
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"type": "object",
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"properties": {
|
||||
"query": {
|
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"type": "string",
|
||||
"description": "Search query",
|
||||
},
|
||||
"max_results": {
|
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"type": "integer",
|
||||
"description": "Number of results to return (default: 5)",
|
||||
},
|
||||
},
|
||||
"required": ["query"],
|
||||
},
|
||||
},
|
||||
{
|
||||
"name": "ddg_image_search",
|
||||
"description": "Perform an image search using DuckDuckGo.",
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"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"query": {
|
||||
"type": "string",
|
||||
"description": "Search query",
|
||||
},
|
||||
"max_results": {
|
||||
"type": "integer",
|
||||
"description": "Number of results to return (default: 5, max: 50)",
|
||||
},
|
||||
},
|
||||
"required": ["query"],
|
||||
},
|
||||
},
|
||||
]
|
||||
|
||||
def get_config_requirements(self):
|
||||
return {}
|
||||
@@ -614,7 +614,7 @@ class Answer(Resource):
|
||||
try:
|
||||
question = data["question"]
|
||||
history = limit_chat_history(
|
||||
json.loads(data.get("history", [])), gpt_model=gpt_model
|
||||
json.loads(data.get("history", "[]")), gpt_model=gpt_model
|
||||
)
|
||||
conversation_id = data.get("conversation_id")
|
||||
prompt_id = data.get("prompt_id", "default")
|
||||
|
||||
@@ -879,29 +879,6 @@ class CombinedJson(Resource):
|
||||
"syncFrequency": index.get("sync_frequency", ""),
|
||||
}
|
||||
)
|
||||
if "duckduck_search" in settings.RETRIEVERS_ENABLED:
|
||||
data.append(
|
||||
{
|
||||
"name": "DuckDuckGo Search",
|
||||
"date": "duckduck_search",
|
||||
"model": settings.EMBEDDINGS_NAME,
|
||||
"location": "custom",
|
||||
"tokens": "",
|
||||
"retriever": "duckduck_search",
|
||||
}
|
||||
)
|
||||
if "brave_search" in settings.RETRIEVERS_ENABLED:
|
||||
data.append(
|
||||
{
|
||||
"name": "Brave Search",
|
||||
"language": "en",
|
||||
"date": "brave_search",
|
||||
"model": settings.EMBEDDINGS_NAME,
|
||||
"location": "custom",
|
||||
"tokens": "",
|
||||
"retriever": "brave_search",
|
||||
}
|
||||
)
|
||||
except Exception as err:
|
||||
current_app.logger.error(f"Error retrieving sources: {err}", exc_info=True)
|
||||
return make_response(jsonify({"success": False}), 400)
|
||||
|
||||
@@ -33,7 +33,7 @@ class Settings(BaseSettings):
|
||||
VECTOR_STORE: str = (
|
||||
"faiss" # "faiss" or "elasticsearch" or "qdrant" or "milvus" or "lancedb"
|
||||
)
|
||||
RETRIEVERS_ENABLED: list = ["classic_rag", "duckduck_search"] # also brave_search
|
||||
RETRIEVERS_ENABLED: list = ["classic_rag"]
|
||||
AGENT_NAME: str = "classic"
|
||||
FALLBACK_LLM_PROVIDER: Optional[str] = None # provider for fallback llm
|
||||
FALLBACK_LLM_NAME: Optional[str] = None # model name for fallback llm
|
||||
@@ -99,7 +99,6 @@ class Settings(BaseSettings):
|
||||
LANCEDB_TABLE_NAME: Optional[str] = (
|
||||
"docsgpts" # Name of the table to use for storing vectors
|
||||
)
|
||||
BRAVE_SEARCH_API_KEY: Optional[str] = None
|
||||
|
||||
FLASK_DEBUG_MODE: bool = False
|
||||
STORAGE_TYPE: str = "local" # local or s3
|
||||
|
||||
@@ -1,112 +0,0 @@
|
||||
import json
|
||||
|
||||
from langchain_community.tools import BraveSearch
|
||||
|
||||
from application.core.settings import settings
|
||||
from application.llm.llm_creator import LLMCreator
|
||||
from application.retriever.base import BaseRetriever
|
||||
|
||||
|
||||
class BraveRetSearch(BaseRetriever):
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
source,
|
||||
chat_history,
|
||||
prompt,
|
||||
chunks=2,
|
||||
token_limit=150,
|
||||
gpt_model="docsgpt",
|
||||
user_api_key=None,
|
||||
decoded_token=None,
|
||||
):
|
||||
self.question = ""
|
||||
self.source = source
|
||||
self.chat_history = chat_history
|
||||
self.prompt = prompt
|
||||
self.chunks = chunks
|
||||
self.gpt_model = gpt_model
|
||||
self.token_limit = (
|
||||
token_limit
|
||||
if token_limit
|
||||
< settings.LLM_TOKEN_LIMITS.get(
|
||||
self.gpt_model, settings.DEFAULT_MAX_HISTORY
|
||||
)
|
||||
else settings.LLM_TOKEN_LIMITS.get(
|
||||
self.gpt_model, settings.DEFAULT_MAX_HISTORY
|
||||
)
|
||||
)
|
||||
self.user_api_key = user_api_key
|
||||
self.decoded_token = decoded_token
|
||||
|
||||
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_PROVIDER == "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) > 0:
|
||||
for i in self.chat_history:
|
||||
if "prompt" in i and "response" in i:
|
||||
messages_combine.append({"role": "user", "content": i["prompt"]})
|
||||
messages_combine.append(
|
||||
{"role": "assistant", "content": i["response"]}
|
||||
)
|
||||
messages_combine.append({"role": "user", "content": self.question})
|
||||
|
||||
llm = LLMCreator.create_llm(
|
||||
settings.LLM_PROVIDER,
|
||||
api_key=settings.API_KEY,
|
||||
user_api_key=self.user_api_key,
|
||||
decoded_token=self.decoded_token,
|
||||
)
|
||||
|
||||
completion = llm.gen_stream(model=self.gpt_model, messages=messages_combine)
|
||||
for line in completion:
|
||||
yield {"answer": str(line)}
|
||||
|
||||
def search(self, query: str = ""):
|
||||
if query:
|
||||
self.question = query
|
||||
return self._get_data()
|
||||
|
||||
def get_params(self):
|
||||
return {
|
||||
"question": self.question,
|
||||
"source": self.source,
|
||||
"chat_history": self.chat_history,
|
||||
"prompt": self.prompt,
|
||||
"chunks": self.chunks,
|
||||
"token_limit": self.token_limit,
|
||||
"gpt_model": self.gpt_model,
|
||||
"user_api_key": self.user_api_key,
|
||||
}
|
||||
@@ -1,111 +0,0 @@
|
||||
from langchain_community.tools import DuckDuckGoSearchResults
|
||||
from langchain_community.utilities import DuckDuckGoSearchAPIWrapper
|
||||
|
||||
from application.core.settings import settings
|
||||
from application.llm.llm_creator import LLMCreator
|
||||
from application.retriever.base import BaseRetriever
|
||||
|
||||
|
||||
class DuckDuckSearch(BaseRetriever):
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
source,
|
||||
chat_history,
|
||||
prompt,
|
||||
chunks=2,
|
||||
token_limit=150,
|
||||
gpt_model="docsgpt",
|
||||
user_api_key=None,
|
||||
decoded_token=None,
|
||||
):
|
||||
self.question = ""
|
||||
self.source = source
|
||||
self.chat_history = chat_history
|
||||
self.prompt = prompt
|
||||
self.chunks = chunks
|
||||
self.gpt_model = gpt_model
|
||||
self.token_limit = (
|
||||
token_limit
|
||||
if token_limit
|
||||
< settings.LLM_TOKEN_LIMITS.get(
|
||||
self.gpt_model, settings.DEFAULT_MAX_HISTORY
|
||||
)
|
||||
else settings.LLM_TOKEN_LIMITS.get(
|
||||
self.gpt_model, settings.DEFAULT_MAX_HISTORY
|
||||
)
|
||||
)
|
||||
self.user_api_key = user_api_key
|
||||
self.decoded_token = decoded_token
|
||||
|
||||
def _get_data(self):
|
||||
if self.chunks == 0:
|
||||
docs = []
|
||||
else:
|
||||
wrapper = DuckDuckGoSearchAPIWrapper(max_results=self.chunks)
|
||||
search = DuckDuckGoSearchResults(api_wrapper=wrapper, output_format="list")
|
||||
results = search.run(self.question)
|
||||
|
||||
docs = []
|
||||
for i in results:
|
||||
try:
|
||||
docs.append(
|
||||
{
|
||||
"text": i.get("snippet", "").strip(),
|
||||
"title": i.get("title", "").strip(),
|
||||
"link": i.get("link", "").strip(),
|
||||
}
|
||||
)
|
||||
except IndexError:
|
||||
pass
|
||||
if settings.LLM_PROVIDER == "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) > 0:
|
||||
for i in self.chat_history:
|
||||
if "prompt" in i and "response" in i:
|
||||
messages_combine.append({"role": "user", "content": i["prompt"]})
|
||||
messages_combine.append(
|
||||
{"role": "assistant", "content": i["response"]}
|
||||
)
|
||||
messages_combine.append({"role": "user", "content": self.question})
|
||||
|
||||
llm = LLMCreator.create_llm(
|
||||
settings.LLM_PROVIDER,
|
||||
api_key=settings.API_KEY,
|
||||
user_api_key=self.user_api_key,
|
||||
decoded_token=self.decoded_token,
|
||||
)
|
||||
|
||||
completion = llm.gen_stream(model=self.gpt_model, messages=messages_combine)
|
||||
for line in completion:
|
||||
yield {"answer": str(line)}
|
||||
|
||||
def search(self, query: str = ""):
|
||||
if query:
|
||||
self.question = query
|
||||
return self._get_data()
|
||||
|
||||
def get_params(self):
|
||||
return {
|
||||
"question": self.question,
|
||||
"source": self.source,
|
||||
"chat_history": self.chat_history,
|
||||
"prompt": self.prompt,
|
||||
"chunks": self.chunks,
|
||||
"token_limit": self.token_limit,
|
||||
"gpt_model": self.gpt_model,
|
||||
"user_api_key": self.user_api_key,
|
||||
}
|
||||
@@ -1,13 +1,9 @@
|
||||
from application.retriever.classic_rag import ClassicRAG
|
||||
from application.retriever.duckduck_search import DuckDuckSearch
|
||||
from application.retriever.brave_search import BraveRetSearch
|
||||
|
||||
|
||||
class RetrieverCreator:
|
||||
retrievers = {
|
||||
"classic": ClassicRAG,
|
||||
"duckduck_search": DuckDuckSearch,
|
||||
"brave_search": BraveRetSearch,
|
||||
"default": ClassicRAG,
|
||||
}
|
||||
|
||||
|
||||
@@ -2,5 +2,13 @@
|
||||
"basics": {
|
||||
"title": "🤖 Agent Basics",
|
||||
"href": "/Agents/basics"
|
||||
},
|
||||
"api": {
|
||||
"title": "🔌 Agent API",
|
||||
"href": "/Agents/api"
|
||||
},
|
||||
"webhooks": {
|
||||
"title": "🪝 Agent Webhooks",
|
||||
"href": "/Agents/webhooks"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
227
docs/pages/Agents/api.mdx
Normal file
227
docs/pages/Agents/api.mdx
Normal file
@@ -0,0 +1,227 @@
|
||||
---
|
||||
title: Interacting with Agents via API
|
||||
description: Learn how to programmatically interact with DocsGPT Agents using the streaming and non-streaming API endpoints.
|
||||
---
|
||||
|
||||
import { Callout, Tabs } from 'nextra/components';
|
||||
|
||||
# Interacting with Agents via API
|
||||
|
||||
DocsGPT Agents can be accessed programmatically through a dedicated API, allowing you to integrate their specialized capabilities into your own applications, scripts, and workflows. This guide covers the two primary methods for interacting with an agent: the streaming API for real-time responses and the non-streaming API for a single, consolidated answer.
|
||||
|
||||
When you use an API key generated for a specific agent, you do not need to pass `prompt`, `tools` etc. The agent's configuration (including its prompt, selected tools, and knowledge sources) is already associated with its unique API key.
|
||||
|
||||
### API Endpoints
|
||||
|
||||
- **Non-Streaming:** `http://localhost:7091/api/answer`
|
||||
- **Streaming:** `http://localhost:7091/stream`
|
||||
|
||||
<Callout type="info">
|
||||
For DocsGPT Cloud, use `https://gptcloud.arc53.com/` as the base URL.
|
||||
</Callout>
|
||||
|
||||
For more technical details, you can explore the API swagger documentation available for the cloud version or your local instance.
|
||||
|
||||
---
|
||||
|
||||
## Non-Streaming API (`/api/answer`)
|
||||
|
||||
This is a standard synchronous endpoint. It waits for the agent to fully process the request and returns a single JSON object with the complete answer. This is the simplest method and is ideal for backend processes where a real-time feed is not required.
|
||||
|
||||
### Request
|
||||
|
||||
- **Endpoint:** `/api/answer`
|
||||
- **Method:** `POST`
|
||||
- **Payload:**
|
||||
- `question` (string, required): The user's query or input for the agent.
|
||||
- `api_key` (string, required): The unique API key for the agent you wish to interact with.
|
||||
- `history` (string, optional): A JSON string representing the conversation history, e.g., `[{\"prompt\": \"first question\", \"answer\": \"first answer\"}]`.
|
||||
|
||||
### Response
|
||||
|
||||
A single JSON object containing:
|
||||
- `answer`: The complete, final answer from the agent.
|
||||
- `sources`: A list of sources the agent consulted.
|
||||
- `conversation_id`: The unique ID for the interaction.
|
||||
|
||||
### Examples
|
||||
|
||||
<Tabs items={['cURL', 'Python', 'JavaScript']}>
|
||||
<Tabs.Tab>
|
||||
```bash
|
||||
curl -X POST http://localhost:7091/api/answer \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"question": "your question here",
|
||||
"api_key": "your_agent_api_key"
|
||||
}'
|
||||
```
|
||||
</Tabs.Tab>
|
||||
<Tabs.Tab>
|
||||
```python
|
||||
import requests
|
||||
|
||||
API_URL = "http://localhost:7091/api/answer"
|
||||
API_KEY = "your_agent_api_key"
|
||||
QUESTION = "your question here"
|
||||
|
||||
response = requests.post(
|
||||
API_URL,
|
||||
json={"question": QUESTION, "api_key": API_KEY}
|
||||
)
|
||||
|
||||
if response.status_code == 200:
|
||||
print(response.json())
|
||||
else:
|
||||
print(f"Error: {response.status_code}")
|
||||
print(response.text)
|
||||
```
|
||||
</Tabs.Tab>
|
||||
<Tabs.Tab>
|
||||
```javascript
|
||||
const apiUrl = 'http://localhost:7091/api/answer';
|
||||
const apiKey = 'your_agent_api_key';
|
||||
const question = 'your question here';
|
||||
|
||||
async function getAnswer() {
|
||||
try {
|
||||
const response = await fetch(apiUrl, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({ question, api_key: apiKey }),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(`HTTP error! Status: ${response.status}`);
|
||||
}
|
||||
|
||||
const data = await response.json();
|
||||
console.log(data);
|
||||
} catch (error) {
|
||||
console.error("Failed to fetch answer:", error);
|
||||
}
|
||||
}
|
||||
|
||||
getAnswer();
|
||||
```
|
||||
</Tabs.Tab>
|
||||
</Tabs>
|
||||
|
||||
---
|
||||
|
||||
## Streaming API (`/stream`)
|
||||
|
||||
The `/stream` endpoint uses Server-Sent Events (SSE) to push data in real-time. This is ideal for applications where you want to display the response as it's being generated, such as in a live chatbot interface.
|
||||
|
||||
### Request
|
||||
|
||||
- **Endpoint:** `/stream`
|
||||
- **Method:** `POST`
|
||||
- **Payload:** Same as the non-streaming API.
|
||||
|
||||
### Response (SSE Stream)
|
||||
|
||||
The stream consists of multiple `data:` events, each containing a JSON object. Your client should listen for these events and process them based on their `type`.
|
||||
|
||||
**Event Types:**
|
||||
- `answer`: A chunk of the agent's final answer.
|
||||
- `source`: A document or source used by the agent.
|
||||
- `thought`: A reasoning step from the agent (for ReAct agents).
|
||||
- `id`: The unique `conversation_id` for the interaction.
|
||||
- `error`: An error message.
|
||||
- `end`: A final message indicating the stream has concluded.
|
||||
|
||||
### Examples
|
||||
|
||||
<Tabs items={['cURL', 'Python', 'JavaScript']}>
|
||||
<Tabs.Tab>
|
||||
```bash
|
||||
curl -X POST http://localhost:7091/stream \
|
||||
-H "Content-Type: application/json" \
|
||||
-H "Accept: text/event-stream" \
|
||||
-d '{
|
||||
"question": "your question here",
|
||||
"api_key": "your_agent_api_key"
|
||||
}'
|
||||
```
|
||||
</Tabs.Tab>
|
||||
<Tabs.Tab>
|
||||
```python
|
||||
import requests
|
||||
import json
|
||||
|
||||
API_URL = "http://localhost:7091/stream"
|
||||
payload = {
|
||||
"question": "your question here",
|
||||
"api_key": "your_agent_api_key"
|
||||
}
|
||||
|
||||
with requests.post(API_URL, json=payload, stream=True) as r:
|
||||
for line in r.iter_lines():
|
||||
if line:
|
||||
decoded_line = line.decode('utf-8')
|
||||
if decoded_line.startswith('data: '):
|
||||
try:
|
||||
data = json.loads(decoded_line[6:])
|
||||
print(data)
|
||||
except json.JSONDecodeError:
|
||||
pass
|
||||
```
|
||||
</Tabs.Tab>
|
||||
<Tabs.Tab>
|
||||
```javascript
|
||||
const apiUrl = 'http://localhost:7091/stream';
|
||||
const apiKey = 'your_agent_api_key';
|
||||
const question = 'your question here';
|
||||
|
||||
async function getStream() {
|
||||
try {
|
||||
const response = await fetch(apiUrl, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
'Accept': 'text/event-stream'
|
||||
},
|
||||
// Corrected line: 'apiKey' is changed to 'api_key'
|
||||
body: JSON.stringify({ question, api_key: apiKey }),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(`HTTP error! Status: ${response.status}`);
|
||||
}
|
||||
|
||||
const reader = response.body.getReader();
|
||||
const decoder = new TextDecoder();
|
||||
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
if (done) break;
|
||||
|
||||
const chunk = decoder.decode(value, { stream: true });
|
||||
// Note: This parsing method assumes each chunk contains whole lines.
|
||||
// For a more robust production implementation, buffer the chunks
|
||||
// and process them line by line.
|
||||
const lines = chunk.split('\n');
|
||||
|
||||
for (const line of lines) {
|
||||
if (line.startsWith('data: ')) {
|
||||
try {
|
||||
const data = JSON.parse(line.substring(6));
|
||||
console.log(data);
|
||||
} catch (e) {
|
||||
console.error("Failed to parse JSON from SSE event:", e);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
console.error("Failed to fetch stream:", error);
|
||||
}
|
||||
}
|
||||
|
||||
getStream();
|
||||
```
|
||||
</Tabs.Tab>
|
||||
</Tabs>
|
||||
152
docs/pages/Agents/webhooks.mdx
Normal file
152
docs/pages/Agents/webhooks.mdx
Normal file
@@ -0,0 +1,152 @@
|
||||
---
|
||||
title: Triggering Agents with Webhooks
|
||||
description: Learn how to automate and integrate DocsGPT Agents using webhooks for asynchronous task execution.
|
||||
---
|
||||
|
||||
import { Callout, Tabs } from 'nextra/components';
|
||||
|
||||
# Triggering Agents with Webhooks
|
||||
|
||||
Agent Webhooks provide a powerful mechanism to trigger an agent's execution from external systems. Unlike the direct API which provides an immediate response, webhooks are designed for **asynchronous** operations. When you call a webhook, DocsGPT enqueues the agent's task for background processing and immediately returns a `task_id`. You then use this ID to poll for the result.
|
||||
|
||||
This workflow is ideal for integrating with services that expect a quick initial response (e.g., form submissions) or for triggering long-running tasks without tying up a client connection.
|
||||
|
||||
Each agent has its own unique webhook URL, which can be generated from the agent's edit page in the DocsGPT UI. This URL includes a secure token for authentication.
|
||||
|
||||
### API Endpoints
|
||||
|
||||
- **Webhook URL:** `http://localhost:7091/api/webhooks/agents/{AGENT_WEBHOOK_TOKEN}`
|
||||
- **Task Status URL:** `http://localhost:7091/api/task_status`
|
||||
|
||||
<Callout type="info">
|
||||
For DocsGPT Cloud, use `https://gptcloud.arc53.com/` as the base URL.
|
||||
</Callout>
|
||||
|
||||
For more technical details, you can explore the API swagger documentation available for the cloud version or your local instance.
|
||||
|
||||
---
|
||||
|
||||
## The Webhook Workflow
|
||||
|
||||
The process involves two main steps: triggering the task and polling for the result.
|
||||
|
||||
### Step 1: Trigger the Webhook
|
||||
|
||||
Send an HTTP `POST` request to the agent's unique webhook URL with the required payload. The structure of this payload should match what the agent's prompt and tools are designed to handle.
|
||||
|
||||
- **Method:** `POST`
|
||||
- **Response:** A JSON object with a `task_id`. `{"task_id": "a1b2c3d4-e5f6-..."}`
|
||||
|
||||
<Tabs items={['cURL', 'Python', 'JavaScript']}>
|
||||
<Tabs.Tab>
|
||||
```bash
|
||||
curl -X POST \
|
||||
http://localhost:7091/api/webhooks/agents/your_webhook_token \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{"question": "Your message to agent"}'
|
||||
```
|
||||
</Tabs.Tab>
|
||||
<Tabs.Tab>
|
||||
```python
|
||||
import requests
|
||||
|
||||
WEBHOOK_URL = "http://localhost:7091/api/webhooks/agents/your_webhook_token"
|
||||
payload = {"question": "Your message to agent"}
|
||||
|
||||
try:
|
||||
response = requests.post(WEBHOOK_URL, json=payload)
|
||||
response.raise_for_status()
|
||||
task_id = response.json().get("task_id")
|
||||
print(f"Task successfully created with ID: {task_id}")
|
||||
except requests.exceptions.RequestException as e:
|
||||
print(f"Error triggering webhook: {e}")
|
||||
```
|
||||
</Tabs.Tab>
|
||||
<Tabs.Tab>
|
||||
```javascript
|
||||
const webhookUrl = 'http://localhost:7091/api/webhooks/agents/your_webhook_token';
|
||||
const payload = { question: 'Your message to agent' };
|
||||
|
||||
async function triggerWebhook() {
|
||||
try {
|
||||
const response = await fetch(webhookUrl, {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify(payload)
|
||||
});
|
||||
if (!response.ok) throw new Error(`HTTP error! ${response.status}`);
|
||||
const data = await response.json();
|
||||
console.log(`Task successfully created with ID: ${data.task_id}`);
|
||||
return data.task_id;
|
||||
} catch (error) {
|
||||
console.error('Error triggering webhook:', error);
|
||||
}
|
||||
}
|
||||
|
||||
triggerWebhook();
|
||||
```
|
||||
</Tabs.Tab>
|
||||
</Tabs>
|
||||
|
||||
### Step 2: Poll for the Result
|
||||
|
||||
Once you have the `task_id`, periodically send a `GET` request to the `/api/task_status` endpoint until the task `status` is `SUCCESS` or `FAILURE`.
|
||||
|
||||
- **`status`**: The current state of the task (`PENDING`, `STARTED`, `SUCCESS`, `FAILURE`).
|
||||
- **`result`**: The final output from the agent, available when the status is `SUCCESS` or `FAILURE`.
|
||||
|
||||
<Tabs items={['cURL', 'Python', 'JavaScript']}>
|
||||
<Tabs.Tab>
|
||||
```bash
|
||||
# Replace the task_id with the one you received
|
||||
curl http://localhost:7091/api/task_status?task_id=YOUR_TASK_ID
|
||||
```
|
||||
</Tabs.Tab>
|
||||
<Tabs.Tab>
|
||||
```python
|
||||
import requests
|
||||
import time
|
||||
|
||||
STATUS_URL = "http://localhost:7091/api/task_status"
|
||||
task_id = "YOUR_TASK_ID"
|
||||
|
||||
while True:
|
||||
response = requests.get(STATUS_URL, params={"task_id": task_id})
|
||||
data = response.json()
|
||||
status = data.get("status")
|
||||
print(f"Current task status: {status}")
|
||||
|
||||
if status in ["SUCCESS", "FAILURE"]:
|
||||
print("Final Result:")
|
||||
print(data.get("result"))
|
||||
break
|
||||
|
||||
time.sleep(2)
|
||||
```
|
||||
</Tabs.Tab>
|
||||
<Tabs.Tab>
|
||||
```javascript
|
||||
const statusUrl = 'http://localhost:7091/api/task_status';
|
||||
const taskId = 'YOUR_TASK_ID';
|
||||
|
||||
const sleep = (ms) => new Promise(resolve => setTimeout(resolve, ms));
|
||||
|
||||
async function pollForResult() {
|
||||
while (true) {
|
||||
const response = await fetch(`${statusUrl}?task_id=${taskId}`);
|
||||
const data = await response.json();
|
||||
const status = data.status;
|
||||
console.log(`Current task status: ${status}`);
|
||||
|
||||
if (status === 'SUCCESS' || status === 'FAILURE') {
|
||||
console.log('Final Result:', data.result);
|
||||
break;
|
||||
}
|
||||
await sleep(2000);
|
||||
}
|
||||
}
|
||||
|
||||
pollForResult();
|
||||
```
|
||||
</Tabs.Tab>
|
||||
</Tabs>
|
||||
1
frontend/public/toolIcons/tool_duckduckgo.svg
Normal file
1
frontend/public/toolIcons/tool_duckduckgo.svg
Normal file
@@ -0,0 +1 @@
|
||||
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 122.88 122.88"><defs><style>.a{fill:#d53;}.b{fill:#fff;}.c{fill:#ddd;}.d{fill:#fc0;}.e{fill:#6b5;}.f{fill:#4a4;}.g{fill:#148;}</style></defs><title>duckduckgo</title><path class="a" d="M122.88,61.44a61.44,61.44,0,1,0-61.44,61.44,61.44,61.44,0,0,0,61.44-61.44Z"/><path class="b" d="M114.37,61.44a52.92,52.92,0,1,0-15.5,37.43,52.76,52.76,0,0,0,15.5-37.43Zm-13.12-39.8A56.29,56.29,0,1,1,61.44,5.15a56.12,56.12,0,0,1,39.81,16.49Z"/><path class="c" d="M43.24,30.15C26.17,34.13,32.43,58,32.43,58l10.81,52.9,4,1.71-4-82.49Zm-4-10.24H34.7L41,22.19s-6.26,0-6.26,4C48.36,25.6,54.61,29,54.61,29l-15.36-9.1Zm0,0Z"/><path class="b" d="M75.66,115.48S62,93.87,62,79.64c0-26.73,17.63-4,17.63-25S62,28.44,62,28.44c-8.53-10.8-25-8.53-25-8.53l4,2.28s-4,1.13-5.12,2.27,10.81-1.7,15.93,2.85C30.72,29,34.13,46.08,34.13,46.08l11.95,68.27,29.58,1.13Zm0,0Z"/><path class="d" d="M75.66,60.87l21.62-5.69C116.62,58,80.78,68.84,78.51,68.27c-17.07-2.85-12,11.37,8.53,6.82s5.12,11.38-13.65,5.12c-26.74-7.39-12.52-20.48,2.27-19.34Z"/><path class="e" d="M70,105.81l1.14-1.7c12.52,4.55,13.09,6.25,12.52-5.12s0-11.38-13.09-1.71c0-2.84-7.39-1.71-8.53,0-11.95-5.12-13.09-6.83-12.52,1.14,1.14,16.5.57,13.65,11.95,8l8.53-.57Zm0,0Z"/><path class="f" d="M60.87,99.56v6.82c.57,1.14,9.67,1.14,9.67-1.14s-4.55,1.71-7.39.57S62,98.42,62,98.42l-1.14,1.14Zm0,0Z"/><path class="g" d="M48.36,43.24c-2.85-3.42-10.24-.57-8.54,4,.57-2.28,4.55-5.69,8.54-4Zm18.2,0c.57-3.42,6.26-4,8-.57a8,8,0,0,0-8,.57Zm-18.77,9.1a1.14,1.14,0,1,1,0,.57v-.57Zm-4.55,2.27a4,4,0,1,0,0-.57v.57Zm29.58-4a1.14,1.14,0,1,1,0,.57v-.57ZM69.4,52.91a3.42,3.42,0,1,0,0-.57v.57Zm0,0Z"/></svg>
|
||||
|
After Width: | Height: | Size: 1.6 KiB |
@@ -288,136 +288,101 @@ const ConversationBubble = forwardRef<
|
||||
{DisableSourceFE ||
|
||||
type === 'ERROR' ||
|
||||
sources?.length === 0 ||
|
||||
sources?.some((source) => source.link === 'None') ? null : !sources &&
|
||||
chunks !== '0' &&
|
||||
selectedDocs ? (
|
||||
<div className="mb-4 flex flex-col flex-wrap items-start self-start lg:flex-nowrap">
|
||||
<div className="my-2 flex flex-row items-center justify-center gap-3">
|
||||
<Avatar
|
||||
className="h-[26px] w-[30px] text-xl"
|
||||
avatar={
|
||||
<img
|
||||
src={Sources}
|
||||
alt={t('conversation.sources.title')}
|
||||
className="h-full w-full object-fill"
|
||||
sources?.some((source) => source.link === 'None')
|
||||
? null
|
||||
: sources && (
|
||||
<div className="mb-4 flex flex-col flex-wrap items-start self-start lg:flex-nowrap">
|
||||
<div className="my-2 flex flex-row items-center justify-center gap-3">
|
||||
<Avatar
|
||||
className="h-[26px] w-[30px] text-xl"
|
||||
avatar={
|
||||
<img
|
||||
src={Sources}
|
||||
alt={t('conversation.sources.title')}
|
||||
className="h-full w-full object-fill"
|
||||
/>
|
||||
}
|
||||
/>
|
||||
}
|
||||
/>
|
||||
<p className="text-base font-semibold">
|
||||
{t('conversation.sources.title')}
|
||||
</p>
|
||||
</div>
|
||||
<div className="grid grid-cols-2 gap-2 lg:grid-cols-4">
|
||||
{Array.from({ length: 4 }).map((_, index) => (
|
||||
<div
|
||||
key={index}
|
||||
className="bg-gray-1000 text-purple-30 dark:bg-gun-metal flex h-28 cursor-pointer flex-col items-start gap-1 rounded-[20px] p-4 hover:bg-[#F1F1F1] hover:text-[#6D3ECC] dark:hover:bg-[#2C2E3C] dark:hover:text-[#8C67D7]"
|
||||
>
|
||||
<span className="h-px w-10 animate-pulse cursor-pointer rounded-[20px] bg-[#B2B2B2] p-1"></span>
|
||||
<span className="h-px w-24 animate-pulse cursor-pointer rounded-[20px] bg-[#B2B2B2] p-1"></span>
|
||||
<span className="h-px w-16 animate-pulse cursor-pointer rounded-[20px] bg-[#B2B2B2] p-1"></span>
|
||||
<span className="h-px w-32 animate-pulse cursor-pointer rounded-[20px] bg-[#B2B2B2] p-1"></span>
|
||||
<span className="h-px w-24 animate-pulse cursor-pointer rounded-[20px] bg-[#B2B2B2] p-1"></span>
|
||||
<span className="h-px w-20 animate-pulse cursor-pointer rounded-[20px] bg-[#B2B2B2] p-1"></span>
|
||||
<p className="text-base font-semibold">
|
||||
{t('conversation.sources.title')}
|
||||
</p>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
) : (
|
||||
sources && (
|
||||
<div className="mb-4 flex flex-col flex-wrap items-start self-start lg:flex-nowrap">
|
||||
<div className="my-2 flex flex-row items-center justify-center gap-3">
|
||||
<Avatar
|
||||
className="h-[26px] w-[30px] text-xl"
|
||||
avatar={
|
||||
<img
|
||||
src={Sources}
|
||||
alt={t('conversation.sources.title')}
|
||||
className="h-full w-full object-fill"
|
||||
/>
|
||||
}
|
||||
/>
|
||||
<p className="text-base font-semibold">
|
||||
{t('conversation.sources.title')}
|
||||
</p>
|
||||
</div>
|
||||
<div className="fade-in mr-5 ml-3 max-w-[90vw] md:max-w-[70vw] lg:max-w-[50vw]">
|
||||
<div className="grid grid-cols-2 gap-2 lg:grid-cols-4">
|
||||
{sources?.slice(0, 3)?.map((source, index) => (
|
||||
<div key={index} className="relative">
|
||||
<div
|
||||
className="bg-gray-1000 dark:bg-gun-metal h-28 cursor-pointer rounded-[20px] p-4 hover:bg-[#F1F1F1] dark:hover:bg-[#2C2E3C]"
|
||||
onMouseOver={() => setActiveTooltip(index)}
|
||||
onMouseOut={() => setActiveTooltip(null)}
|
||||
>
|
||||
<p className="ellipsis-text h-12 text-xs break-words">
|
||||
{source.text}
|
||||
</p>
|
||||
<div className="fade-in mr-5 ml-3 max-w-[90vw] md:max-w-[70vw] lg:max-w-[50vw]">
|
||||
<div className="grid grid-cols-2 gap-2 lg:grid-cols-4">
|
||||
{sources?.slice(0, 3)?.map((source, index) => (
|
||||
<div key={index} className="relative">
|
||||
<div
|
||||
className={`mt-[14px] flex flex-row items-center gap-[6px] underline-offset-2 ${
|
||||
source.link && source.link !== 'local'
|
||||
? 'hover:text-[#007DFF] hover:underline dark:hover:text-[#48A0FF]'
|
||||
: ''
|
||||
}`}
|
||||
onClick={() =>
|
||||
source.link && source.link !== 'local'
|
||||
? window.open(
|
||||
source.link,
|
||||
'_blank',
|
||||
'noopener, noreferrer',
|
||||
)
|
||||
: null
|
||||
}
|
||||
>
|
||||
<img
|
||||
src={Document}
|
||||
alt="Document"
|
||||
className="h-[17px] w-[17px] object-fill"
|
||||
/>
|
||||
<p
|
||||
className="mt-[2px] truncate text-xs"
|
||||
title={
|
||||
source.link && source.link !== 'local'
|
||||
? source.link
|
||||
: source.title
|
||||
}
|
||||
>
|
||||
{source.link && source.link !== 'local'
|
||||
? source.link
|
||||
: source.title}
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
{activeTooltip === index && (
|
||||
<div
|
||||
className={`dark:bg-chinese-black dark:text-chinese-silver absolute left-1/2 z-50 max-h-48 w-40 translate-x-[-50%] translate-y-[3px] rounded-xl bg-[#FBFBFB] p-4 text-black shadow-xl sm:w-56`}
|
||||
className="bg-gray-1000 dark:bg-gun-metal h-28 cursor-pointer rounded-[20px] p-4 hover:bg-[#F1F1F1] dark:hover:bg-[#2C2E3C]"
|
||||
onMouseOver={() => setActiveTooltip(index)}
|
||||
onMouseOut={() => setActiveTooltip(null)}
|
||||
>
|
||||
<p className="line-clamp-6 max-h-[164px] overflow-hidden rounded-md text-sm break-words text-ellipsis">
|
||||
<p className="ellipsis-text h-12 text-xs break-words">
|
||||
{source.text}
|
||||
</p>
|
||||
<div
|
||||
className={`mt-[14px] flex flex-row items-center gap-[6px] underline-offset-2 ${
|
||||
source.link && source.link !== 'local'
|
||||
? 'hover:text-[#007DFF] hover:underline dark:hover:text-[#48A0FF]'
|
||||
: ''
|
||||
}`}
|
||||
onClick={() =>
|
||||
source.link && source.link !== 'local'
|
||||
? window.open(
|
||||
source.link,
|
||||
'_blank',
|
||||
'noopener, noreferrer',
|
||||
)
|
||||
: null
|
||||
}
|
||||
>
|
||||
<img
|
||||
src={Document}
|
||||
alt="Document"
|
||||
className="h-[17px] w-[17px] object-fill"
|
||||
/>
|
||||
<p
|
||||
className="mt-[2px] truncate text-xs"
|
||||
title={
|
||||
source.link && source.link !== 'local'
|
||||
? source.link
|
||||
: source.title
|
||||
}
|
||||
>
|
||||
{source.link && source.link !== 'local'
|
||||
? source.link
|
||||
: source.title}
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
))}
|
||||
{(sources?.length ?? 0) > 3 && (
|
||||
<div
|
||||
className="bg-gray-1000 text-purple-30 dark:bg-gun-metal flex h-28 cursor-pointer flex-col-reverse rounded-[20px] p-4 hover:bg-[#F1F1F1] hover:text-[#6D3ECC] dark:hover:bg-[#2C2E3C] dark:hover:text-[#8C67D7]"
|
||||
onClick={() => setIsSidebarOpen(true)}
|
||||
>
|
||||
<p className="ellipsis-text h-22 text-xs">
|
||||
{t('conversation.sources.view_more', {
|
||||
count: sources?.length ? sources.length - 3 : 0,
|
||||
})}
|
||||
</p>
|
||||
</div>
|
||||
)}
|
||||
{activeTooltip === index && (
|
||||
<div
|
||||
className={`dark:bg-chinese-black dark:text-chinese-silver absolute left-1/2 z-50 max-h-48 w-40 translate-x-[-50%] translate-y-[3px] rounded-xl bg-[#FBFBFB] p-4 text-black shadow-xl sm:w-56`}
|
||||
onMouseOver={() => setActiveTooltip(index)}
|
||||
onMouseOut={() => setActiveTooltip(null)}
|
||||
>
|
||||
<p className="line-clamp-6 max-h-[164px] overflow-hidden rounded-md text-sm break-words text-ellipsis">
|
||||
{source.text}
|
||||
</p>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
))}
|
||||
{(sources?.length ?? 0) > 3 && (
|
||||
<div
|
||||
className="bg-gray-1000 text-purple-30 dark:bg-gun-metal flex h-28 cursor-pointer flex-col-reverse rounded-[20px] p-4 hover:bg-[#F1F1F1] hover:text-[#6D3ECC] dark:hover:bg-[#2C2E3C] dark:hover:text-[#8C67D7]"
|
||||
onClick={() => setIsSidebarOpen(true)}
|
||||
>
|
||||
<p className="ellipsis-text h-22 text-xs">
|
||||
{t('conversation.sources.view_more', {
|
||||
count: sources?.length ? sources.length - 3 : 0,
|
||||
})}
|
||||
</p>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
)}
|
||||
)}
|
||||
{toolCalls && toolCalls.length > 0 && (
|
||||
<ToolCalls toolCalls={toolCalls} />
|
||||
)}
|
||||
|
||||
@@ -284,14 +284,9 @@ export const conversationSlice = createSlice({
|
||||
query: Partial<Query>;
|
||||
}>,
|
||||
) {
|
||||
const { conversationId, index, query } = action.payload;
|
||||
if (state.conversationId !== conversationId) return;
|
||||
|
||||
if (!state.queries[index].sources) {
|
||||
state.queries[index].sources = query?.sources;
|
||||
} else if (query.sources) {
|
||||
state.queries[index].sources!.push(...query.sources);
|
||||
}
|
||||
const { index, query } = action.payload;
|
||||
if (query.sources !== undefined)
|
||||
state.queries[index].sources = query.sources;
|
||||
},
|
||||
updateToolCall(state, action) {
|
||||
const { index, tool_call } = action.payload;
|
||||
|
||||
@@ -33,6 +33,19 @@ export default function ChunkModal({
|
||||
setChunkText(originalText || '');
|
||||
}, [originalTitle, originalText]);
|
||||
|
||||
const resetForm = () => {
|
||||
setTitle('');
|
||||
setChunkText('');
|
||||
};
|
||||
|
||||
const handleDeleteConfirmed = () => {
|
||||
if (handleDelete) {
|
||||
handleDelete();
|
||||
}
|
||||
setDeleteModal('INACTIVE');
|
||||
setModalState('INACTIVE');
|
||||
};
|
||||
|
||||
if (modalState !== 'ACTIVE') return null;
|
||||
|
||||
const content = (
|
||||
@@ -71,6 +84,7 @@ export default function ChunkModal({
|
||||
onClick={() => {
|
||||
handleSubmit(title, chunkText);
|
||||
setModalState('INACTIVE');
|
||||
resetForm();
|
||||
}}
|
||||
className="bg-purple-30 hover:bg-violets-are-blue rounded-3xl px-5 py-2 text-sm text-white transition-all"
|
||||
>
|
||||
@@ -79,6 +93,7 @@ export default function ChunkModal({
|
||||
<button
|
||||
onClick={() => {
|
||||
setModalState('INACTIVE');
|
||||
resetForm();
|
||||
}}
|
||||
className="dark:text-light-gray cursor-pointer rounded-3xl px-5 py-2 text-sm font-medium hover:bg-gray-100 dark:bg-transparent dark:hover:bg-[#767183]/50"
|
||||
>
|
||||
@@ -124,6 +139,7 @@ export default function ChunkModal({
|
||||
<WrapperModal
|
||||
close={() => setModalState('INACTIVE')}
|
||||
className="sm:w-[620px]"
|
||||
isPerformingTask={true}
|
||||
>
|
||||
{content}
|
||||
</WrapperModal>
|
||||
@@ -133,13 +149,7 @@ export default function ChunkModal({
|
||||
message={t('modals.chunk.deleteConfirmation')}
|
||||
modalState={deleteModal}
|
||||
setModalState={setDeleteModal}
|
||||
handleSubmit={
|
||||
handleDelete
|
||||
? handleDelete
|
||||
: () => {
|
||||
/* no-op */
|
||||
}
|
||||
}
|
||||
handleSubmit={handleDeleteConfirmed}
|
||||
submitLabel={t('modals.chunk.delete')}
|
||||
/>
|
||||
)}
|
||||
|
||||
@@ -29,33 +29,40 @@ export default function ConfirmationModal({
|
||||
? 'rounded-3xl bg-rosso-corsa px-5 py-2 text-sm text-lotion transition-all hover:bg-red-2000 hover:font-bold tracking-[0.019em] hover:tracking-normal'
|
||||
: 'rounded-3xl bg-purple-30 px-5 py-2 text-sm text-lotion transition-all hover:bg-violets-are-blue';
|
||||
|
||||
const handleSubmitClick = (e: React.MouseEvent) => {
|
||||
e.preventDefault();
|
||||
e.stopPropagation();
|
||||
handleSubmit();
|
||||
setModalState('INACTIVE');
|
||||
};
|
||||
|
||||
const handleCancelClick = (e: React.MouseEvent) => {
|
||||
e.preventDefault();
|
||||
e.stopPropagation();
|
||||
setModalState('INACTIVE');
|
||||
handleCancel?.();
|
||||
};
|
||||
|
||||
return (
|
||||
<>
|
||||
{modalState === 'ACTIVE' && (
|
||||
<WrapperModal close={() => setModalState('INACTIVE')}>
|
||||
<div className="relative">
|
||||
<div>
|
||||
<p className="font-base mb-1 w-[90%] break-words text-lg text-jet dark:text-bright-gray">
|
||||
<p className="font-base text-jet dark:text-bright-gray mb-1 w-[90%] text-lg break-words">
|
||||
{message}
|
||||
</p>
|
||||
<div>
|
||||
<div className="mt-6 flex flex-row-reverse gap-1">
|
||||
<button
|
||||
onClick={(e) => {
|
||||
e.stopPropagation();
|
||||
handleSubmit();
|
||||
}}
|
||||
onClick={handleSubmitClick}
|
||||
className={submitButtonClasses}
|
||||
>
|
||||
{submitLabel}
|
||||
</button>
|
||||
<button
|
||||
onClick={(e) => {
|
||||
e.stopPropagation();
|
||||
setModalState('INACTIVE');
|
||||
handleCancel && handleCancel();
|
||||
}}
|
||||
className="cursor-pointer rounded-3xl px-5 py-2 text-sm font-medium hover:bg-gray-100 dark:bg-transparent dark:text-light-gray dark:hover:bg-[#767183]/50"
|
||||
onClick={handleCancelClick}
|
||||
className="dark:text-light-gray cursor-pointer rounded-3xl px-5 py-2 text-sm font-medium hover:bg-gray-100 dark:bg-transparent dark:hover:bg-[#767183]/50"
|
||||
>
|
||||
{cancelLabel ? cancelLabel : t('cancel')}
|
||||
</button>
|
||||
|
||||
@@ -3,38 +3,33 @@ import { createPortal } from 'react-dom';
|
||||
|
||||
import Exit from '../assets/exit.svg';
|
||||
|
||||
interface WrapperModalPropsType {
|
||||
type WrapperModalPropsType = {
|
||||
children: React.ReactNode;
|
||||
close: () => void;
|
||||
isPerformingTask?: boolean;
|
||||
className?: string;
|
||||
contentClassName?: string;
|
||||
}
|
||||
};
|
||||
|
||||
export default function WrapperModal({
|
||||
children,
|
||||
close,
|
||||
isPerformingTask = false,
|
||||
className = '', // Default width, but can be overridden
|
||||
contentClassName = '', // Default padding, but can be overridden
|
||||
className = '',
|
||||
contentClassName = '',
|
||||
}: WrapperModalPropsType) {
|
||||
const modalRef = useRef<HTMLDivElement>(null);
|
||||
|
||||
useEffect(() => {
|
||||
if (isPerformingTask) return;
|
||||
|
||||
const handleClickOutside = (event: MouseEvent) => {
|
||||
if (
|
||||
modalRef.current &&
|
||||
!modalRef.current.contains(event.target as Node)
|
||||
) {
|
||||
if (modalRef.current && !modalRef.current.contains(event.target as Node))
|
||||
close();
|
||||
}
|
||||
};
|
||||
|
||||
const handleEscapePress = (event: KeyboardEvent) => {
|
||||
if (event.key === 'Escape') {
|
||||
close();
|
||||
}
|
||||
if (event.key === 'Escape') close();
|
||||
};
|
||||
|
||||
document.addEventListener('mousedown', handleClickOutside);
|
||||
@@ -44,17 +39,17 @@ export default function WrapperModal({
|
||||
document.removeEventListener('mousedown', handleClickOutside);
|
||||
document.removeEventListener('keydown', handleEscapePress);
|
||||
};
|
||||
}, [close]);
|
||||
}, [close, isPerformingTask]);
|
||||
|
||||
const modalContent = (
|
||||
<div className="fixed left-0 top-0 z-30 flex h-screen w-screen items-center justify-center bg-gray-alpha bg-opacity-50">
|
||||
<div className="bg-gray-alpha bg-opacity-50 fixed top-0 left-0 z-30 flex h-screen w-screen items-center justify-center">
|
||||
<div
|
||||
ref={modalRef}
|
||||
className={`relative w-11/12 rounded-2xl bg-white p-8 dark:bg-[#26272E] sm:w-[512px] ${className}`}
|
||||
className={`relative w-11/12 rounded-2xl bg-white p-8 sm:w-[512px] dark:bg-[#26272E] ${className}`}
|
||||
>
|
||||
{!isPerformingTask && (
|
||||
<button
|
||||
className="absolute right-4 top-3 z-50 m-2 w-3"
|
||||
className="absolute top-3 right-4 z-50 m-2 w-3"
|
||||
onClick={close}
|
||||
>
|
||||
<img className="filter dark:invert" src={Exit} alt="Close" />
|
||||
|
||||
@@ -9,8 +9,10 @@ import Edit from '../assets/edit.svg';
|
||||
import EyeView from '../assets/eye-view.svg';
|
||||
import NoFilesDarkIcon from '../assets/no-files-dark.svg';
|
||||
import NoFilesIcon from '../assets/no-files.svg';
|
||||
import SyncIcon from '../assets/sync.svg';
|
||||
import Trash from '../assets/red-trash.svg';
|
||||
import SyncIcon from '../assets/sync.svg';
|
||||
import ThreeDots from '../assets/three-dots.svg';
|
||||
import ContextMenu, { MenuOption } from '../components/ContextMenu';
|
||||
import Pagination from '../components/DocumentPagination';
|
||||
import DropdownMenu from '../components/DropdownMenu';
|
||||
import Input from '../components/Input';
|
||||
@@ -29,8 +31,6 @@ import {
|
||||
import Upload from '../upload/Upload';
|
||||
import { formatDate } from '../utils/dateTimeUtils';
|
||||
import { ChunkType } from './types';
|
||||
import ContextMenu, { MenuOption } from '../components/ContextMenu';
|
||||
import ThreeDots from '../assets/three-dots.svg';
|
||||
|
||||
const formatTokens = (tokens: number): string => {
|
||||
const roundToTwoDecimals = (num: number): string => {
|
||||
@@ -766,19 +766,23 @@ function DocumentChunks({
|
||||
setModalState={setAddModal}
|
||||
handleSubmit={handleAddChunk}
|
||||
/>
|
||||
<ChunkModal
|
||||
type="EDIT"
|
||||
modalState={editModal.state}
|
||||
setModalState={(state) => setEditModal((prev) => ({ ...prev, state }))}
|
||||
handleSubmit={(title, text) => {
|
||||
handleUpdateChunk(title, text, editModal.chunk as ChunkType);
|
||||
}}
|
||||
originalText={editModal.chunk?.text}
|
||||
originalTitle={editModal.chunk?.metadata?.title}
|
||||
handleDelete={() => {
|
||||
handleDeleteChunk(editModal.chunk as ChunkType);
|
||||
}}
|
||||
/>
|
||||
{editModal.chunk && (
|
||||
<ChunkModal
|
||||
type="EDIT"
|
||||
modalState={editModal.state}
|
||||
setModalState={(state) =>
|
||||
setEditModal((prev) => ({ ...prev, state }))
|
||||
}
|
||||
handleSubmit={(title, text) => {
|
||||
handleUpdateChunk(title, text, editModal.chunk as ChunkType);
|
||||
}}
|
||||
originalText={editModal.chunk?.text ?? ''}
|
||||
originalTitle={editModal.chunk?.metadata?.title ?? ''}
|
||||
handleDelete={() => {
|
||||
handleDeleteChunk(editModal.chunk as ChunkType);
|
||||
}}
|
||||
/>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user