274 lines
12 KiB
Python
274 lines
12 KiB
Python
import inspect
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import json
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from concurrent.futures import ThreadPoolExecutor
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from collections.abc import Callable
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from sqlalchemy import func, select
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from sqlalchemy.orm import Session, sessionmaker
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from app.config import get_settings
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from app.db import SessionLocal
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from app.models import Comment, ContentItem, Hotspot, Task
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from app.platforms.base import PlatformAPIError, TikHubClient
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from app.platforms.douyin import DouyinPlatform
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from app.platforms.xiaohongshu import XiaohongshuPlatform
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from app.schemas import CreateTaskRequest
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from app.services.ai_service import OpenAICompatibleAIClient, analyze_comments_with_retry, build_report_summary_prompt, calculate_analysis_status
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from app.services.report_service import generate_hotspot_report, generate_item_report
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RUNNING_TASK_MESSAGE = "当前有正在运行的任务，请稍后再试"
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RESTART_ERROR_MESSAGE = "系统重启，任务被中断"
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task_executor = ThreadPoolExecutor(max_workers=1)
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def has_running_task(session: Session) -> bool:
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return session.scalar(select(Task.id).where(Task.status == "running").limit(1)) is not None
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def recover_running_tasks(session: Session) -> int:
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tasks = list(session.scalars(select(Task).where(Task.status == "running")))
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for task in tasks:
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task.status = "failed"
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task.error_stage = "system"
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task.error_type = "unexpected_restart"
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task.error_message = RESTART_ERROR_MESSAGE
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session.commit()
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return len(tasks)
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def build_platform(platform: str):
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settings = get_settings()
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client = TikHubClient(
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base_url=settings.tikhub_base_url,
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api_key=settings.tikhub_api_key,
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timeout_seconds=settings.http_timeout_seconds,
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max_retries=settings.http_max_retries,
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)
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if platform == "xiaohongshu":
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return XiaohongshuPlatform(client)
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if platform == "douyin":
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return DouyinPlatform(client)
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raise ValueError(f"Unsupported platform: {platform}")
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def build_ai_client() -> OpenAICompatibleAIClient | None:
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settings = get_settings()
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if settings.ai_base_url and settings.ai_api_key and settings.ai_model:
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return OpenAICompatibleAIClient(
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base_url=settings.ai_base_url,
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api_key=settings.ai_api_key,
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model=settings.ai_model,
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timeout_seconds=settings.ai_timeout_seconds,
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)
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return None
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def build_ai_requester(client: OpenAICompatibleAIClient | None = None):
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client = client if client is not None else build_ai_client()
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if client is not None:
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return lambda prompt: client.request(
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prompt,
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system_prompt="只返回 JSON Array，不输出 Markdown 或解释性自然语言。",
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)
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def fallback_requester(_prompt: str) -> str:
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return "[]"
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return fallback_requester
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def build_report_summary_provider(client: OpenAICompatibleAIClient | None):
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if client is None:
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return None
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def summarize_report(metrics: dict, typical: dict, *, word_limit: int = 200) -> str:
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return client.request(
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build_report_summary_prompt(metrics, typical, word_limit=word_limit),
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system_prompt="只返回一段中文总结，不使用 Markdown。",
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)
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return summarize_report
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def build_ai_dependencies():
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client = build_ai_client()
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requester = build_ai_requester(client)
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return requester, build_report_summary_provider(client)
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def create_task(session: Session, request: CreateTaskRequest, *, submit_background: bool = True) -> Task:
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task = Task(
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platform=request.platform,
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status="running",
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hotspot_limit=request.hotspot_limit,
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item_limit_per_hotspot=request.item_limit_per_hotspot,
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comment_limit_per_item=request.comment_limit_per_item,
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total_items_count=0,
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processed_items_count=0,
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successful_items_count=0,
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failed_items_count=0,
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analysis_success_rate=0.0,
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analysis_status="normal",
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)
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session.add(task)
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session.commit()
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session.refresh(task)
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if submit_background:
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task_executor.submit(run_task, task.id)
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return task
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def list_tasks(session: Session) -> list[Task]:
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return list(session.scalars(select(Task).order_by(Task.created_at.desc())))
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def get_task(session: Session, task_id: str) -> Task | None:
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return session.get(Task, task_id)
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def run_task(task_id: str, *, session_factory: Callable[[], Session] | sessionmaker = SessionLocal) -> None:
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session = session_factory()
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close_session = hasattr(session, "close")
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try:
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task = session.get(Task, task_id)
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if task is None:
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return
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try:
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platform = build_platform(task.platform)
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ai_requester, report_summary_provider = build_ai_dependencies()
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try:
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hotspots = platform.fetch_hotspots(limit=task.hotspot_limit)
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except PlatformAPIError as exc:
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_mark_task_failed(task, "crawl_hotspots", exc.error_type, str(exc))
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session.commit()
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return
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except Exception as exc:
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_mark_task_failed(task, "crawl_hotspots", "api_error", str(exc))
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session.commit()
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return
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for hotspot_data in hotspots:
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hotspot = Hotspot(
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task_id=task.id,
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platform=task.platform,
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source_hot_id=hotspot_data.source_hot_id,
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rank=hotspot_data.rank,
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title=hotspot_data.title,
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heat_value=hotspot_data.heat_value,
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raw_data=json.dumps(hotspot_data.raw_data or {}, ensure_ascii=False),
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)
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session.add(hotspot)
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session.flush()
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try:
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items = platform.search_items_by_hotspot(hotspot.title, limit=task.item_limit_per_hotspot)
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except Exception as exc:
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task.failed_items_count += task.item_limit_per_hotspot
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task.error_stage = "crawl_items"
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task.error_type = getattr(exc, "error_type", "api_error")
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task.error_message = str(exc)
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session.commit()
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continue
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task.total_items_count += len(items)
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seen_item_ids: set[str] = set()
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for item_data in items:
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if item_data.source_item_id in seen_item_ids:
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continue
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seen_item_ids.add(item_data.source_item_id)
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item = ContentItem(
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task_id=task.id,
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hotspot_id=hotspot.id,
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platform=task.platform,
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source_item_id=item_data.source_item_id,
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item_type=item_data.item_type,
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title=item_data.title,
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summary=item_data.summary,
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url=item_data.url,
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status="pending",
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raw_data=json.dumps(item_data.raw_data or {}, ensure_ascii=False),
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)
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session.add(item)
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session.flush()
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try:
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comments = platform.fetch_comments(item.source_item_id, limit=task.comment_limit_per_item)
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for comment_data in comments:
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session.add(
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Comment(
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task_id=task.id,
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hotspot_id=hotspot.id,
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content_item_id=item.id,
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platform=task.platform,
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source_comment_id=comment_data.source_comment_id,
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content=comment_data.content,
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author=comment_data.author,
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like_count=comment_data.like_count,
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comment_time=comment_data.comment_time,
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raw_data=json.dumps(comment_data.raw_data or {}, ensure_ascii=False),
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)
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)
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session.flush()
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item_comments = list(session.scalars(select(Comment).where(Comment.content_item_id == item.id)))
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ai_results = analyze_comments_with_retry(
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[{"comment_id": comment.id, "content": comment.content} for comment in item_comments],
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requester=ai_requester,
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max_retries=get_settings().ai_max_retries,
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)
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results_by_comment_id = {result.comment_id: result for result in ai_results}
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for comment in item_comments:
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result = results_by_comment_id.get(comment.id)
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if result is None:
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comment.sentiment = "unknown"
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comment.labels = "[]"
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comment.reason = "ai_missing_result"
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comment.ai_analysis_status = "failed"
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continue
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comment.sentiment = result.sentiment
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comment.labels = json.dumps(result.labels, ensure_ascii=False)
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comment.reason = result.reason
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comment.ai_analysis_status = result.ai_analysis_status
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item.status = "success"
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task.successful_items_count += 1
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generate_item_report(session, item.id, summary_provider=report_summary_provider)
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except Exception as exc:
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item.status = "failed"
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item.error_stage = "crawl_comments"
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item.error_type = getattr(exc, "error_type", "api_error")
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item.error_message = str(exc)
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task.failed_items_count += 1
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task.error_stage = item.error_stage
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task.error_type = item.error_type
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task.error_message = item.error_message
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finally:
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task.processed_items_count += 1
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session.commit()
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if task.successful_items_count > 0:
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total_comments = session.scalar(select(func.count(Comment.id)).where(Comment.task_id == task.id)) or 0
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success_comments = sum(1 for comment in task.comments if comment.ai_analysis_status == "success")
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task.analysis_success_rate, task.analysis_status = calculate_analysis_status(
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success_count=success_comments,
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total_count=total_comments,
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)
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for hotspot in task.hotspots:
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generate_hotspot_report(session, hotspot.id, summary_provider=report_summary_provider)
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task.status = "success"
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else:
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_mark_task_failed(task, task.error_stage or "crawl_items", task.error_type or "no_successful_items", task.error_message or "没有任何内容条目成功")
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session.commit()
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except Exception as exc:
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_mark_task_failed(task, "system", "unexpected_error", str(exc))
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session.commit()
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finally:
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if close_session:
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session.close()
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def _mark_task_failed(task: Task, stage: str, error_type: str, message: str) -> None:
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task.status = "failed"
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task.error_stage = stage
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task.error_type = error_type
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task.error_message = message
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