feat: 打通多源新闻记录链路,检索/日报/知识库可见多源 (方案A+B)

- 模型层: EmbeddingResult/SearchResult 新增 sources 字段(主源居首,旧产物兜底) - M5 run_embedding: events/deduped 产物透传 sources 进 EmbeddingResult - M6 run_qdrant_ingest: payload 写入 sources(M5 → 回查 M4 → 兜底 [主源]) - vectorstore: 检索读取 payload.sources - 日报 HTML / CLI search / MCP: 多源显示「财联社 / 新浪 [多源]」 - 新增 scripts/backfill_qdrant_sources.py: 指纹库为权威源,scroll+upsert 回填存量 (本地模式 set_payload 逐点 0.65s 不可行,改走 ingest 同款快速路径) - 新增 tests/test_multisource.py 10 个;全量 276 passed
2026-08-22 22:26:10 +08:00
parent 8fa27ad65b
commit 80828310d6
11 changed files with 490 additions and 17 deletions
@@ -0,0 +1,165 @@
+"""一次性回填脚本:为 Qdrant 存量 point 的 payload 补充 sources 多源字段。
+
+背景:
+    M5/M6 旧链路未把 M3 多源记录写入 EmbeddingResult / Qdrant payload,
+    导致知识库检索只能看到单源。新链路修复后,此脚本为存量数据补齐。
+
+数据来源(按优先级):
+    1. 指纹库 data/dedup/fingerprints.sqlite3 的 source_ids 列(权威多源记录);
+    2. source_ids 为 NULL 的旧行回退 [source_id];
+    3. 指纹库查不到的 point 回退 payload.source_id。
+
+实现:
+    本地文件模式 Qdrant 的 set_payload 逐点极慢(≈0.65s/点,33k 条约 6 小时),
+    故采用与正常 ingest 相同的快速路径:
+        scroll 分页取全部 point(含向量)→ 合并 sources → 批量 upsert 回写。
+
+注意:
+    Qdrant 为本地文件模式,同一时刻仅允许一个进程打开;
+    执行前请确认无 pipeline 子进程正在运行(避开调度窗口)。
+
+用法:
+    uv run python -m scripts.backfill_qdrant_sources          # 实际执行
+    uv run python -m scripts.backfill_qdrant_sources --dry-run  # 只统计不写入
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import sqlite3
+import sys
+from pathlib import Path
+
+from loguru import logger
+from qdrant_client.http.models import PointStruct
+
+from vectorstore import DEFAULT_COLLECTION, make_qdrant_client
+
+_SCROLL_LIMIT = 1000
+_UPSERT_BATCH = 100
+
+
+def _setup_logger(level: str) -> None:
+    logger.remove()
+    logger.add(
+        sys.stderr,
+        level=level,
+        format="{time:YYYY-MM-DD HH:mm:ss} | {level} | {name} | {message}",
+    )
+
+
+def _load_fingerprint_sources(db_path: Path) -> dict[str, list[str]]:
+    """从指纹库读 url_hash -> sources(source_ids 为 NULL 时回退 [source_id])。"""
+    conn = sqlite3.connect(db_path)
+    conn.row_factory = sqlite3.Row
+    rows = conn.execute(
+        "SELECT url_hash, source_id, source_ids FROM fingerprints"
+    ).fetchall()
+    conn.close()
+
+    result: dict[str, list[str]] = {}
+    for r in rows:
+        sources: list[str] = []
+        if r["source_ids"]:
+            try:
+                val = json.loads(r["source_ids"])
+                if isinstance(val, list):
+                    sources = [s for s in val if s]
+            except (TypeError, ValueError):
+                sources = []
+        if not sources:
+            sources = [r["source_id"]] if r["source_id"] else []
+        # 保证主源居首
+        if r["source_id"] and r["source_id"] in sources:
+            sources = [r["source_id"], *[s for s in sources if s != r["source_id"]]]
+        if sources:
+            result[r["url_hash"]] = sources
+    return result
+
+
+def _build_points(
+    records: list,
+    fp_sources: dict[str, list[str]],
+) -> list[PointStruct]:
+    """把 scroll 记录转回 PointStruct,payload 补入 sources 字段。"""
+    points: list[PointStruct] = []
+    for rec in records:
+        payload = dict(rec.payload or {})
+        url_hash = payload.get("url_hash") or ""
+        source_id = payload.get("source_id") or ""
+        sources = fp_sources.get(url_hash) or ([source_id] if source_id else [])
+        if sources:
+            payload["sources"] = sources
+        points.append(PointStruct(
+            id=rec.id,
+            vector=rec.vector,
+            payload=payload,
+        ))
+    return points
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description="Qdrant 存量 payload 回填 sources 多源字段")
+    parser.add_argument("--db", default="data/dedup/fingerprints.sqlite3",
+                        help="指纹库路径")
+    parser.add_argument("--collection", default=DEFAULT_COLLECTION)
+    parser.add_argument("--dry-run", action="store_true", help="只统计不写入")
+    parser.add_argument("--log-level", default="INFO")
+    args = parser.parse_args()
+
+    _setup_logger(args.log_level)
+
+    fp_sources = _load_fingerprint_sources(Path(args.db))
+    logger.info("指纹库加载完成: {} 条,其中多源 {} 条",
+                len(fp_sources), sum(1 for v in fp_sources.values() if len(v) > 1))
+
+    client = make_qdrant_client()
+
+    # scroll 分页 + (非 dry-run) 批量 upsert 回写
+    total = 0
+    multi_cnt = 0
+    updated = 0
+    offset = None
+    while True:
+        records, offset = client.scroll(
+            collection_name=args.collection,
+            limit=_SCROLL_LIMIT,
+            offset=offset,
+            with_payload=True,
+            with_vectors=True,
+        )
+        if not records:
+            if offset is None:
+                break
+            continue
+        total += len(records)
+        multi_cnt += sum(
+            1 for r in records
+            if len((r.payload or {}).get("sources") or []) > 1
+        )
+        if not args.dry_run:
+            points = _build_points(records, fp_sources)
+            for i in range(0, len(points), _UPSERT_BATCH):
+                client.upsert(
+                    collection_name=args.collection,
+                    points=points[i : i + _UPSERT_BATCH],
+                )
+            updated += len(points)
+        if offset is None:
+            break
+
+    logger.info("Qdrant 现存 point: {} 条(其中 payload 已含多源 {} 条)", total, multi_cnt)
+    if args.dry_run:
+        logger.info("--dry-run: 不执行写入")
+        client.close()
+        return 0
+
+    logger.info("回填完成: 重新 upsert {} 条 point(payload 已补 sources)", updated)
+    client.close()
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
+