初始化

app/cli.py

@@ -0,0 +1,255 @@
+"""English Financial News — CLI 入口"""
+
+import logging
+import sys
+
+from dotenv import load_dotenv
+import typer
+
+# 加载 .env 环境变量（必须在所有模块导入之前）
+load_dotenv()
+
+app = typer.Typer(
+    name="en-news",
+    help="国际财经新闻抓取与深度研究平台",
+    no_args_is_help=True,
+)
+
+# ── 日志配置 ──────────────────────────────────────────
+
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
+    datefmt="%Y-%m-%d %H:%M:%S",
+    stream=sys.stderr,
+)
+
+# 抑制第三方库噪音日志
+for _lib in ("httpx", "httpcore", "openai", "urllib3"):
+    logging.getLogger(_lib).setLevel(logging.WARNING)
+
+logger = logging.getLogger("en-news")
+
+
+@app.command()
+def crawl(
+    source: str | None = typer.Option(
+        None, "--source", "-s",
+        help="只抓取指定 source_id（不传则全部）",
+    ),
+    profile: str | None = typer.Option(
+        None, "--profile", "-p",
+        help="Profile 名称（2g_headless / 8g_headful）",
+    ),
+):
+    """M1: 抓取英文财经新闻（部署海外）"""
+    import os
+    from crawler.orchestrator import run_crawl_sync
+
+    if profile:
+        os.environ["EN_NEWS_PROFILE"] = profile
+        logger.info("📋 使用 Profile: %s", profile)
+
+    try:
+        stats = run_crawl_sync(source_filter=source)
+        typer.echo(f"\n✅ 完成: {stats.sources_crawled} 源, {stats.total_articles} 篇文章")
+        if stats.sources_failed:
+            typer.echo(f"⚠️  {stats.sources_failed} 个源有错误")
+    except FileNotFoundError as e:
+        typer.echo(f"❌ {e}", err=True)
+        raise typer.Exit(code=1)
+    except Exception as e:
+        logger.exception("抓取失败")
+        typer.echo(f"❌ 抓取出错: {e}", err=True)
+        raise typer.Exit(code=1)
+
+
+@app.command()
+def extract(
+    source: str | None = typer.Option(
+        None, "--source", "-s",
+        help="只处理指定 source_id（不传则全部）",
+    ),
+):
+    """M2: 英文正文提取（trafilatura）"""
+    from extractor.pipeline import process_all_sources
+
+    try:
+        stats = process_all_sources(source_filter=source)
+        typer.echo(
+            f"\n✅ 提取: {stats['sources_processed']} 源, "
+            f"{stats['total_articles']} 篇, {stats['elapsed_sec']:.1f}s"
+        )
+    except Exception as e:
+        logger.exception("正文提取失败")
+        typer.echo(f"❌ 提取出错: {e}", err=True)
+        raise typer.Exit(code=1)
+
+
+@app.command()
+def dedup():
+    """M3: 三层去重"""
+    from dedup.pipeline import dedup_all_sources
+
+    try:
+        stats = dedup_all_sources()
+        typer.echo(
+            f"\n✅ 去重: {stats['sources_processed']} 源, "
+            f"唯一 {stats['unique']} / 重复 {stats['duplicate']} / "
+            f"总计 {stats['total_articles']}, {stats['elapsed_sec']:.1f}s"
+        )
+    except Exception as e:
+        logger.exception("去重失败")
+        typer.echo(f"❌ 去重出错: {e}", err=True)
+        raise typer.Exit(code=1)
+
+
+@app.command()
+def translate():
+    """M4: 全文翻译 + 投资事件抽取（LLM）"""
+    from llm.pipeline import translate_all_deduped
+
+    try:
+        stats = translate_all_deduped()
+        typer.echo(
+            f"\n✅ 翻译+事件抽取: {stats['success']}/{stats['total']} 篇, "
+            f"{stats['elapsed_sec']:.1f}s ({stats['provider']}/{stats['model']})"
+        )
+    except Exception as e:
+        logger.exception("翻译失败")
+        typer.echo(f"❌ 翻译出错: {e}", err=True)
+        raise typer.Exit(code=1)
+
+
+@app.command()
+def embed():
+    """M5: 向量生成"""
+    from embedding.pipeline import embed_all_events
+
+    try:
+        stats = embed_all_events()
+        typer.echo(
+            f"\n✅ 向量生成: {stats['success']}/{stats['total']} 篇, "
+            f"{stats['elapsed_sec']:.1f}s ({stats['provider']}/{stats['model']})"
+        )
+    except Exception as e:
+        logger.exception("向量生成失败")
+        typer.echo(f"❌ 向量生成出错: {e}", err=True)
+        raise typer.Exit(code=1)
+
+
+@app.command()
+def index(
+    recreate: bool = typer.Option(
+        False, "--recreate",
+        help="重建 collection（会删除已有数据）",
+    ),
+):
+    """M6: Qdrant 入库"""
+    from vectorstore.pipeline import get_collection_info, ingest_all_embeddings
+
+    try:
+        stats = ingest_all_embeddings(recreate=recreate)
+        typer.echo(
+            f"\n✅ 入库: {stats['ingested']}/{stats['total']} 条, "
+            f"{stats['elapsed_sec']:.1f}s"
+        )
+        info = get_collection_info()
+        typer.echo(f"📊 Collection: {info['name']} — {info['vectors_count']} 条向量")
+    except Exception as e:
+        logger.exception("入库失败")
+        typer.echo(f"❌ 入库出错: {e}", err=True)
+        raise typer.Exit(code=1)
+
+
+@app.command()
+def search(
+    query: str = typer.Argument(..., help="中文检索查询"),
+    top_k: int = typer.Option(10, help="返回结果数"),
+):
+    """M6: Qdrant 语义检索"""
+    from vectorstore.pipeline import search_news
+
+    try:
+        results = search_news(query, top_k=top_k)
+        if not results:
+            typer.echo("🔍 未找到相关结果")
+            return
+
+        typer.echo(f"\n🔍 搜索: {query}\n")
+        for i, r in enumerate(results, 1):
+            typer.echo(f"{i}. [{r.source_id}] score={r.score:.4f}")
+            typer.echo(f"   📰 {r.title_zh or r.title}")
+            if r.events:
+                events_summary = ", ".join(
+                    f"{ev.get('event_type','')}({ev.get('sentiment','')})"
+                    for ev in r.events[:3]
+                )
+                typer.echo(f"   📌 事件: {events_summary}")
+            typer.echo(f"   🔗 {r.url}")
+            typer.echo()
+    except Exception as e:
+        logger.exception("搜索失败")
+        typer.echo(f"❌ 搜索出错: {e}", err=True)
+        raise typer.Exit(code=1)
+
+
+@app.command()
+def report():
+    """M7: 日报生成"""
+    from scheduler.reporter import generate_report
+
+    try:
+        path = generate_report()
+        if path:
+            typer.echo(f"\n✅ 日报已生成: {path}")
+        else:
+            typer.echo("⚠️  无数据，跳过日报生成")
+    except Exception as e:
+        logger.exception("日报生成失败")
+        typer.echo(f"❌ 日报生成出错: {e}", err=True)
+        raise typer.Exit(code=1)
+
+
+@app.command()
+def pipeline(
+    skip_report: bool = typer.Option(
+        False, "--skip-report",
+        help="跳过日报生成",
+    ),
+):
+    """M7: 一键运行完整管道 M2→M6（+ 可选日报）"""
+    from crawler.utils import get_news_day
+    from scheduler.pipeline import run_pipeline
+
+    date_str = get_news_day()
+    typer.echo(f"🚀 开始全链路管道，日期: {date_str}\n")
+
+    try:
+        result = run_pipeline(date_str, skip_report=skip_report)
+
+        typer.echo(f"\n{'='*50}")
+        typer.echo(f"Pipeline 完成: {result.success_count}/{len(result.steps)} 成功")
+        for s in result.steps:
+            flag = "✅" if s.success else "❌"
+            typer.echo(f"  {flag} {s.name}: {s.message} ({s.elapsed_sec:.0f}s)")
+        if result.finished_at and result.started_at:
+            total = (result.finished_at - result.started_at).total_seconds()
+            typer.echo(f"\n⏱ 总耗时: {total:.0f}s")
+    except Exception as e:
+        logger.exception("管道执行失败")
+        typer.echo(f"❌ 管道执行出错: {e}", err=True)
+        raise typer.Exit(code=1)
+
+
+@app.command()
+def mcp_server():
+    """M8: 启动 MCP 服务（供 Claude Code / Cherry Studio 调用）"""
+    from mcp_server.server import mcp
+
+    typer.echo("🚀 启动国际财经 Deep Research MCP 服务...")
+    mcp.run()
+
+
+if __name__ == "__main__":
+    app()