""" Job endpoints (enqueue + poll) for long-running LL​M extraction and raw crawl. Relies on the existing Redis task helpers in api.py """ from typing import Dict, Optional, Callable from fastapi import APIRouter, BackgroundTasks, Depends, Request from pydantic import BaseModel, HttpUrl from api import ( handle_llm_request, handle_crawl_job, handle_task_status, ) from schemas import WebhookConfig # ------------- dependency placeholders ------------- _redis = None # will be injected from server.py _config = None _token_dep: Callable = lambda: None # dummy until injected # public router router = APIRouter() # === init hook called by server.py ========================================= def init_job_router(redis, config, token_dep) -> APIRouter: """Inject shared singletons and return the router for mounting.""" global _redis, _config, _token_dep _redis, _config, _token_dep = redis, config, token_dep return router # ---------- payload models -------------------------------------------------- class LlmJobPayload(BaseModel): url: HttpUrl q: str schema: Optional[str] = None cache: bool = False provider: Optional[str] = None webhook_config: Optional[WebhookConfig] = None temperature: Optional[float] = None base_url: Optional[str] = None class CrawlJobPayload(BaseModel): urls: list[HttpUrl] browser_config: Dict = {} crawler_config: Dict = {} webhook_config: Optional[WebhookConfig] = None # ---------- LL​M job --------------------------------------------------------- @router.post("/llm/job", status_code=202) async def llm_job_enqueue( payload: LlmJobPayload, background_tasks: BackgroundTasks, request: Request, _td: Dict = Depends(lambda: _token_dep()), # late-bound dep ): webhook_config = None if payload.webhook_config: webhook_config = payload.webhook_config.model_dump(mode='json') return await handle_llm_request( _redis, background_tasks, request, str(payload.url), query=payload.q, schema=payload.schema, cache=payload.cache, config=_config, provider=payload.provider, webhook_config=webhook_config, temperature=payload.temperature, api_base_url=payload.base_url, ) @router.get("/llm/job/{task_id}") async def llm_job_status( request: Request, task_id: str, _td: Dict = Depends(lambda: _token_dep()) ): return await handle_task_status(_redis, task_id, base_url=str(request.base_url)) # ---------- CRAWL job ------------------------------------------------------- @router.post("/crawl/job", status_code=202) async def crawl_job_enqueue( payload: CrawlJobPayload, background_tasks: BackgroundTasks, _td: Dict = Depends(lambda: _token_dep()), ): webhook_config = None if payload.webhook_config: webhook_config = payload.webhook_config.model_dump(mode='json') return await handle_crawl_job( _redis, background_tasks, [str(u) for u in payload.urls], payload.browser_config, payload.crawler_config, config=_config, webhook_config=webhook_config, ) @router.get("/crawl/job/{task_id}") async def crawl_job_status( request: Request, task_id: str, _td: Dict = Depends(lambda: _token_dep()) ): return await handle_task_status(_redis, task_id, base_url=str(request.base_url))