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feat: implement agent caches and fix invalid prompt cache configs
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- Added a new function `_warm_agent_jit_caches` to pre-warm agent caches at startup, reducing cold invocation costs. - Updated the `SurfSenseContextSchema` to include per-invocation fields for better state management during agent execution. - Introduced caching mechanisms in various tools to ensure fresh database sessions are used, improving performance and reliability. - Enhanced middleware to support new context features and improve error handling during connector and document type discovery.
This commit is contained in:
DESKTOP-RTLN3BA\$punk
parent
90a653c8c7
commit
a34f1fb25c
60 changed files with 8477 additions and 5381 deletions
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@ -6,6 +6,7 @@ from sqlalchemy.ext.asyncio import AsyncSession
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from app.agents.new_chat.tools.hitl import request_approval
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from app.connectors.linear_connector import LinearAPIError, LinearConnector
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from app.db import async_session_maker
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from app.services.linear import LinearToolMetadataService
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logger = logging.getLogger(__name__)
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@ -17,11 +18,17 @@ def create_create_linear_issue_tool(
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user_id: str | None = None,
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connector_id: int | None = None,
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):
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"""
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Factory function to create the create_linear_issue tool.
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"""Factory function to create the create_linear_issue tool.
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The tool acquires its own short-lived ``AsyncSession`` per call via
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:data:`async_session_maker`. This is critical for the compiled-agent
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cache: the compiled graph (and therefore this closure) is reused
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across HTTP requests, so capturing a per-request session here would
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surface stale/closed sessions on cache hits.
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Args:
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db_session: Database session for accessing the Linear connector
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db_session: Reserved for registry compatibility. Per-call sessions
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are opened via :data:`async_session_maker` inside the tool body.
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search_space_id: Search space ID to find the Linear connector
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user_id: User ID for fetching user-specific context
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connector_id: Optional specific connector ID (if known)
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@ -29,6 +36,7 @@ def create_create_linear_issue_tool(
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Returns:
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Configured create_linear_issue tool
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"""
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del db_session # per-call session — see docstring
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@tool
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async def create_linear_issue(
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@ -65,7 +73,7 @@ def create_create_linear_issue_tool(
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"""
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logger.info(f"create_linear_issue called: title='{title}'")
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if db_session is None or search_space_id is None or user_id is None:
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if search_space_id is None or user_id is None:
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logger.error(
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"Linear tool not properly configured - missing required parameters"
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)
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@ -75,160 +83,170 @@ def create_create_linear_issue_tool(
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}
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try:
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metadata_service = LinearToolMetadataService(db_session)
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context = await metadata_service.get_creation_context(
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search_space_id, user_id
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)
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if "error" in context:
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logger.error(f"Failed to fetch creation context: {context['error']}")
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return {"status": "error", "message": context["error"]}
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workspaces = context.get("workspaces", [])
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if workspaces and all(w.get("auth_expired") for w in workspaces):
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logger.warning("All Linear accounts have expired authentication")
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return {
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"status": "auth_error",
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"message": "All connected Linear accounts need re-authentication. Please re-authenticate in your connector settings.",
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"connector_type": "linear",
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}
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logger.info(f"Requesting approval for creating Linear issue: '{title}'")
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result = request_approval(
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action_type="linear_issue_creation",
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tool_name="create_linear_issue",
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params={
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"title": title,
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"description": description,
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"team_id": None,
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"state_id": None,
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"assignee_id": None,
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"priority": None,
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"label_ids": [],
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"connector_id": connector_id,
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},
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context=context,
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)
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if result.rejected:
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logger.info("Linear issue creation rejected by user")
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return {
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"status": "rejected",
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"message": "User declined. Do not retry or suggest alternatives.",
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}
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final_title = result.params.get("title", title)
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final_description = result.params.get("description", description)
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final_team_id = result.params.get("team_id")
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final_state_id = result.params.get("state_id")
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final_assignee_id = result.params.get("assignee_id")
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final_priority = result.params.get("priority")
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final_label_ids = result.params.get("label_ids") or []
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final_connector_id = result.params.get("connector_id", connector_id)
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if not final_title or not final_title.strip():
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logger.error("Title is empty or contains only whitespace")
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return {"status": "error", "message": "Issue title cannot be empty."}
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if not final_team_id:
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return {
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"status": "error",
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"message": "A team must be selected to create an issue.",
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}
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from sqlalchemy.future import select
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from app.db import SearchSourceConnector, SearchSourceConnectorType
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actual_connector_id = final_connector_id
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if actual_connector_id is None:
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result = await db_session.execute(
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select(SearchSourceConnector).filter(
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SearchSourceConnector.search_space_id == search_space_id,
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SearchSourceConnector.user_id == user_id,
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SearchSourceConnector.connector_type
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== SearchSourceConnectorType.LINEAR_CONNECTOR,
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)
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async with async_session_maker() as db_session:
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metadata_service = LinearToolMetadataService(db_session)
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context = await metadata_service.get_creation_context(
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search_space_id, user_id
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)
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connector = result.scalars().first()
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if not connector:
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if "error" in context:
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logger.error(
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f"Failed to fetch creation context: {context['error']}"
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)
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return {"status": "error", "message": context["error"]}
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workspaces = context.get("workspaces", [])
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if workspaces and all(w.get("auth_expired") for w in workspaces):
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logger.warning("All Linear accounts have expired authentication")
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return {
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"status": "auth_error",
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"message": "All connected Linear accounts need re-authentication. Please re-authenticate in your connector settings.",
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"connector_type": "linear",
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}
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logger.info(f"Requesting approval for creating Linear issue: '{title}'")
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result = request_approval(
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action_type="linear_issue_creation",
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tool_name="create_linear_issue",
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params={
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"title": title,
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"description": description,
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"team_id": None,
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"state_id": None,
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"assignee_id": None,
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"priority": None,
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"label_ids": [],
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"connector_id": connector_id,
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},
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context=context,
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)
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if result.rejected:
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logger.info("Linear issue creation rejected by user")
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return {
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"status": "rejected",
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"message": "User declined. Do not retry or suggest alternatives.",
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}
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final_title = result.params.get("title", title)
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final_description = result.params.get("description", description)
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final_team_id = result.params.get("team_id")
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final_state_id = result.params.get("state_id")
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final_assignee_id = result.params.get("assignee_id")
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final_priority = result.params.get("priority")
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final_label_ids = result.params.get("label_ids") or []
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final_connector_id = result.params.get("connector_id", connector_id)
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if not final_title or not final_title.strip():
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logger.error("Title is empty or contains only whitespace")
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return {
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"status": "error",
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"message": "No Linear connector found. Please connect Linear in your workspace settings.",
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"message": "Issue title cannot be empty.",
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}
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actual_connector_id = connector.id
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logger.info(f"Found Linear connector: id={actual_connector_id}")
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else:
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result = await db_session.execute(
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select(SearchSourceConnector).filter(
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SearchSourceConnector.id == actual_connector_id,
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SearchSourceConnector.search_space_id == search_space_id,
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SearchSourceConnector.user_id == user_id,
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SearchSourceConnector.connector_type
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== SearchSourceConnectorType.LINEAR_CONNECTOR,
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)
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)
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connector = result.scalars().first()
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if not connector:
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if not final_team_id:
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return {
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"status": "error",
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"message": "Selected Linear connector is invalid or has been disconnected.",
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"message": "A team must be selected to create an issue.",
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}
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logger.info(f"Validated Linear connector: id={actual_connector_id}")
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logger.info(
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f"Creating Linear issue with final params: title='{final_title}'"
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)
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linear_client = LinearConnector(
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session=db_session, connector_id=actual_connector_id
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)
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result = await linear_client.create_issue(
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team_id=final_team_id,
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title=final_title,
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description=final_description,
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state_id=final_state_id,
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assignee_id=final_assignee_id,
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priority=final_priority,
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label_ids=final_label_ids if final_label_ids else None,
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)
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from sqlalchemy.future import select
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if result.get("status") == "error":
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logger.error(f"Failed to create Linear issue: {result.get('message')}")
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return {"status": "error", "message": result.get("message")}
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from app.db import SearchSourceConnector, SearchSourceConnectorType
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logger.info(
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f"Linear issue created: {result.get('identifier')} - {result.get('title')}"
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)
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kb_message_suffix = ""
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try:
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from app.services.linear import LinearKBSyncService
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kb_service = LinearKBSyncService(db_session)
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kb_result = await kb_service.sync_after_create(
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issue_id=result.get("id"),
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issue_identifier=result.get("identifier", ""),
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issue_title=result.get("title", final_title),
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issue_url=result.get("url"),
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description=final_description,
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connector_id=actual_connector_id,
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search_space_id=search_space_id,
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user_id=user_id,
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)
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if kb_result["status"] == "success":
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kb_message_suffix = " Your knowledge base has also been updated."
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actual_connector_id = final_connector_id
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if actual_connector_id is None:
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result = await db_session.execute(
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select(SearchSourceConnector).filter(
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SearchSourceConnector.search_space_id == search_space_id,
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SearchSourceConnector.user_id == user_id,
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SearchSourceConnector.connector_type
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== SearchSourceConnectorType.LINEAR_CONNECTOR,
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)
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)
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connector = result.scalars().first()
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if not connector:
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return {
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"status": "error",
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"message": "No Linear connector found. Please connect Linear in your workspace settings.",
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}
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actual_connector_id = connector.id
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logger.info(f"Found Linear connector: id={actual_connector_id}")
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else:
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kb_message_suffix = " This issue will be added to your knowledge base in the next scheduled sync."
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except Exception as kb_err:
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logger.warning(f"KB sync after create failed: {kb_err}")
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kb_message_suffix = " This issue will be added to your knowledge base in the next scheduled sync."
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result = await db_session.execute(
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select(SearchSourceConnector).filter(
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SearchSourceConnector.id == actual_connector_id,
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SearchSourceConnector.search_space_id == search_space_id,
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SearchSourceConnector.user_id == user_id,
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SearchSourceConnector.connector_type
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== SearchSourceConnectorType.LINEAR_CONNECTOR,
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)
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)
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connector = result.scalars().first()
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if not connector:
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return {
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"status": "error",
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"message": "Selected Linear connector is invalid or has been disconnected.",
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}
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logger.info(f"Validated Linear connector: id={actual_connector_id}")
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return {
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"status": "success",
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"issue_id": result.get("id"),
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"identifier": result.get("identifier"),
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"url": result.get("url"),
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"message": (result.get("message", "") + kb_message_suffix),
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}
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logger.info(
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f"Creating Linear issue with final params: title='{final_title}'"
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)
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linear_client = LinearConnector(
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session=db_session, connector_id=actual_connector_id
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)
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result = await linear_client.create_issue(
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team_id=final_team_id,
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title=final_title,
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description=final_description,
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state_id=final_state_id,
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assignee_id=final_assignee_id,
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priority=final_priority,
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label_ids=final_label_ids if final_label_ids else None,
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)
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if result.get("status") == "error":
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logger.error(
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f"Failed to create Linear issue: {result.get('message')}"
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)
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return {"status": "error", "message": result.get("message")}
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logger.info(
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f"Linear issue created: {result.get('identifier')} - {result.get('title')}"
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)
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kb_message_suffix = ""
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try:
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from app.services.linear import LinearKBSyncService
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kb_service = LinearKBSyncService(db_session)
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kb_result = await kb_service.sync_after_create(
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issue_id=result.get("id"),
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issue_identifier=result.get("identifier", ""),
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issue_title=result.get("title", final_title),
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issue_url=result.get("url"),
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description=final_description,
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connector_id=actual_connector_id,
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search_space_id=search_space_id,
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user_id=user_id,
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)
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if kb_result["status"] == "success":
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kb_message_suffix = (
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" Your knowledge base has also been updated."
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)
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else:
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kb_message_suffix = " This issue will be added to your knowledge base in the next scheduled sync."
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except Exception as kb_err:
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logger.warning(f"KB sync after create failed: {kb_err}")
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kb_message_suffix = " This issue will be added to your knowledge base in the next scheduled sync."
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return {
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"status": "success",
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"issue_id": result.get("id"),
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"identifier": result.get("identifier"),
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"url": result.get("url"),
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"message": (result.get("message", "") + kb_message_suffix),
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}
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except Exception as e:
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from langgraph.errors import GraphInterrupt
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|
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@ -6,6 +6,7 @@ from sqlalchemy.ext.asyncio import AsyncSession
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from app.agents.new_chat.tools.hitl import request_approval
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from app.connectors.linear_connector import LinearAPIError, LinearConnector
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from app.db import async_session_maker
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from app.services.linear import LinearToolMetadataService
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logger = logging.getLogger(__name__)
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@ -17,11 +18,17 @@ def create_delete_linear_issue_tool(
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user_id: str | None = None,
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connector_id: int | None = None,
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):
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"""
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Factory function to create the delete_linear_issue tool.
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"""Factory function to create the delete_linear_issue tool.
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|
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The tool acquires its own short-lived ``AsyncSession`` per call via
|
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:data:`async_session_maker`. This is critical for the compiled-agent
|
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cache: the compiled graph (and therefore this closure) is reused
|
||||
across HTTP requests, so capturing a per-request session here would
|
||||
surface stale/closed sessions on cache hits.
|
||||
|
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Args:
|
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db_session: Database session for accessing the Linear connector
|
||||
db_session: Reserved for registry compatibility. Per-call sessions
|
||||
are opened via :data:`async_session_maker` inside the tool body.
|
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search_space_id: Search space ID to find the Linear connector
|
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user_id: User ID for finding the correct Linear connector
|
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connector_id: Optional specific connector ID (if known)
|
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|
|
@ -29,6 +36,7 @@ def create_delete_linear_issue_tool(
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Returns:
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Configured delete_linear_issue tool
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"""
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del db_session # per-call session — see docstring
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|
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@tool
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async def delete_linear_issue(
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|
|
@ -73,7 +81,7 @@ def create_delete_linear_issue_tool(
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f"delete_linear_issue called: issue_ref='{issue_ref}', delete_from_kb={delete_from_kb}"
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)
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if db_session is None or search_space_id is None or user_id is None:
|
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if search_space_id is None or user_id is None:
|
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logger.error(
|
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"Linear tool not properly configured - missing required parameters"
|
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)
|
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|
|
@ -83,149 +91,152 @@ def create_delete_linear_issue_tool(
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}
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try:
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metadata_service = LinearToolMetadataService(db_session)
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context = await metadata_service.get_delete_context(
|
||||
search_space_id, user_id, issue_ref
|
||||
)
|
||||
|
||||
if "error" in context:
|
||||
error_msg = context["error"]
|
||||
if context.get("auth_expired"):
|
||||
logger.warning(f"Auth expired for delete context: {error_msg}")
|
||||
return {
|
||||
"status": "auth_error",
|
||||
"message": error_msg,
|
||||
"connector_id": context.get("connector_id"),
|
||||
"connector_type": "linear",
|
||||
}
|
||||
if "not found" in error_msg.lower():
|
||||
logger.warning(f"Issue not found: {error_msg}")
|
||||
return {"status": "not_found", "message": error_msg}
|
||||
else:
|
||||
logger.error(f"Failed to fetch delete context: {error_msg}")
|
||||
return {"status": "error", "message": error_msg}
|
||||
|
||||
issue_id = context["issue"]["id"]
|
||||
issue_identifier = context["issue"].get("identifier", "")
|
||||
document_id = context["issue"]["document_id"]
|
||||
connector_id_from_context = context.get("workspace", {}).get("id")
|
||||
|
||||
logger.info(
|
||||
f"Requesting approval for deleting Linear issue: '{issue_ref}' "
|
||||
f"(id={issue_id}, delete_from_kb={delete_from_kb})"
|
||||
)
|
||||
result = request_approval(
|
||||
action_type="linear_issue_deletion",
|
||||
tool_name="delete_linear_issue",
|
||||
params={
|
||||
"issue_id": issue_id,
|
||||
"connector_id": connector_id_from_context,
|
||||
"delete_from_kb": delete_from_kb,
|
||||
},
|
||||
context=context,
|
||||
)
|
||||
|
||||
if result.rejected:
|
||||
logger.info("Linear issue deletion rejected by user")
|
||||
return {
|
||||
"status": "rejected",
|
||||
"message": "User declined. Do not retry or suggest alternatives.",
|
||||
}
|
||||
|
||||
final_issue_id = result.params.get("issue_id", issue_id)
|
||||
final_connector_id = result.params.get(
|
||||
"connector_id", connector_id_from_context
|
||||
)
|
||||
final_delete_from_kb = result.params.get("delete_from_kb", delete_from_kb)
|
||||
|
||||
logger.info(
|
||||
f"Deleting Linear issue with final params: issue_id={final_issue_id}, "
|
||||
f"connector_id={final_connector_id}, delete_from_kb={final_delete_from_kb}"
|
||||
)
|
||||
|
||||
from sqlalchemy.future import select
|
||||
|
||||
from app.db import SearchSourceConnector, SearchSourceConnectorType
|
||||
|
||||
if final_connector_id:
|
||||
result = await db_session.execute(
|
||||
select(SearchSourceConnector).filter(
|
||||
SearchSourceConnector.id == final_connector_id,
|
||||
SearchSourceConnector.search_space_id == search_space_id,
|
||||
SearchSourceConnector.user_id == user_id,
|
||||
SearchSourceConnector.connector_type
|
||||
== SearchSourceConnectorType.LINEAR_CONNECTOR,
|
||||
)
|
||||
async with async_session_maker() as db_session:
|
||||
metadata_service = LinearToolMetadataService(db_session)
|
||||
context = await metadata_service.get_delete_context(
|
||||
search_space_id, user_id, issue_ref
|
||||
)
|
||||
connector = result.scalars().first()
|
||||
if not connector:
|
||||
logger.error(
|
||||
f"Invalid connector_id={final_connector_id} for search_space_id={search_space_id}"
|
||||
|
||||
if "error" in context:
|
||||
error_msg = context["error"]
|
||||
if context.get("auth_expired"):
|
||||
logger.warning(f"Auth expired for delete context: {error_msg}")
|
||||
return {
|
||||
"status": "auth_error",
|
||||
"message": error_msg,
|
||||
"connector_id": context.get("connector_id"),
|
||||
"connector_type": "linear",
|
||||
}
|
||||
if "not found" in error_msg.lower():
|
||||
logger.warning(f"Issue not found: {error_msg}")
|
||||
return {"status": "not_found", "message": error_msg}
|
||||
else:
|
||||
logger.error(f"Failed to fetch delete context: {error_msg}")
|
||||
return {"status": "error", "message": error_msg}
|
||||
|
||||
issue_id = context["issue"]["id"]
|
||||
issue_identifier = context["issue"].get("identifier", "")
|
||||
document_id = context["issue"]["document_id"]
|
||||
connector_id_from_context = context.get("workspace", {}).get("id")
|
||||
|
||||
logger.info(
|
||||
f"Requesting approval for deleting Linear issue: '{issue_ref}' "
|
||||
f"(id={issue_id}, delete_from_kb={delete_from_kb})"
|
||||
)
|
||||
result = request_approval(
|
||||
action_type="linear_issue_deletion",
|
||||
tool_name="delete_linear_issue",
|
||||
params={
|
||||
"issue_id": issue_id,
|
||||
"connector_id": connector_id_from_context,
|
||||
"delete_from_kb": delete_from_kb,
|
||||
},
|
||||
context=context,
|
||||
)
|
||||
|
||||
if result.rejected:
|
||||
logger.info("Linear issue deletion rejected by user")
|
||||
return {
|
||||
"status": "rejected",
|
||||
"message": "User declined. Do not retry or suggest alternatives.",
|
||||
}
|
||||
|
||||
final_issue_id = result.params.get("issue_id", issue_id)
|
||||
final_connector_id = result.params.get(
|
||||
"connector_id", connector_id_from_context
|
||||
)
|
||||
final_delete_from_kb = result.params.get(
|
||||
"delete_from_kb", delete_from_kb
|
||||
)
|
||||
|
||||
logger.info(
|
||||
f"Deleting Linear issue with final params: issue_id={final_issue_id}, "
|
||||
f"connector_id={final_connector_id}, delete_from_kb={final_delete_from_kb}"
|
||||
)
|
||||
|
||||
from sqlalchemy.future import select
|
||||
|
||||
from app.db import SearchSourceConnector, SearchSourceConnectorType
|
||||
|
||||
if final_connector_id:
|
||||
result = await db_session.execute(
|
||||
select(SearchSourceConnector).filter(
|
||||
SearchSourceConnector.id == final_connector_id,
|
||||
SearchSourceConnector.search_space_id == search_space_id,
|
||||
SearchSourceConnector.user_id == user_id,
|
||||
SearchSourceConnector.connector_type
|
||||
== SearchSourceConnectorType.LINEAR_CONNECTOR,
|
||||
)
|
||||
)
|
||||
connector = result.scalars().first()
|
||||
if not connector:
|
||||
logger.error(
|
||||
f"Invalid connector_id={final_connector_id} for search_space_id={search_space_id}"
|
||||
)
|
||||
return {
|
||||
"status": "error",
|
||||
"message": "Selected Linear connector is invalid or has been disconnected.",
|
||||
}
|
||||
actual_connector_id = connector.id
|
||||
logger.info(f"Validated Linear connector: id={actual_connector_id}")
|
||||
else:
|
||||
logger.error("No connector found for this issue")
|
||||
return {
|
||||
"status": "error",
|
||||
"message": "Selected Linear connector is invalid or has been disconnected.",
|
||||
"message": "No connector found for this issue.",
|
||||
}
|
||||
actual_connector_id = connector.id
|
||||
logger.info(f"Validated Linear connector: id={actual_connector_id}")
|
||||
else:
|
||||
logger.error("No connector found for this issue")
|
||||
return {
|
||||
"status": "error",
|
||||
"message": "No connector found for this issue.",
|
||||
}
|
||||
|
||||
linear_client = LinearConnector(
|
||||
session=db_session, connector_id=actual_connector_id
|
||||
)
|
||||
linear_client = LinearConnector(
|
||||
session=db_session, connector_id=actual_connector_id
|
||||
)
|
||||
|
||||
result = await linear_client.archive_issue(issue_id=final_issue_id)
|
||||
result = await linear_client.archive_issue(issue_id=final_issue_id)
|
||||
|
||||
logger.info(
|
||||
f"archive_issue result: {result.get('status')} - {result.get('message', '')}"
|
||||
)
|
||||
logger.info(
|
||||
f"archive_issue result: {result.get('status')} - {result.get('message', '')}"
|
||||
)
|
||||
|
||||
deleted_from_kb = False
|
||||
if (
|
||||
result.get("status") == "success"
|
||||
and final_delete_from_kb
|
||||
and document_id
|
||||
):
|
||||
try:
|
||||
from app.db import Document
|
||||
deleted_from_kb = False
|
||||
if (
|
||||
result.get("status") == "success"
|
||||
and final_delete_from_kb
|
||||
and document_id
|
||||
):
|
||||
try:
|
||||
from app.db import Document
|
||||
|
||||
doc_result = await db_session.execute(
|
||||
select(Document).filter(Document.id == document_id)
|
||||
)
|
||||
document = doc_result.scalars().first()
|
||||
if document:
|
||||
await db_session.delete(document)
|
||||
await db_session.commit()
|
||||
deleted_from_kb = True
|
||||
logger.info(
|
||||
f"Deleted document {document_id} from knowledge base"
|
||||
doc_result = await db_session.execute(
|
||||
select(Document).filter(Document.id == document_id)
|
||||
)
|
||||
document = doc_result.scalars().first()
|
||||
if document:
|
||||
await db_session.delete(document)
|
||||
await db_session.commit()
|
||||
deleted_from_kb = True
|
||||
logger.info(
|
||||
f"Deleted document {document_id} from knowledge base"
|
||||
)
|
||||
else:
|
||||
logger.warning(f"Document {document_id} not found in KB")
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to delete document from KB: {e}")
|
||||
await db_session.rollback()
|
||||
result["warning"] = (
|
||||
f"Issue archived in Linear, but failed to remove from knowledge base: {e!s}"
|
||||
)
|
||||
else:
|
||||
logger.warning(f"Document {document_id} not found in KB")
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to delete document from KB: {e}")
|
||||
await db_session.rollback()
|
||||
result["warning"] = (
|
||||
f"Issue archived in Linear, but failed to remove from knowledge base: {e!s}"
|
||||
)
|
||||
|
||||
if result.get("status") == "success":
|
||||
result["deleted_from_kb"] = deleted_from_kb
|
||||
if issue_identifier:
|
||||
result["message"] = (
|
||||
f"Issue {issue_identifier} archived successfully."
|
||||
)
|
||||
if deleted_from_kb:
|
||||
result["message"] = (
|
||||
f"{result.get('message', '')} Also removed from the knowledge base."
|
||||
)
|
||||
if result.get("status") == "success":
|
||||
result["deleted_from_kb"] = deleted_from_kb
|
||||
if issue_identifier:
|
||||
result["message"] = (
|
||||
f"Issue {issue_identifier} archived successfully."
|
||||
)
|
||||
if deleted_from_kb:
|
||||
result["message"] = (
|
||||
f"{result.get('message', '')} Also removed from the knowledge base."
|
||||
)
|
||||
|
||||
return result
|
||||
return result
|
||||
|
||||
except Exception as e:
|
||||
from langgraph.errors import GraphInterrupt
|
||||
|
|
|
|||
|
|
@ -6,6 +6,7 @@ from sqlalchemy.ext.asyncio import AsyncSession
|
|||
|
||||
from app.agents.new_chat.tools.hitl import request_approval
|
||||
from app.connectors.linear_connector import LinearAPIError, LinearConnector
|
||||
from app.db import async_session_maker
|
||||
from app.services.linear import LinearKBSyncService, LinearToolMetadataService
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
|
@ -17,11 +18,17 @@ def create_update_linear_issue_tool(
|
|||
user_id: str | None = None,
|
||||
connector_id: int | None = None,
|
||||
):
|
||||
"""
|
||||
Factory function to create the update_linear_issue tool.
|
||||
"""Factory function to create the update_linear_issue tool.
|
||||
|
||||
The tool acquires its own short-lived ``AsyncSession`` per call via
|
||||
:data:`async_session_maker`. This is critical for the compiled-agent
|
||||
cache: the compiled graph (and therefore this closure) is reused
|
||||
across HTTP requests, so capturing a per-request session here would
|
||||
surface stale/closed sessions on cache hits.
|
||||
|
||||
Args:
|
||||
db_session: Database session for accessing the Linear connector
|
||||
db_session: Reserved for registry compatibility. Per-call sessions
|
||||
are opened via :data:`async_session_maker` inside the tool body.
|
||||
search_space_id: Search space ID to find the Linear connector
|
||||
user_id: User ID for fetching user-specific context
|
||||
connector_id: Optional specific connector ID (if known)
|
||||
|
|
@ -29,6 +36,7 @@ def create_update_linear_issue_tool(
|
|||
Returns:
|
||||
Configured update_linear_issue tool
|
||||
"""
|
||||
del db_session # per-call session — see docstring
|
||||
|
||||
@tool
|
||||
async def update_linear_issue(
|
||||
|
|
@ -86,7 +94,7 @@ def create_update_linear_issue_tool(
|
|||
"""
|
||||
logger.info(f"update_linear_issue called: issue_ref='{issue_ref}'")
|
||||
|
||||
if db_session is None or search_space_id is None or user_id is None:
|
||||
if search_space_id is None or user_id is None:
|
||||
logger.error(
|
||||
"Linear tool not properly configured - missing required parameters"
|
||||
)
|
||||
|
|
@ -96,176 +104,177 @@ def create_update_linear_issue_tool(
|
|||
}
|
||||
|
||||
try:
|
||||
metadata_service = LinearToolMetadataService(db_session)
|
||||
context = await metadata_service.get_update_context(
|
||||
search_space_id, user_id, issue_ref
|
||||
)
|
||||
|
||||
if "error" in context:
|
||||
error_msg = context["error"]
|
||||
if context.get("auth_expired"):
|
||||
logger.warning(f"Auth expired for update context: {error_msg}")
|
||||
return {
|
||||
"status": "auth_error",
|
||||
"message": error_msg,
|
||||
"connector_id": context.get("connector_id"),
|
||||
"connector_type": "linear",
|
||||
}
|
||||
if "not found" in error_msg.lower():
|
||||
logger.warning(f"Issue not found: {error_msg}")
|
||||
return {"status": "not_found", "message": error_msg}
|
||||
else:
|
||||
logger.error(f"Failed to fetch update context: {error_msg}")
|
||||
return {"status": "error", "message": error_msg}
|
||||
|
||||
issue_id = context["issue"]["id"]
|
||||
document_id = context["issue"]["document_id"]
|
||||
connector_id_from_context = context.get("workspace", {}).get("id")
|
||||
|
||||
team = context.get("team", {})
|
||||
new_state_id = _resolve_state(team, new_state_name)
|
||||
new_assignee_id = _resolve_assignee(team, new_assignee_email)
|
||||
new_label_ids = _resolve_labels(team, new_label_names)
|
||||
|
||||
logger.info(
|
||||
f"Requesting approval for updating Linear issue: '{issue_ref}' (id={issue_id})"
|
||||
)
|
||||
result = request_approval(
|
||||
action_type="linear_issue_update",
|
||||
tool_name="update_linear_issue",
|
||||
params={
|
||||
"issue_id": issue_id,
|
||||
"document_id": document_id,
|
||||
"new_title": new_title,
|
||||
"new_description": new_description,
|
||||
"new_state_id": new_state_id,
|
||||
"new_assignee_id": new_assignee_id,
|
||||
"new_priority": new_priority,
|
||||
"new_label_ids": new_label_ids,
|
||||
"connector_id": connector_id_from_context,
|
||||
},
|
||||
context=context,
|
||||
)
|
||||
|
||||
if result.rejected:
|
||||
logger.info("Linear issue update rejected by user")
|
||||
return {
|
||||
"status": "rejected",
|
||||
"message": "User declined. Do not retry or suggest alternatives.",
|
||||
}
|
||||
|
||||
final_issue_id = result.params.get("issue_id", issue_id)
|
||||
final_document_id = result.params.get("document_id", document_id)
|
||||
final_new_title = result.params.get("new_title", new_title)
|
||||
final_new_description = result.params.get(
|
||||
"new_description", new_description
|
||||
)
|
||||
final_new_state_id = result.params.get("new_state_id", new_state_id)
|
||||
final_new_assignee_id = result.params.get(
|
||||
"new_assignee_id", new_assignee_id
|
||||
)
|
||||
final_new_priority = result.params.get("new_priority", new_priority)
|
||||
final_new_label_ids: list[str] | None = result.params.get(
|
||||
"new_label_ids", new_label_ids
|
||||
)
|
||||
final_connector_id = result.params.get(
|
||||
"connector_id", connector_id_from_context
|
||||
)
|
||||
|
||||
if not final_connector_id:
|
||||
logger.error("No connector found for this issue")
|
||||
return {
|
||||
"status": "error",
|
||||
"message": "No connector found for this issue.",
|
||||
}
|
||||
|
||||
from sqlalchemy.future import select
|
||||
|
||||
from app.db import SearchSourceConnector, SearchSourceConnectorType
|
||||
|
||||
result = await db_session.execute(
|
||||
select(SearchSourceConnector).filter(
|
||||
SearchSourceConnector.id == final_connector_id,
|
||||
SearchSourceConnector.search_space_id == search_space_id,
|
||||
SearchSourceConnector.user_id == user_id,
|
||||
SearchSourceConnector.connector_type
|
||||
== SearchSourceConnectorType.LINEAR_CONNECTOR,
|
||||
async with async_session_maker() as db_session:
|
||||
metadata_service = LinearToolMetadataService(db_session)
|
||||
context = await metadata_service.get_update_context(
|
||||
search_space_id, user_id, issue_ref
|
||||
)
|
||||
)
|
||||
connector = result.scalars().first()
|
||||
if not connector:
|
||||
logger.error(
|
||||
f"Invalid connector_id={final_connector_id} for search_space_id={search_space_id}"
|
||||
)
|
||||
return {
|
||||
"status": "error",
|
||||
"message": "Selected Linear connector is invalid or has been disconnected.",
|
||||
}
|
||||
logger.info(f"Validated Linear connector: id={final_connector_id}")
|
||||
|
||||
logger.info(
|
||||
f"Updating Linear issue with final params: issue_id={final_issue_id}"
|
||||
)
|
||||
linear_client = LinearConnector(
|
||||
session=db_session, connector_id=final_connector_id
|
||||
)
|
||||
updated_issue = await linear_client.update_issue(
|
||||
issue_id=final_issue_id,
|
||||
title=final_new_title,
|
||||
description=final_new_description,
|
||||
state_id=final_new_state_id,
|
||||
assignee_id=final_new_assignee_id,
|
||||
priority=final_new_priority,
|
||||
label_ids=final_new_label_ids,
|
||||
)
|
||||
if "error" in context:
|
||||
error_msg = context["error"]
|
||||
if context.get("auth_expired"):
|
||||
logger.warning(f"Auth expired for update context: {error_msg}")
|
||||
return {
|
||||
"status": "auth_error",
|
||||
"message": error_msg,
|
||||
"connector_id": context.get("connector_id"),
|
||||
"connector_type": "linear",
|
||||
}
|
||||
if "not found" in error_msg.lower():
|
||||
logger.warning(f"Issue not found: {error_msg}")
|
||||
return {"status": "not_found", "message": error_msg}
|
||||
else:
|
||||
logger.error(f"Failed to fetch update context: {error_msg}")
|
||||
return {"status": "error", "message": error_msg}
|
||||
|
||||
if updated_issue.get("status") == "error":
|
||||
logger.error(
|
||||
f"Failed to update Linear issue: {updated_issue.get('message')}"
|
||||
)
|
||||
return {
|
||||
"status": "error",
|
||||
"message": updated_issue.get("message"),
|
||||
}
|
||||
issue_id = context["issue"]["id"]
|
||||
document_id = context["issue"]["document_id"]
|
||||
connector_id_from_context = context.get("workspace", {}).get("id")
|
||||
|
||||
logger.info(
|
||||
f"update_issue result: {updated_issue.get('identifier')} - {updated_issue.get('title')}"
|
||||
)
|
||||
team = context.get("team", {})
|
||||
new_state_id = _resolve_state(team, new_state_name)
|
||||
new_assignee_id = _resolve_assignee(team, new_assignee_email)
|
||||
new_label_ids = _resolve_labels(team, new_label_names)
|
||||
|
||||
if final_document_id is not None:
|
||||
logger.info(
|
||||
f"Updating knowledge base for document {final_document_id}..."
|
||||
f"Requesting approval for updating Linear issue: '{issue_ref}' (id={issue_id})"
|
||||
)
|
||||
kb_service = LinearKBSyncService(db_session)
|
||||
kb_result = await kb_service.sync_after_update(
|
||||
document_id=final_document_id,
|
||||
issue_id=final_issue_id,
|
||||
user_id=user_id,
|
||||
search_space_id=search_space_id,
|
||||
result = request_approval(
|
||||
action_type="linear_issue_update",
|
||||
tool_name="update_linear_issue",
|
||||
params={
|
||||
"issue_id": issue_id,
|
||||
"document_id": document_id,
|
||||
"new_title": new_title,
|
||||
"new_description": new_description,
|
||||
"new_state_id": new_state_id,
|
||||
"new_assignee_id": new_assignee_id,
|
||||
"new_priority": new_priority,
|
||||
"new_label_ids": new_label_ids,
|
||||
"connector_id": connector_id_from_context,
|
||||
},
|
||||
context=context,
|
||||
)
|
||||
if kb_result["status"] == "success":
|
||||
logger.info(
|
||||
f"Knowledge base successfully updated for issue {final_issue_id}"
|
||||
)
|
||||
kb_message = " Your knowledge base has also been updated."
|
||||
elif kb_result["status"] == "not_indexed":
|
||||
kb_message = " This issue will be added to your knowledge base in the next scheduled sync."
|
||||
else:
|
||||
logger.warning(
|
||||
f"KB update failed for issue {final_issue_id}: {kb_result.get('message')}"
|
||||
)
|
||||
kb_message = " Your knowledge base will be updated in the next scheduled sync."
|
||||
else:
|
||||
kb_message = ""
|
||||
|
||||
identifier = updated_issue.get("identifier")
|
||||
default_msg = f"Issue {identifier} updated successfully."
|
||||
return {
|
||||
"status": "success",
|
||||
"identifier": identifier,
|
||||
"url": updated_issue.get("url"),
|
||||
"message": f"{updated_issue.get('message', default_msg)}{kb_message}",
|
||||
}
|
||||
if result.rejected:
|
||||
logger.info("Linear issue update rejected by user")
|
||||
return {
|
||||
"status": "rejected",
|
||||
"message": "User declined. Do not retry or suggest alternatives.",
|
||||
}
|
||||
|
||||
final_issue_id = result.params.get("issue_id", issue_id)
|
||||
final_document_id = result.params.get("document_id", document_id)
|
||||
final_new_title = result.params.get("new_title", new_title)
|
||||
final_new_description = result.params.get(
|
||||
"new_description", new_description
|
||||
)
|
||||
final_new_state_id = result.params.get("new_state_id", new_state_id)
|
||||
final_new_assignee_id = result.params.get(
|
||||
"new_assignee_id", new_assignee_id
|
||||
)
|
||||
final_new_priority = result.params.get("new_priority", new_priority)
|
||||
final_new_label_ids: list[str] | None = result.params.get(
|
||||
"new_label_ids", new_label_ids
|
||||
)
|
||||
final_connector_id = result.params.get(
|
||||
"connector_id", connector_id_from_context
|
||||
)
|
||||
|
||||
if not final_connector_id:
|
||||
logger.error("No connector found for this issue")
|
||||
return {
|
||||
"status": "error",
|
||||
"message": "No connector found for this issue.",
|
||||
}
|
||||
|
||||
from sqlalchemy.future import select
|
||||
|
||||
from app.db import SearchSourceConnector, SearchSourceConnectorType
|
||||
|
||||
result = await db_session.execute(
|
||||
select(SearchSourceConnector).filter(
|
||||
SearchSourceConnector.id == final_connector_id,
|
||||
SearchSourceConnector.search_space_id == search_space_id,
|
||||
SearchSourceConnector.user_id == user_id,
|
||||
SearchSourceConnector.connector_type
|
||||
== SearchSourceConnectorType.LINEAR_CONNECTOR,
|
||||
)
|
||||
)
|
||||
connector = result.scalars().first()
|
||||
if not connector:
|
||||
logger.error(
|
||||
f"Invalid connector_id={final_connector_id} for search_space_id={search_space_id}"
|
||||
)
|
||||
return {
|
||||
"status": "error",
|
||||
"message": "Selected Linear connector is invalid or has been disconnected.",
|
||||
}
|
||||
logger.info(f"Validated Linear connector: id={final_connector_id}")
|
||||
|
||||
logger.info(
|
||||
f"Updating Linear issue with final params: issue_id={final_issue_id}"
|
||||
)
|
||||
linear_client = LinearConnector(
|
||||
session=db_session, connector_id=final_connector_id
|
||||
)
|
||||
updated_issue = await linear_client.update_issue(
|
||||
issue_id=final_issue_id,
|
||||
title=final_new_title,
|
||||
description=final_new_description,
|
||||
state_id=final_new_state_id,
|
||||
assignee_id=final_new_assignee_id,
|
||||
priority=final_new_priority,
|
||||
label_ids=final_new_label_ids,
|
||||
)
|
||||
|
||||
if updated_issue.get("status") == "error":
|
||||
logger.error(
|
||||
f"Failed to update Linear issue: {updated_issue.get('message')}"
|
||||
)
|
||||
return {
|
||||
"status": "error",
|
||||
"message": updated_issue.get("message"),
|
||||
}
|
||||
|
||||
logger.info(
|
||||
f"update_issue result: {updated_issue.get('identifier')} - {updated_issue.get('title')}"
|
||||
)
|
||||
|
||||
if final_document_id is not None:
|
||||
logger.info(
|
||||
f"Updating knowledge base for document {final_document_id}..."
|
||||
)
|
||||
kb_service = LinearKBSyncService(db_session)
|
||||
kb_result = await kb_service.sync_after_update(
|
||||
document_id=final_document_id,
|
||||
issue_id=final_issue_id,
|
||||
user_id=user_id,
|
||||
search_space_id=search_space_id,
|
||||
)
|
||||
if kb_result["status"] == "success":
|
||||
logger.info(
|
||||
f"Knowledge base successfully updated for issue {final_issue_id}"
|
||||
)
|
||||
kb_message = " Your knowledge base has also been updated."
|
||||
elif kb_result["status"] == "not_indexed":
|
||||
kb_message = " This issue will be added to your knowledge base in the next scheduled sync."
|
||||
else:
|
||||
logger.warning(
|
||||
f"KB update failed for issue {final_issue_id}: {kb_result.get('message')}"
|
||||
)
|
||||
kb_message = " Your knowledge base will be updated in the next scheduled sync."
|
||||
else:
|
||||
kb_message = ""
|
||||
|
||||
identifier = updated_issue.get("identifier")
|
||||
default_msg = f"Issue {identifier} updated successfully."
|
||||
return {
|
||||
"status": "success",
|
||||
"identifier": identifier,
|
||||
"url": updated_issue.get("url"),
|
||||
"message": f"{updated_issue.get('message', default_msg)}{kb_message}",
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
from langgraph.errors import GraphInterrupt
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue