mirror of
https://github.com/MODSetter/SurfSense.git
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97 lines
3.4 KiB
Python
97 lines
3.4 KiB
Python
"""Run one ``agent_task`` invocation: ainvoke + auto-decision resume loop."""
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from __future__ import annotations
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import time
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import uuid
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from typing import Any
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from langchain_core.messages import HumanMessage
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from langgraph.types import Command
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from app.agents.multi_agent_chat import create_multi_agent_chat_deep_agent
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from app.automations.registries.actions.types import ActionContext
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from app.db import ChatVisibility, async_session_maker
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from .auto_decide import build_auto_decisions
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from .dependencies import build_dependencies
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from .finalize import extract_final_assistant_message
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# Cap on HITL resume iterations. The agent should not need this many turns in one
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# step; treat overshoot as a runaway and fail the step.
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_MAX_RESUMES = 50
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async def run_agent_task(
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*,
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ctx: ActionContext,
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query: str,
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auto_approve_all: bool,
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) -> dict[str, Any]:
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"""Invoke multi_agent_chat for one rendered query and return its outcome.
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Opens its own DB session so the executor's bookkeeping session isn't tied
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up for the entire invocation. The LangGraph ``thread_id`` (a fresh UUID)
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is returned as ``agent_session_id`` for later inspection.
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"""
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agent_session_id = str(uuid.uuid4())
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user_id = str(ctx.creator_user_id) if ctx.creator_user_id else None
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decision = "approve" if auto_approve_all else "reject"
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async with async_session_maker() as agent_session:
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deps = await build_dependencies(
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session=agent_session,
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search_space_id=ctx.search_space_id,
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)
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agent = await create_multi_agent_chat_deep_agent(
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llm=deps.llm,
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search_space_id=ctx.search_space_id,
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db_session=agent_session,
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connector_service=deps.connector_service,
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checkpointer=deps.checkpointer,
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user_id=user_id,
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thread_id=None,
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agent_config=deps.agent_config,
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firecrawl_api_key=deps.firecrawl_api_key,
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thread_visibility=ChatVisibility.PRIVATE,
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)
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request_id = f"automation:{ctx.run_id}:{ctx.step_id}"
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turn_id = f"{request_id}:{int(time.time() * 1000)}"
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input_state: dict[str, Any] = {
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"messages": [HumanMessage(content=query)],
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"search_space_id": ctx.search_space_id,
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"request_id": request_id,
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"turn_id": turn_id,
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}
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config: dict[str, Any] = {
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"configurable": {
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"thread_id": agent_session_id,
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"request_id": request_id,
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"turn_id": turn_id,
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},
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"recursion_limit": 10_000,
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}
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result = await agent.ainvoke(input_state, config=config)
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resumes = 0
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while True:
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state = await agent.aget_state(config)
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if not getattr(state, "interrupts", None):
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break
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if resumes >= _MAX_RESUMES:
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raise RuntimeError(
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f"agent_task exceeded {_MAX_RESUMES} HITL resume iterations"
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)
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lg_resume_map, routed = build_auto_decisions(state, decision)
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config["configurable"]["surfsense_resume_value"] = routed
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result = await agent.ainvoke(Command(resume=lg_resume_map), config=config)
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resumes += 1
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return {
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"agent_session_id": agent_session_id,
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"final_message": extract_final_assistant_message(result),
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"resumes": resumes,
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}
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