init: RAG 知识库服务初始提交

- 后端 API（Flask + Gunicorn） - RAG 引擎（混合检索 + 云端 Reranker + 引用溯源） - 文档解析（MinerU + 多格式支持） - Docker 生产部署配置 - 排除前端项目、敏感配置、模型文件
2026-06-04 17:35:27 +08:00
commit 100d1a06eb
158 changed files with 64534 additions and 0 deletions
--- a/scripts/fix_image_paths.py
+++ b/scripts/fix_image_paths.py
@@ -0,0 +1,116 @@
+# -*- coding: utf-8 -*-
+"""
+修复向量库中的图片路径格式
+
+问题：历史数据中 image_path 存储为 "images/xxx.jpg" 格式
+修复：统一改为只存储文件名 "xxx.jpg"
+
+使用方式：
+    python scripts/fix_image_paths.py [--dry-run]
+"""
+
+import argparse
+import os
+import sys
+
+# 添加项目根目录到路径
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+import chromadb
+
+
+def fix_image_paths(dry_run: bool = False):
+    """
+    修复向量库中的图片路径格式
+
+    Args:
+        dry_run: 仅预览，不实际修改
+    """
+    chroma_path = "knowledge/vector_store/chroma"
+    client = chromadb.PersistentClient(path=chroma_path)
+
+    # 获取所有集合
+    collections = client.list_collections()
+    print(f"找到 {len(collections)} 个集合")
+
+    for collection in collections:
+        print(f"\n处理集合: {collection.name}")
+
+        # 获取所有图片类型的切片
+        try:
+            results = collection.get(
+                where={"chunk_type": "image"},
+                include=["metadatas", "documents", "embeddings"]
+            )
+
+            if not results["ids"]:
+                print(f"  无图片类型切片")
+                continue
+
+            print(f"  找到 {len(results['ids'])} 个图片切片")
+
+            # 检查需要修复的路径
+            needs_fix = []
+            for i, (id, meta) in enumerate(zip(results["ids"], results["metadatas"])):
+                image_path = meta.get("image_path", "")
+                if image_path and ("/" in image_path or "\\" in image_path):
+                    # 路径包含目录，需要修复
+                    new_path = os.path.basename(image_path)
+                    needs_fix.append({
+                        "id": id,
+                        "old_path": image_path,
+                        "new_path": new_path,
+                        "index": i
+                    })
+
+            if not needs_fix:
+                print(f"  所有路径格式正确，无需修复")
+                continue
+
+            print(f"  需要修复 {len(needs_fix)} 条记录:")
+            for item in needs_fix[:5]:  # 只显示前5条
+                print(f"    {item['old_path']} -> {item['new_path']}")
+            if len(needs_fix) > 5:
+                print(f"    ... 还有 {len(needs_fix) - 5} 条")
+
+            if dry_run:
+                print(f"  [DRY-RUN] 跳过实际修改")
+                continue
+
+            # 执行修复
+            ids_to_update = []
+            metadatas_to_update = []
+
+            for item in needs_fix:
+                # 更新元数据
+                new_meta = results["metadatas"][item["index"]].copy()
+                new_meta["image_path"] = item["new_path"]
+                ids_to_update.append(item["id"])
+                metadatas_to_update.append(new_meta)
+
+            # 批量更新
+            collection.update(
+                ids=ids_to_update,
+                metadatas=metadatas_to_update
+            )
+            print(f"  ✓ 已修复 {len(ids_to_update)} 条记录")
+
+        except Exception as e:
+            print(f"  处理集合 {collection.name} 时出错: {e}")
+
+
+def main():
+    parser = argparse.ArgumentParser(description="修复向量库中的图片路径格式")
+    parser.add_argument("--dry-run", action="store_true", help="仅预览，不实际修改")
+    args = parser.parse_args()
+
+    if args.dry_run:
+        print("=== DRY-RUN 模式：仅预览，不修改数据 ===\n")
+
+    fix_image_paths(dry_run=args.dry_run)
+
+    print("\n完成!")
+
+
+if __name__ == "__main__":
+    main()