Support kind=llm profiles (instruction/schema), optional multi-event posts via #eN URLs, and recover stale running/queued parse jobs after worker crashes. Co-authored-by: Cursor <cursoragent@cursor.com>
111 lines
3.7 KiB
Python
111 lines
3.7 KiB
Python
import json
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import os
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import sys
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from pathlib import Path
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import redis
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from sqlalchemy.orm import Session
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# Allow importing shared contracts from monorepo root in local runs
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_HERE = Path(__file__).resolve()
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for _candidate in (_HERE.parent, *_HERE.parents):
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if (_candidate / "contracts").is_dir():
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if str(_candidate) not in sys.path:
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sys.path.insert(0, str(_candidate))
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break
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from contracts.queues import queue_key_for_source # noqa: E402
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from contracts.sources import TelegramSourceConfig, parse_source_config # noqa: E402
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from ..models import ParseChannel, ParseJob, ParserProfile # noqa: E402
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REDIS_URL = os.getenv("REDIS_URL", "redis://redis:6379/0")
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def get_redis() -> redis.Redis:
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return redis.from_url(REDIS_URL, decode_responses=True)
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def flatten_pair_config(
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channel: ParseChannel,
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profile: ParserProfile,
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*,
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limit: int = 100,
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) -> dict:
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"""Expand Profile + Channel into Redis/CP source_config."""
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kind = (profile.kind or "heuristic").strip().lower()
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if kind == "llm":
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from contracts.llm_profile import LlmProfile
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if not profile.llm_profile:
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raise ValueError("ParserProfile.llm_profile is empty")
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llm = LlmProfile.model_validate(profile.llm_profile)
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cfg = TelegramSourceConfig(
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channel=channel.channel.strip(),
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limit=limit,
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extract_mode="llm",
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extract_schema=llm.extract_schema,
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instruction=llm.instruction,
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required_fields=list(llm.required_fields),
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multi_event=bool(llm.multi_event),
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sample_post=profile.sample_post or None,
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)
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return cfg.model_dump()
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if not profile.heuristic_profile:
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raise ValueError("ParserProfile.heuristic_profile is empty")
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cfg = TelegramSourceConfig(
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channel=channel.channel.strip(),
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limit=limit,
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extract_mode="profile",
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heuristic_profile=profile.heuristic_profile,
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sample_post=profile.sample_post or None,
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)
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return cfg.model_dump()
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def resolve_job_source_config(db: Session, job: ParseJob) -> dict:
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"""
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For pair jobs, rebuild flat source_config from current Profile/Channel.
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Legacy jobs keep stored source_config.
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"""
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if job.profile_id and job.channel_id:
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profile = db.query(ParserProfile).filter(ParserProfile.id == job.profile_id).first()
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channel = db.query(ParseChannel).filter(ParseChannel.id == job.channel_id).first()
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if not profile:
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raise ValueError(f"ParserProfile {job.profile_id} not found")
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if not channel:
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raise ValueError(f"ParseChannel {job.channel_id} not found")
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existing = job.source_config or {}
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limit = existing.get("limit", 100)
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if not isinstance(limit, int) or limit < 1:
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limit = 100
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flattened = flatten_pair_config(channel, profile, limit=limit)
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job.source_config = flattened
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return flattened
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return dict(job.source_config or {})
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def enqueue_job(job_id: int, source_type: str, source_config: dict) -> None:
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# Validate known configs early; unknown types still raise from queue_key_for_source
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try:
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parse_source_config(source_type, source_config or {})
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except Exception:
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# Keep enqueue resilient for legacy rows; worker validates again
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pass
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payload = {
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"job_id": job_id,
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"source_type": source_type,
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"source_config": source_config or {},
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}
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key = queue_key_for_source(source_type)
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get_redis().rpush(key, json.dumps(payload))
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def enqueue_parse_job(db: Session, job: ParseJob) -> None:
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"""Resolve (flatten if pair) then push to Redis."""
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source_config = resolve_job_source_config(db, job)
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db.commit()
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enqueue_job(job.id, job.source_type, source_config)
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