AgentEvalTool/backend/agenteval/web/routers/runs.py
sinohqb 739d586aec feat(backend): v0.4 triggered_by tracking, login gate, compare guard, dashboard stats
- EvalRun.triggered_by 全链路(manual/ai_assistant/cli)+ 迁移 b7d4e6f81c22
- 标准 agenteval-run SKILL.md 纳入版本管理,deploy 脚本同步 + API Key 注入
- 简单登录:AGENTEVAL_ADMIN_PASSWORD + HMAC 会话 token,require_auth 双凭据
- 对比报告限同场景(400)+ 空 results 误判修复
- /api/stats/dashboard 扩展聚合;/api/runs 返回场景/对象名
- 测试 218 → 232
2026-07-28 17:40:54 +08:00

204 lines
7.3 KiB
Python

"""API routes for evaluation runs."""
import asyncio
from typing import Optional
from fastapi import APIRouter, Depends, HTTPException
from pydantic import BaseModel
from sqlmodel import Session
from agenteval.evaluation.engine import EvalEngine
from agenteval.models import EvalRun, RunStatus, RunTrigger
from agenteval.storage.db import get_session, iso_utc
from agenteval.storage.repository import RunRepository, ScenarioRepository, TargetRepository
from agenteval.utils.llm import extract_reply_text
from agenteval.utils.webhook import send_run_webhook
from agenteval.web.deps import get_db
from agenteval.web.websocket import ws_manager
router = APIRouter()
class StartRunRequest(BaseModel):
target_id: str
scenario_id: str
triggered_by: RunTrigger = RunTrigger.MANUAL
# ── Task registry for live evaluation runs ─────────────────────────────
# Each running evaluation is an asyncio.Task keyed by run_id. The cancel
# token is a cooperative ``asyncio.Event`` the engine checks between cases.
_tasks: dict[str, asyncio.Task] = {}
_cancel_tokens: dict[str, asyncio.Event] = {}
async def _run_evaluation(run_id: str, target_id: str, scenario_id: str) -> None:
"""Background coroutine that drives one evaluation run to completion."""
session = get_session()
cancel_token = asyncio.Event()
_cancel_tokens[run_id] = cancel_token
try:
target = TargetRepository(session).get(target_id)
scenario = ScenarioRepository(session).get(scenario_id)
existing_run = RunRepository(session).get(run_id)
if not target or not scenario:
return
engine = EvalEngine(
target=target,
scenario=scenario,
session=session,
cancel_token=cancel_token,
)
await engine.run(
progress_callback=lambda event, data: ws_manager.emit(run_id, event, data),
existing_run=existing_run,
)
# Fire webhook after run completes (non-blocking, best-effort)
completed_run = RunRepository(session).get(run_id)
if completed_run:
await send_run_webhook(
run_id=run_id,
status=completed_run.status.value,
summary=completed_run.summary or {},
)
finally:
session.close()
_cancel_tokens.pop(run_id, None)
_tasks.pop(run_id, None)
@router.get("")
async def list_runs(session: Session = Depends(get_db)) -> list[dict]:
scenario_names = {s.id: s.name for s in ScenarioRepository(session).list_all()}
target_names = {t.id: t.name for t in TargetRepository(session).list_all()}
return [
{
**r.model_dump(),
"scenario_name": scenario_names.get(r.scenario_id),
"target_name": target_names.get(r.target_id),
}
for r in RunRepository(session).list_all()
]
@router.post("")
async def start_run(
request: StartRunRequest,
session: Session = Depends(get_db),
) -> dict:
target = TargetRepository(session).get(request.target_id)
scenario = ScenarioRepository(session).get(request.scenario_id)
if not target or not scenario:
raise HTTPException(status_code=404, detail="target or scenario not found")
run = EvalRun(
target_id=request.target_id,
scenario_id=request.scenario_id,
triggered_by=request.triggered_by,
)
run = RunRepository(session).create(run)
task = asyncio.create_task(
_run_evaluation(run.id, request.target_id, request.scenario_id),
name=f"eval-run-{run.id}",
)
_tasks[run.id] = task
return run.model_dump()
@router.get("/{run_id}")
async def get_run(run_id: str, session: Session = Depends(get_db)) -> dict:
run = RunRepository(session).get(run_id)
if not run:
raise HTTPException(status_code=404, detail="run not found")
return run.model_dump()
@router.post("/{run_id}/cancel")
async def cancel_run(run_id: str, session: Session = Depends(get_db)) -> dict:
repo = RunRepository(session)
run = repo.get(run_id)
if not run:
raise HTTPException(status_code=404, detail="run not found")
if run.status not in (RunStatus.PENDING, RunStatus.RUNNING):
raise HTTPException(status_code=400, detail="run is not in a cancellable state")
cancel_token = _cancel_tokens.get(run_id)
task: Optional[asyncio.Task] = _tasks.get(run_id)
if cancel_token is not None:
# Cooperative cancel: the engine will catch CancelledError and mark
# the run as FAILED with code=cancelled_by_user.
cancel_token.set()
elif task is not None:
# Fallback: hard-cancel the task if no token exists (shouldn't happen).
task.cancel()
else:
# No live task (e.g. process restarted): mark the DB row directly.
run.status = RunStatus.FAILED
run.summary = {
"error": {"code": "cancelled_by_user", "message": "评测已手动停止"},
}
repo.update(run)
return run.model_dump()
@router.get("/{run_id}/logs")
async def get_run_logs(run_id: str, session: Session = Depends(get_db)) -> dict:
repo = RunRepository(session)
run = repo.get(run_id)
if not run:
raise HTTPException(status_code=404, detail="run not found")
turns = repo.get_turns(run_id)
results = repo.get_results(run_id)
turns_data = [
{
"id": t.id,
"case_id": t.case_id,
"round_index": t.round_index,
"latency_ms": t.latency_ms,
"sent_text": t.get_sent_message().get("msgBody", {}).get("content", ""),
"reply_text": extract_reply_text(t.get_reply()),
"sent_at": iso_utc(t.sent_at),
"received_at": iso_utc(t.received_at),
}
for t in turns
]
results_data = [
{
"case_id": r.case_id,
"rule_type": r.rule_type,
"passed": r.passed,
"score": r.score,
"reason": r.reason,
}
for r in results
]
scenario_snapshot: dict = {}
scenario = ScenarioRepository(session).get(run.scenario_id)
if scenario:
for case in scenario.cases:
scenario_snapshot[case.id] = {
"id": case.id,
"type": case.type.value if hasattr(case.type, "value") else str(case.type),
"messages": list(case.messages),
"prompt": case.prompt,
"turns": case.turns,
"expectations": {
"intent": case.expectations.intent,
"keywords_include": list(case.expectations.keywords_include),
"keywords_exclude": list(case.expectations.keywords_exclude),
"response_time_max_ms": case.expectations.response_time_max_ms,
"coherence_min_score": case.expectations.coherence_min_score,
},
"eval_rules": [{"type": r.type, "params": dict(r.params), "weight": r.weight} for r in case.eval_rules],
"rule_logic": case.rule_logic.value if hasattr(case.rule_logic, "value") else str(case.rule_logic),
"rule_pass_threshold": case.rule_pass_threshold,
}
return {"turns": turns_data, "results": results_data, "scenario_snapshot": scenario_snapshot}