af53111928
Address all architecture review findings: P0 fixes: - Add API key authentication for admin endpoints (analytics, replay, openapi) and WebSocket connections via ADMIN_API_KEY env var - Add PostgreSQL-backed PgSessionManager and PgInterruptManager for multi-worker production deployments (in-memory defaults preserved) P1 fixes: - Implement actual tool generation in OpenAPI approve_job endpoint using generate_tool_code() and generate_agent_yaml() - Add missing clarification, interrupt_expired, and tool_result message handlers in frontend ChatPage P2 fixes: - Replace monkey-patching on CompiledStateGraph with typed GraphContext - Replace 9-param dispatch_message with WebSocketContext dataclass - Extract duplicate _envelope() into shared app/api_utils.py - Replace mutable module-level counter with crypto.randomUUID() - Remove hardcoded mock data from ReviewPage, use api.ts wrappers - Remove `as any` type escape from ReplayPage All 516 tests passing, 0 TypeScript errors.
283 lines
8.4 KiB
Python
283 lines
8.4 KiB
Python
"""FastAPI router for OpenAPI import review workflow.
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Exposes endpoints for:
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- Starting an import job (triggers background pipeline)
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- Querying job status
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- Reviewing and editing classifications
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- Approving a job to trigger tool generation
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"""
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from __future__ import annotations
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import asyncio
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import logging
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import re
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import uuid
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from typing import Literal
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from fastapi import APIRouter, BackgroundTasks, Depends, HTTPException
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from pydantic import BaseModel, field_validator
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from app.auth import require_admin_api_key
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from app.openapi.generator import generate_agent_yaml, generate_tool_code
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from app.openapi.importer import ImportOrchestrator
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from app.openapi.models import ClassificationResult, ImportJob
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logger = logging.getLogger(__name__)
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router = APIRouter(
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prefix="/api/openapi",
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tags=["openapi"],
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dependencies=[Depends(require_admin_api_key)],
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)
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# In-memory store: job_id -> job dict, guarded by async lock
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_job_store: dict[str, dict] = {}
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_store_lock = asyncio.Lock()
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# Shared orchestrator instance
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_orchestrator = ImportOrchestrator()
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# --- Request / Response schemas ---
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class ImportRequest(BaseModel):
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url: str
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@field_validator("url")
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@classmethod
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def url_must_be_valid(cls, value: str) -> str:
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stripped = value.strip()
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if not stripped:
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raise ValueError("url must not be empty")
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if not stripped.startswith(("http://", "https://")):
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raise ValueError("url must start with http:// or https://")
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return stripped
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class JobResponse(BaseModel):
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job_id: str
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status: str
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spec_url: str
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total_endpoints: int = 0
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classified_count: int = 0
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error_message: str | None = None
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class ClassificationResponse(BaseModel):
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index: int
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access_type: str
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needs_interrupt: bool
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agent_group: str
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confidence: float
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customer_params: list[str]
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endpoint: dict
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class UpdateClassificationRequest(BaseModel):
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access_type: Literal["read", "write"]
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needs_interrupt: bool
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agent_group: str
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@field_validator("agent_group")
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@classmethod
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def agent_group_must_be_safe(cls, value: str) -> str:
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if not value.strip() or not re.fullmatch(r"[a-zA-Z0-9_\-]+", value):
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raise ValueError(
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"agent_group must be non-empty and contain only "
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"alphanumeric characters, underscores, or hyphens"
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)
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return value
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# --- Helpers ---
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def _job_to_response(job: dict) -> dict:
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return {
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"job_id": job["job_id"],
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"status": job["status"],
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"spec_url": job["spec_url"],
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"total_endpoints": job.get("total_endpoints", 0),
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"classified_count": job.get("classified_count", 0),
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"error_message": job.get("error_message"),
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}
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def _classification_to_response(idx: int, clf: ClassificationResult) -> dict:
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ep = clf.endpoint
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return {
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"index": idx,
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"access_type": clf.access_type,
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"needs_interrupt": clf.needs_interrupt,
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"agent_group": clf.agent_group,
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"confidence": clf.confidence,
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"customer_params": list(clf.customer_params),
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"endpoint": {
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"path": ep.path,
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"method": ep.method,
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"operation_id": ep.operation_id,
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"summary": ep.summary,
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"description": ep.description,
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},
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}
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async def _run_import(job_id: str, url: str) -> None:
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"""Run the import pipeline as a background task."""
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def on_progress(stage: str, result_job: ImportJob) -> None:
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if job_id in _job_store:
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_job_store[job_id] = {
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**_job_store[job_id],
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"status": result_job.status,
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"total_endpoints": result_job.total_endpoints,
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"classified_count": result_job.classified_count,
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"error_message": result_job.error_message,
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}
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try:
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result = await _orchestrator.start_import(
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url=url, job_id=job_id, on_progress=on_progress,
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)
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if job_id in _job_store:
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_job_store[job_id] = {
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**_job_store[job_id],
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"status": result.status,
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"total_endpoints": result.total_endpoints,
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"classified_count": result.classified_count,
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"error_message": result.error_message,
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}
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except Exception:
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logger.exception("Background import failed for job %s", job_id)
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if job_id in _job_store:
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_job_store[job_id] = {
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**_job_store[job_id],
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"status": "failed",
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"error_message": "Import failed. Please check the URL and try again.",
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}
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# --- Endpoints ---
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@router.post("/import", status_code=202)
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async def start_import(
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request: ImportRequest,
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background_tasks: BackgroundTasks,
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) -> dict:
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"""Start an OpenAPI import job for the given spec URL."""
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job_id = str(uuid.uuid4())
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job: dict = {
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"job_id": job_id,
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"status": "pending",
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"spec_url": request.url,
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"total_endpoints": 0,
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"classified_count": 0,
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"error_message": None,
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"classifications": [],
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}
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_job_store[job_id] = job
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background_tasks.add_task(_run_import, job_id, request.url)
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return _job_to_response(job)
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@router.get("/jobs/{job_id}")
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async def get_job(job_id: str) -> dict:
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"""Get the status of an import job."""
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job = _job_store.get(job_id)
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if job is None:
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raise HTTPException(status_code=404, detail=f"Job '{job_id}' not found")
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return _job_to_response(job)
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@router.get("/jobs/{job_id}/classifications")
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async def get_classifications(job_id: str) -> list:
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"""Get all classifications for an import job."""
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job = _job_store.get(job_id)
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if job is None:
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raise HTTPException(status_code=404, detail=f"Job '{job_id}' not found")
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classifications: list[ClassificationResult] = job.get("classifications", [])
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return [
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_classification_to_response(i, clf)
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for i, clf in enumerate(classifications)
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]
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@router.put("/jobs/{job_id}/classifications/{idx}")
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async def update_classification(
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job_id: str,
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idx: int,
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request: UpdateClassificationRequest,
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) -> dict:
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"""Update a specific classification by index."""
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job = _job_store.get(job_id)
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if job is None:
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raise HTTPException(status_code=404, detail=f"Job '{job_id}' not found")
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classifications: list[ClassificationResult] = job.get("classifications", [])
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if idx < 0 or idx >= len(classifications):
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raise HTTPException(
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status_code=404,
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detail=f"Classification index {idx} out of range",
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)
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original = classifications[idx]
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updated = ClassificationResult(
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endpoint=original.endpoint,
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access_type=request.access_type,
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customer_params=original.customer_params,
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agent_group=request.agent_group,
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confidence=original.confidence,
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needs_interrupt=request.needs_interrupt,
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)
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new_classifications = list(classifications)
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new_classifications[idx] = updated
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_job_store[job_id] = {**job, "classifications": new_classifications}
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return _classification_to_response(idx, updated)
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@router.post("/jobs/{job_id}/approve")
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async def approve_job(job_id: str) -> dict:
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"""Approve a job's classifications and trigger tool generation.
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Generates Python tool code for each classified endpoint and
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produces an agent YAML configuration snippet.
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"""
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job = _job_store.get(job_id)
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if job is None:
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raise HTTPException(status_code=404, detail=f"Job '{job_id}' not found")
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classifications: list[ClassificationResult] = job.get("classifications", [])
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if not classifications:
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raise HTTPException(
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status_code=400,
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detail="No classifications to approve. Import must complete first.",
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)
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base_url = job["spec_url"].rsplit("/", 1)[0]
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generated_tools = []
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for clf in classifications:
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tool = generate_tool_code(clf, base_url)
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generated_tools.append({
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"function_name": tool.function_name,
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"agent_group": clf.agent_group,
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"code": tool.code,
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})
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agent_yaml = generate_agent_yaml(tuple(classifications), base_url)
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updated_job = {
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**job,
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"status": "approved",
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"generated_tools": generated_tools,
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"agent_yaml": agent_yaml,
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}
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_job_store[job_id] = updated_job
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response = _job_to_response(updated_job)
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response["generated_tools_count"] = len(generated_tools)
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return response
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