Files
beaver_project/app-instance/backend/beaver/tasks/validation.py

155 lines
6.2 KiB
Python

"""Automatic validation for internal Task mode."""
from __future__ import annotations
import json
from typing import Any
from beaver.engine.providers import ProviderBundle
from .models import TaskRecord, ValidationResult
class ValidationService:
async def validate_task_result(
self,
*,
task: TaskRecord,
user_message: str,
final_output: str,
evidence_packet: Any | None = None,
evidence_text: str = "",
transcript_excerpt: str = "",
tool_summaries: list[str] | None = None,
team_summaries: list[str] | None = None,
provider_bundle: ProviderBundle | None = None,
) -> ValidationResult:
provider = None
model = None
if provider_bundle is not None:
provider = provider_bundle.auxiliary_provider or provider_bundle.main_provider
runtime = provider_bundle.auxiliary_runtime or provider_bundle.main_runtime
model = getattr(runtime, "model", None)
if provider is not None:
try:
return await self._validate_with_provider(
provider=provider,
model=model,
task=task,
user_message=user_message,
final_output=final_output,
evidence_text=evidence_text,
transcript_excerpt=transcript_excerpt,
tool_summaries=tool_summaries or [],
team_summaries=team_summaries or [],
)
except Exception as exc:
return ValidationResult(
status="validator_error",
score=0.0,
issues=[f"Validator failed: {exc}"],
evidence_gaps=["Automatic validation failed before producing a reliable decision."],
missing_requirements=["User review is required because automatic validation failed."],
recommended_revision_prompt=(
"Review the answer and evidence, then decide whether to revise or accept it."
),
validator="llm_error",
)
return self._heuristic_validate(final_output)
async def _validate_with_provider(
self,
*,
provider: Any,
model: str | None,
task: TaskRecord,
user_message: str,
final_output: str,
evidence_text: str,
transcript_excerpt: str,
tool_summaries: list[str],
team_summaries: list[str],
) -> ValidationResult:
legacy_context = "" if evidence_text else (
f"Transcript excerpt:\n{transcript_excerpt}\n\n"
f"Tool summaries:\n{json.dumps(tool_summaries, ensure_ascii=False)}\n\n"
f"Team summaries:\n{json.dumps(team_summaries, ensure_ascii=False)}\n\n"
)
prompt = (
"Validate whether the assistant output satisfies the task. "
"Return only compact JSON with keys: passed, score, issues, "
"missing_requirements, recommended_revision_prompt.\n\n"
f"Task goal:\n{task.goal}\n\n"
f"Current user request:\n{user_message}\n\n"
f"Evidence packet:\n{evidence_text}\n\n"
f"{legacy_context}"
f"Assistant final output:\n{final_output}"
)
response = await provider.chat(
messages=[
{"role": "system", "content": "You are a strict task result validator."},
{"role": "user", "content": prompt},
],
tools=None,
model=model,
max_tokens=4096,
temperature=0.0,
)
payload = self._parse_json_object(response.content or "")
status = payload.get("status")
if status not in {"accepted", "rejected", "insufficient_evidence", "validator_error"}:
status = (
"accepted"
if payload.get("passed") and float(payload.get("score", 0.0) or 0.0) >= 0.75
else "rejected"
)
return ValidationResult(
status=status,
score=max(0.0, min(1.0, float(payload.get("score", 0.0) or 0.0))),
issues=[str(item) for item in payload.get("issues") or []],
missing_requirements=[str(item) for item in payload.get("missing_requirements") or []],
evidence_gaps=[str(item) for item in payload.get("evidence_gaps") or []],
recommended_revision_prompt=str(payload.get("recommended_revision_prompt") or ""),
validator="llm",
)
@staticmethod
def _heuristic_validate(final_output: str) -> ValidationResult:
text = final_output.strip()
if not text:
return ValidationResult(
passed=False,
score=0.0,
issues=["Assistant output is empty."],
missing_requirements=["A non-empty result is required."],
recommended_revision_prompt="Produce a complete, non-empty answer for the task.",
validator="heuristic",
)
lowered = text.lower()
if "run failed before completion" in lowered or "tool loop stopped" in lowered:
return ValidationResult(
passed=False,
score=0.35,
issues=["The run did not complete cleanly."],
missing_requirements=["A successful final result is required."],
recommended_revision_prompt="Retry the task and address the failure before returning the final answer.",
validator="heuristic",
)
return ValidationResult(passed=True, score=0.85, validator="heuristic")
@staticmethod
def _parse_json_object(text: str) -> dict[str, Any]:
cleaned = text.strip()
if cleaned.startswith("```"):
cleaned = cleaned.strip("`")
if cleaned.lower().startswith("json"):
cleaned = cleaned[4:].strip()
start = cleaned.find("{")
end = cleaned.rfind("}")
if start >= 0 and end >= start:
cleaned = cleaned[start : end + 1]
payload = json.loads(cleaned)
if not isinstance(payload, dict):
raise ValueError("validator response must be a JSON object")
return payload