feat: 接入 DeepSeek AI 分析公告是否为中国电信可承接项目

- 新增 ai_enabled/ai_api_key/ai_base_url/ai_model 等配置项，通过 .env 管理
- 新增 app/services/ai_analyzer.py — DeepSeek API 调用 + 详情页正文提取
- 新增 extract_page_content() 从详情页抓取正文供 AI 分析
- Announcement 模型新增 ai_relevant / ai_analysis 字段
- 流水线集成 AI 分析步骤（关键词匹配后、通知前）
- AI 标记为可承接的项目额外发送 markdown 着重通知
- 创建 alembic 迁移版本 6e8f4c2d1b0a

app/services/pipeline.py

@@ -1,8 +1,12 @@
+import logging
 from typing import Any
 
+from app.config import settings
 from app.crawler.base import PipelineConfig, PipelineResult
 from app.services.filter_service import dedup_by_hash
 
+logger = logging.getLogger(__name__)
+
 
 class PostCrawlPipeline:
     def __init__(self, db_session, notification_service):
@@ -41,6 +45,10 @@ class PostCrawlPipeline:
         if to_notify:
             to_notify = await self._exclude_sent(to_notify)
 
+        # 5.5 AI 分析（可选）
+        if settings.ai_enabled and to_notify:
+            await self._ai_analyze(to_notify)
+
         # 6. Notify
         if config.notify_mode == "all":
             result.notified = await self._send_notifications(to_notify)
@@ -129,3 +137,52 @@ class PostCrawlPipeline:
     def _match_keywords(announcement: dict[str, Any], keywords: list[str]) -> bool:
         text = f"{announcement.get('title', '')} {announcement.get('purchase_name', '')}"
         return any(kw in text for kw in keywords)
+
+    async def _ai_analyze(self, announcements: list[dict[str, Any]]) -> None:
+        """对公告列表执行 AI 分析，将结果附加到每条公告的 ai_result 字段，并更新数据库"""
+        from app.services.ai_analyzer import AiAnalyzer
+
+        analyzer = AiAnalyzer()
+        logger.info("AI 分析开始：共 %d 条公告", len(announcements))
+
+        results = await analyzer.analyze_batch(announcements)
+
+        ai_updates = []
+        for ann, ai_result in zip(announcements, results):
+            ann["ai_result"] = {
+                "is_relevant": ai_result.is_relevant,
+                "reason": ai_result.reason,
+                "business_type": ai_result.business_type,
+            }
+            if ai_result.error:
+                logger.warning("AI 分析失败 [%s]: %s", ann.get("title", "")[:30], ai_result.error)
+            else:
+                ai_updates.append({
+                    "content_hash": ann["content_hash"],
+                    "ai_relevant": ai_result.is_relevant,
+                    "ai_analysis": ai_result.reason,
+                })
+                if ai_result.is_relevant:
+                    logger.info("AI 标记可承接项目: %s (%s)", ann.get("title", "")[:40], ai_result.business_type)
+
+        # 批量更新数据库中的 AI 分析结果
+        if ai_updates:
+            await self._update_ai_results(ai_updates)
+
+    async def _update_ai_results(self, updates: list[dict[str, Any]]) -> None:
+        """批量更新公告的 AI 分析结果到数据库"""
+        from sqlalchemy import update
+
+        from app.models.announcement import Announcement
+
+        for u in updates:
+            stmt = (
+                update(Announcement)
+                .where(Announcement.content_hash == u["content_hash"])
+                .values(
+                    ai_relevant=u["ai_relevant"],
+                    ai_analysis=u["ai_analysis"],
+                )
+            )
+            await self.db.execute(stmt)
+        await self.db.commit()