Files
api/app/agents/task_agent.py
roberto 8bfce9da00 Refactor LLM instantiation across agents and orchestrator
- Replaced direct instantiation of ChatOpenAI with a centralized get_llm function in CheckpointAgent, NoteAgent, ProjectAgent, and TaskAgent.
- Introduced a new llm.py module to handle LLM model instantiation and API key management.
- Updated settings.py to include LLM_MODEL and LLM_ROUTER_MODEL configurations.
- Modified orchestrator.py to use get_router_llm for intent classification.
- Updated requirements.txt to include litellm for LLM management.
- Adjusted tests to mock get_llm instead of ChatOpenAI directly.
2026-03-03 15:46:44 +01:00

229 lines
7.0 KiB
Python

"""Task agent — full CRUD for tasks and task comments."""
from __future__ import annotations
import json
from typing import Any
from langchain_core.messages import HumanMessage, SystemMessage
from langchain_core.tools import tool
from app.core.agent_registry import ChatAgent, registry
from app.core.llm import get_llm
_SYSTEM_PROMPT = (
"You are a task management assistant for a project workspace.\n"
"You create, update, list, and track tasks and their comments.\n\n"
"Rules:\n"
" - status must be one of: todo, in_progress, done\n"
" - priority must be one of: high, medium, low\n"
" - due_date is a Unix timestamp in milliseconds; convert human dates\n"
" - assignees is a JSON-encoded array of strings (e.g. '[\"Alice\",\"Bob\"]')\n"
" - project_id is optional; link to a project when the user mentions one\n"
" - is_ai_suggested: 1 only when proactively proposing a task the user\n"
" did not explicitly request; 0 otherwise\n"
" - is_approved defaults to 0; set to 1 only when the user confirms\n"
" - Use list_tasks_due_today for 'what's due today' queries\n"
" - For update_task, use -1 for integer fields you do not want to change\n"
" - Always confirm the action in plain, user-friendly language."
)
# ── Task tools ────────────────────────────────────────────────────────
@tool
async def list_tasks(
project_id: str = "",
status: str = "",
search: str = "",
order_by: str = "",
) -> str:
"""List tasks, optionally filtered by project_id, status (todo|in_progress|done),
a search string, or an order_by field name (dueDate|priority|createdAt)."""
return json.dumps({
"action": "list",
"table": "tasks",
"filters": {
"projectId": project_id or None,
"status": status or None,
"search": search or None,
"orderBy": order_by or None,
},
})
@tool
async def create_task(
title: str,
description: str = "",
status: str = "todo",
priority: str = "medium",
assignees: str = "[]",
due_date: int = 0,
project_id: str = "",
is_ai_suggested: int = 0,
is_approved: int = 0,
) -> str:
"""Create a new task.
title: task title (required)
description: optional details
status: todo | in_progress | done (default: todo)
priority: high | medium | low (default: medium)
assignees: JSON-encoded array of assignee names, e.g. '["Alice"]'
due_date: Unix timestamp in milliseconds; 0 means no due date
project_id: optional UUID of the parent project
is_ai_suggested: 1 if proactively suggested, 0 if user-requested
is_approved: 0 until the user confirms; 1 when confirmed
"""
return json.dumps({
"action": "create_record",
"table": "tasks",
"data": {
"title": title,
"description": description or None,
"status": status,
"priority": priority,
"assignee": assignees,
"dueDate": due_date or None,
"projectId": project_id or None,
"isAiSuggested": is_ai_suggested,
"isApproved": is_approved,
},
})
@tool
async def update_task(
task_id: str,
title: str = "",
description: str = "",
status: str = "",
priority: str = "",
assignees: str = "",
due_date: int = -1,
project_id: str = "",
is_approved: int = -1,
) -> str:
"""Update fields on an existing task. Only pass fields you want to change.
task_id: the task's UUID (required)
due_date: -1 means unchanged; 0 clears the due date; any positive value sets it
is_approved: -1 means unchanged; 0 or 1 sets the value
"""
updates: dict[str, Any] = {}
if title:
updates["title"] = title
if description:
updates["description"] = description
if status:
updates["status"] = status
if priority:
updates["priority"] = priority
if assignees:
updates["assignee"] = assignees
if due_date != -1:
updates["dueDate"] = due_date or None
if project_id:
updates["projectId"] = project_id
if is_approved != -1:
updates["isApproved"] = is_approved
return json.dumps({
"action": "update_record",
"table": "tasks",
"data": {"id": task_id, "updates": updates},
})
@tool
async def delete_task(task_id: str) -> str:
"""Delete a task permanently by its UUID."""
return json.dumps({
"action": "delete_record",
"table": "tasks",
"data": {"id": task_id},
})
@tool
async def list_tasks_due_today() -> str:
"""List all tasks whose due date falls on today's date."""
return json.dumps({
"action": "list_due_today",
"table": "tasks",
})
# ── Task comment tools ────────────────────────────────────────────────
@tool
async def list_task_comments(task_id: str) -> str:
"""List all comments on a task by its UUID."""
return json.dumps({
"action": "list",
"table": "taskComments",
"filters": {"taskId": task_id},
})
@tool
async def add_task_comment(task_id: str, author: str, content: str) -> str:
"""Add a comment to a task.
task_id: UUID of the task to comment on
author: name or ID of the comment author
content: comment text
"""
return json.dumps({
"action": "create_record",
"table": "taskComments",
"data": {
"taskId": task_id,
"author": author,
"content": content,
},
})
@tool
async def delete_task_comment(comment_id: str) -> str:
"""Delete a task comment by its UUID."""
return json.dumps({
"action": "delete_record",
"table": "taskComments",
"data": {"id": comment_id},
})
# ── Agent ─────────────────────────────────────────────────────────────
@registry.register
class TaskAgent(ChatAgent):
def get_name(self) -> str:
return "task_agent"
def get_description(self) -> str:
return "Manages tasks and comments: list, create, update, delete, due-today, comments"
def get_tools(self) -> list[Any]:
return [
list_tasks,
create_task,
update_task,
delete_task,
list_tasks_due_today,
list_task_comments,
add_task_comment,
delete_task_comment,
]
async def handle(self, query: str, context: dict[str, Any]) -> str:
llm = get_llm()
messages = [
SystemMessage(content=_SYSTEM_PROMPT),
HumanMessage(
content=f"User query: {query}\nContext: {json.dumps(context)[:1000]}"
),
]
return await self._tool_loop(llm, messages, self.get_tools())