dev：编制依据入库完成

.env

@@ -14,3 +14,7 @@ MILVUS_USER=
 MILVUS_PASSWORD=
 
 DATABASE_URL=mysql+aiomysql://root:lq123@192.168.92.61:13306/lq_oauth_db
+# OpenAI Embedding向量模型配置
+EMBEDDING_BASE_URL=http://192.168.91.253:9003/v1
+EMBEDDING_MODEL=Qwen3-Embedding-8B
+EMBEDDING_API_KEY=dummy

pyproject.toml

@@ -5,6 +5,9 @@ description = "Add your description here"
 readme = "README.md"
 requires-python = ">=3.12"
 dependencies = [
+    "aiomysql>=0.3.2",
+    "langchain>=1.2.7",
+    "langchain-openai>=1.1.7",
     "minio>=7.2.20",
     "openpyxl>=3.1.5",
     "pymilvus>=2.6.6",

src/app/config/__init__.py

@@ -1,14 +0,0 @@
-from .setting import Settings, load_settings, settings
-from .database import get_async_engine, get_async_sessionmaker
-from .minio_client import get_minio_client
-from .milvus_client import get_milvus_connection
-
-__all__ = [
-	"Settings",
-	"load_settings",
-	"settings",
-	"get_async_engine",
-	"get_async_sessionmaker",
-	"get_minio_client",
-	"get_milvus_connection",
-]

src/app/config/database.py

@@ -17,11 +17,11 @@ def get_async_engine():
     if _engine is not None:
         return _engine
 
-    if not settings.database_url:
+    if not settings.DATABASE_URL:
         raise ValueError("DATABASE_URL is not configured")
 
     _engine = create_async_engine(
-        settings.database_url,
+        settings.DATABASE_URL,
         echo=False,
         pool_pre_ping=True,
         pool_recycle=3600,
@@ -39,3 +39,4 @@ def get_async_sessionmaker():
 
     _sessionmaker = async_sessionmaker(engine, expire_on_commit=False)
     return _sessionmaker
+

src/app/config/embeddings.py

@@ -0,0 +1,26 @@
+"""OpenAI Embeddings 配置和客户端获取。"""
+from __future__ import annotations
+
+from functools import lru_cache
+
+from langchain_openai import OpenAIEmbeddings
+
+from .setting import settings
+
+
+@lru_cache(maxsize=1)
+def get_embeddings() -> OpenAIEmbeddings:
+    """
+    创建或返回已缓存的 OpenAI Embeddings 客户端。
+    
+    Returns:
+        OpenAIEmbeddings 实例
+    """
+    if not settings.EMBEDDING_BASE_URL or not settings.EMBEDDING_MODEL:
+        raise ValueError("Embedding configuration is incomplete")
+    
+    return OpenAIEmbeddings(
+        base_url=settings.EMBEDDING_BASE_URL,
+        model=settings.EMBEDDING_MODEL,
+        api_key=settings.EMBEDDING_API_KEY,
+    )

src/app/config/milvus_client.py

@@ -1,32 +1,16 @@
-"""基于 .env 配置创建/获取 Milvus 连接。"""
 from __future__ import annotations
-
-from typing import Optional
-
-from pymilvus import connections
-
+from functools import lru_cache
+from pymilvus import MilvusClient
 from .setting import settings
 
-_default_alias = "default"
-
-
-def get_milvus_connection(alias: Optional[str] = None):
-    """连接 Milvus（若已连接则复用）并返回连接别名。"""
-
-    alias_name = alias or _default_alias
-    if connections.has_connection(alias_name):
-        return alias_name
-
-    cfg = settings.milvus
-    if not cfg.host or not cfg.port:
+@lru_cache(maxsize=1)
+def get_milvusclient() -> MilvusClient:
+    if not settings.MILVUS_HOST or not settings.MILVUS_PORT:
         raise ValueError("Milvus configuration is incomplete")
 
-    connections.connect(
-        alias=alias_name,
-        host=cfg.host,
-        port=cfg.port,
-        user=cfg.user or None,
-        password=cfg.password or None,
-        db_name=cfg.db or None,
-    )
-    return alias_name
+    uri = f"http://{settings.MILVUS_HOST}:{settings.MILVUS_PORT}"
+    
+    return MilvusClient(
+        uri=uri,
+        db_name=settings.MILVUS_DB
+    )

src/app/config/minio_client.py

@@ -16,14 +16,13 @@ def get_minio_client():
     if _client is not None:
         return _client
 
-    cfg = settings.minio
-    if not cfg.endpoint or not cfg.access_key or not cfg.secret_key:
+    if not settings.MINIO_ENDPOINT or not settings.MINIO_ACCESS_KEY or not settings.MINIO_SECRET_KEY:
         raise ValueError("MinIO configuration is incomplete")
 
     _client = Minio(
-        cfg.endpoint,
-        access_key=cfg.access_key,
-        secret_key=cfg.secret_key,
-        secure=cfg.use_ssl,
+        settings.MINIO_ENDPOINT,
+        access_key=settings.MINIO_ACCESS_KEY,
+        secret_key=settings.MINIO_SECRET_KEY,
+        secure=settings.MINIO_USE_SSL,
     )
-    return _client
+    return _client

src/app/config/setting.py

@@ -2,12 +2,10 @@
 from __future__ import annotations
 
 import os
-from dataclasses import dataclass
 from pathlib import Path
-from typing import Optional
 
-# Resolve project root (three levels up from this file: config -> app -> src -> project root)
-PROJECT_ROOT = Path(__file__).resolve().parent.parent.parent
+# Resolve project root - .env should be at workspace root
+PROJECT_ROOT = Path(__file__).resolve().parent.parent.parent.parent
 ENV_FILE = PROJECT_ROOT / ".env"
 
 
@@ -29,70 +27,35 @@ def _load_env_file(path: Path = ENV_FILE) -> None:
             os.environ[key] = value
 
 
-def _to_bool(value: Optional[str], default: bool = False) -> bool:
-    if value is None:
-        return default
-    return value.strip().lower() in {"1", "true", "t", "yes", "y", "on"}
-
-
-def _to_int(value: Optional[str], default: int) -> int:
-    try:
-        return int(value) if value is not None and value != "" else default
-    except ValueError:
-        return default
-
-
-@dataclass
-class MinioSettings:
-    endpoint: str
-    access_key: str
-    secret_key: str
-    bucket_name: str
-    use_ssl: bool
-    base_path: str
-
-
-@dataclass
-class MilvusSettings:
-    host: str
-    port: int
-    db: str
-    user: Optional[str]
-    password: Optional[str]
-
-
-@dataclass
 class Settings:
-    minio: MinioSettings
-    milvus: MilvusSettings
-    database_url: str
-
-
-def load_settings(env_file: Path = ENV_FILE) -> Settings:
-    """Load settings from the given .env file into structured objects."""
-    _load_env_file(env_file)
-
-    minio = MinioSettings(
-        endpoint=os.getenv("MINIO_ENDPOINT", ""),
-        access_key=os.getenv("MINIO_ACCESS_KEY", ""),
-        secret_key=os.getenv("MINIO_SECRET_KEY", ""),
-        bucket_name=os.getenv("MINIO_BUCKET_NAME", ""),
-        use_ssl=_to_bool(os.getenv("MINIO_USE_SSL"), default=False),
-        base_path=os.getenv("MINIO_BASE_PATH", ""),
-    )
-
-    milvus = MilvusSettings(
-        host=os.getenv("MILVUS_HOST", ""),
-        port=_to_int(os.getenv("MILVUS_PORT"), default=19530),
-        db=os.getenv("MILVUS_DB", ""),
-        user=os.getenv("MILVUS_USER"),
-        password=os.getenv("MILVUS_PASSWORD"),
-    )
-
-    database_url = os.getenv("DATABASE_URL", "")
-
-    return Settings(minio=minio, milvus=milvus, database_url=database_url)
-
-
-# Eagerly load settings so they are available on import.
-settings = load_settings()
+    """Settings loaded from .env file."""
+
+    def __init__(self):
+        _load_env_file()
+        
+        # MinIO settings
+        self.MINIO_ENDPOINT = os.getenv("MINIO_ENDPOINT", "")
+        self.MINIO_ACCESS_KEY = os.getenv("MINIO_ACCESS_KEY", "")
+        self.MINIO_SECRET_KEY = os.getenv("MINIO_SECRET_KEY", "")
+        self.MINIO_BUCKET_NAME = os.getenv("MINIO_BUCKET_NAME", "")
+        self.MINIO_USE_SSL = os.getenv("MINIO_USE_SSL", "False").lower() in {"true", "1", "yes"}
+        self.MINIO_BASE_PATH = os.getenv("MINIO_BASE_PATH", "")
+        
+        # Milvus settings
+        self.MILVUS_HOST = os.getenv("MILVUS_HOST", "")
+        self.MILVUS_PORT = int(os.getenv("MILVUS_PORT", "19530"))
+        self.MILVUS_DB = os.getenv("MILVUS_DB", "")
+        self.MILVUS_USER = os.getenv("MILVUS_USER")
+        self.MILVUS_PASSWORD = os.getenv("MILVUS_PASSWORD")
+        
+        # Database settings
+        self.DATABASE_URL = os.getenv("DATABASE_URL", "")
+        
+        # Embedding settings
+        self.EMBEDDING_BASE_URL = os.getenv("EMBEDDING_BASE_URL", "")
+        self.EMBEDDING_MODEL = os.getenv("EMBEDDING_MODEL", "")
+        self.EMBEDDING_API_KEY = os.getenv("EMBEDDING_API_KEY", "")
+
+
+# Eagerly load settings on import
+settings = Settings()

src/app/scripts/base_create_collection.py

@@ -0,0 +1,70 @@
+"""Milvus Collection 创建脚本。"""
+from __future__ import annotations
+
+from pymilvus import DataType, Function, FunctionType
+
+from app.config.milvus_client import get_milvusclient
+
+# Collection 配置
+PARENT_COLLECTION_NAME = "test_27_parent"
+CHILD_COLLECTION_NAME = "test_27_child"
+DENSE_DIM_DEFAULT = 4096
+
+
+def ensure_collection(collection_name: str, dense_dim: int = DENSE_DIM_DEFAULT):
+    """
+    创建或获取 Milvus Collection。
+    
+    Args:
+        collection_name: Collection 名称
+        dense_dim: 密集向量维度，默认 1024
+    """
+    client = get_milvusclient()
+    
+    if client.has_collection(collection_name=collection_name):
+        return
+
+    schema = client.create_schema(auto_id=True, enable_dynamic_fields=False)
+
+    # 主键和核心字段
+    schema.add_field("pk", DataType.INT64, is_primary=True, auto_id=True, description="主键ID，自动生成")
+    schema.add_field("text", DataType.VARCHAR, max_length=65535, enable_analyzer=True, description="文本内容，用于全文检索")
+    schema.add_field("dense", DataType.FLOAT_VECTOR, dim=dense_dim, description="密集向量，用于语义检索")
+    schema.add_field("sparse", DataType.SPARSE_FLOAT_VECTOR, description="稀疏向量，由BM25函数生成")
+    
+    # 业务字段
+    schema.add_field("document_id", DataType.VARCHAR, max_length=256, description="文档ID")
+    schema.add_field("parent_id", DataType.VARCHAR, max_length=256, description="父节点ID，用于构建层级关系")
+    schema.add_field("index", DataType.INT64, description="索引序号")
+    schema.add_field("tag_list", DataType.VARCHAR, max_length=2048, description="标签列表，逗号分隔")
+    schema.add_field("permission", DataType.JSON, description="权限信息JSON")
+    schema.add_field("metadata", DataType.JSON, description="元数据JSON")
+    schema.add_field("is_deleted", DataType.BOOL, description="逻辑删除标记")
+    
+    # 审计字段
+    schema.add_field("created_by", DataType.VARCHAR, max_length=256, description="创建人")
+    schema.add_field("created_time", DataType.INT64, description="创建时间戳")
+    schema.add_field("updated_by", DataType.VARCHAR, max_length=256, description="更新人")
+    schema.add_field("updated_time", DataType.INT64, description="更新时间戳")
+
+    schema.add_function(
+        Function(
+            name="bm25_fn",
+            input_field_names=["text"],
+            output_field_names=["sparse"],
+            function_type=FunctionType.BM25,
+        )
+    )
+
+    client.create_collection(collection_name=collection_name, schema=schema)
+
+
+if __name__ == "__main__":
+    # 创建父表和子表
+    try:
+        ensure_collection(PARENT_COLLECTION_NAME, dense_dim=DENSE_DIM_DEFAULT)
+        ensure_collection(CHILD_COLLECTION_NAME, dense_dim=DENSE_DIM_DEFAULT)
+        print(f"✅ Collection 创建完成: {PARENT_COLLECTION_NAME}, {CHILD_COLLECTION_NAME}")
+    except Exception as e:
+        print(f"❌ 创建 Collection 失败, 错误信息: {e}")
+        raise

src/app/scripts/base_in_collection.py

@@ -0,0 +1,262 @@
+"""
+将 JSON 文件中的 parent 和 children 数据插入 Milvus Collection。
+读取每个子文件夹的 JSON，解析 doc、parent、children 数组并构造入库数据。
+"""
+from __future__ import annotations
+
+import json
+from datetime import datetime
+from pathlib import Path
+from typing import Any, Dict, List
+
+from pymilvus import MilvusClient
+
+from app.config.embeddings import get_embeddings
+from app.config.milvus_client import get_milvusclient
+from app.config.setting import settings
+
+# 根目录配置
+ROOT_FOLDER = r"C:\Users\ZengChao\Desktop\新建文件夹 (2)"
+
+# Collection 名称
+PARENT_COLLECTION_NAME = "test_27_parent"
+CHILD_COLLECTION_NAME = "test_27_child"
+
+# 默认创建人/修改人ID
+DEFAULT_USER_ID = "ed6a79d3-0083-4d81-8b48-fc522f686f74"
+
+# MinIO URL 前缀
+PREFIX = "sampledata/base"
+
+
+def build_metadata(doc_data: Dict[str, Any], hierarchy: str, file_url: str) -> Dict[str, Any]:
+    """
+    构造 metadata 字段。
+    
+    Args:
+        doc_data: JSON 中的 doc 数据
+        hierarchy: 文档层级信息
+        file_url: 文件 URL
+    
+    Returns:
+        metadata 字典
+    """
+    return {
+        "file_name": doc_data.get("chinese_name", ""),
+        "standard_number": doc_data.get("standard_number", ""),
+        "issuing_authority": doc_data.get("issuing_authority", ""),
+        "document_type": doc_data.get("document_type", ""),
+        "professional_field": doc_data.get("professional_field", ""),
+        "validity": doc_data.get("validity", ""),
+        "hierarchy": hierarchy,
+        "file_url": file_url,
+        "plan_type_list": {}  # 空 JSON
+    }
+
+
+def insert_parent_rows(client: MilvusClient, collection_name: str, parent_rows: List[Dict[str, Any]], 
+                       doc_data: Dict[str, Any], doc_id: str, folder_name: str) -> int:
+    """
+    插入 parent 数据到 Milvus。
+    
+    Args:
+        client: Milvus 客户端
+        collection_name: Collection 名称
+        parent_rows: parent 数组
+        doc_data: doc 数据
+        doc_id: 文档 ID
+        folder_name: 文件夹名称
+    
+    Returns:
+        插入的行数
+    """
+    if not parent_rows:
+        return 0
+    
+    # 获取 embeddings 客户端
+    embeddings = get_embeddings()
+    
+    file_url = f"{PREFIX}/{doc_id}.md"
+    now_ts = int(datetime.now().timestamp())
+    
+    # 批量提取所有文本
+    texts = [row.get("text", "") for row in parent_rows]
+    # 批量生成向量
+    vectors = embeddings.embed_documents(texts)
+    
+    entities = []
+    for idx, row in enumerate(parent_rows):
+        entity = {
+            "text": texts[idx],
+            "dense": vectors[idx],
+            "document_id": doc_id,
+            "parent_id": str(row.get("parent_id", "")),
+            "index": row.get("index", 0),
+            "tag_list": "",
+            "permission": {},
+            "metadata": build_metadata(doc_data, row.get("hierarchy", ""), file_url),
+            "is_deleted": False,
+            "created_by": DEFAULT_USER_ID,
+            "created_time": now_ts,
+            "updated_by": DEFAULT_USER_ID,
+            "updated_time": now_ts,
+        }
+        entities.append(entity)
+    
+    try:
+        client.insert(collection_name=collection_name, data=entities)
+        return len(entities)
+    except Exception as e:
+        print(f"📁 {folder_name} ❌ 插入 parent 失败: {e}")
+        return 0
+
+
+def insert_child_rows(client: MilvusClient, collection_name: str, child_rows: List[Dict[str, Any]], 
+                      doc_data: Dict[str, Any], doc_id: str, folder_name: str) -> int:
+    """
+    插入 children 数据到 Milvus。
+    
+    Args:
+        client: Milvus 客户端
+        collection_name: Collection 名称
+        child_rows: children 数组
+        doc_data: doc 数据
+        doc_id: 文档 ID
+        folder_name: 文件夹名称
+    
+    Returns:
+        插入的行数
+    """
+    if not child_rows:
+        return 0
+    
+    # 获取 embeddings 客户端
+    embeddings = get_embeddings()
+    
+    file_url = f"{PREFIX}/{doc_id}.md"
+    now_ts = int(datetime.now().timestamp())
+    
+    # 批量提取所有文本
+    texts = [row.get("text", "") for row in child_rows]
+    # 批量生成向量
+    vectors = embeddings.embed_documents(texts)
+    
+    entities = []
+    for idx, row in enumerate(child_rows):
+        entity = {
+            "text": texts[idx],
+            "dense": vectors[idx],
+            "document_id": doc_id,
+            "parent_id": str(row.get("parent_id", "")),
+            "index": row.get("index", 0),
+            "tag_list": "",
+            "permission": {},
+            "metadata": build_metadata(doc_data, row.get("hierarchy", ""), file_url),
+            "is_deleted": False,
+            "created_by": DEFAULT_USER_ID,
+            "created_time": now_ts,
+            "updated_by": DEFAULT_USER_ID,
+            "updated_time": now_ts,
+        }
+        entities.append(entity)
+    
+    try:
+        client.insert(collection_name=collection_name, data=entities)
+        return len(entities)
+    except Exception as e:
+        print(f"📁 {folder_name} ❌ 插入 children 失败: {e}")
+        return 0
+
+
+def process_folder(root_folder: str | Path) -> Dict[str, int]:
+    """
+    处理文件夹结构，导入 Milvus。
+    
+    Args:
+        root_folder: 根目录路径
+    
+    Returns:
+        统计信息字典
+    """
+    root_folder = Path(root_folder)
+    if not root_folder.is_dir():
+        raise NotADirectoryError(f"不是有效的文件夹: {root_folder}")
+    
+    client = get_milvusclient()
+    
+    stats = {"success": 0, "failed": 0, "skipped": 0, "parent_rows": 0, "child_rows": 0}
+    
+    for subfolder in sorted(root_folder.iterdir()):
+        if not subfolder.is_dir():
+            continue
+        
+        folder_name = subfolder.name
+        
+        # 查找 JSON 文件
+        json_files = list(subfolder.glob("*.json"))
+        if not json_files:
+            print(f"📁 {folder_name} ⊘ 无JSON文件")
+            stats["skipped"] += 1
+            continue
+        
+        json_path = json_files[0]
+        
+        try:
+            # 读取 JSON
+            with open(json_path, "r", encoding="utf-8") as f:
+                data = json.load(f)
+            
+            doc_data = data.get("doc")
+            parent_rows = data.get("parent", [])
+            child_rows = data.get("children", [])
+            
+            if not doc_data or not doc_data.get("id"):
+                print(f"📁 {folder_name} ❌ JSON格式错误或缺少doc/id")
+                stats["failed"] += 1
+                continue
+            
+            doc_id = doc_data.get("id")
+            
+            # 插入 parent 和 children
+            parent_count = insert_parent_rows(client, PARENT_COLLECTION_NAME, parent_rows, doc_data, doc_id, folder_name)
+            child_count = insert_child_rows(client, CHILD_COLLECTION_NAME, child_rows, doc_data, doc_id, folder_name)
+            
+            if parent_count > 0 or child_count > 0:
+                print(f"📁 {folder_name} ✅ parent: {parent_count}, child: {child_count}")
+                stats["success"] += 1
+                stats["parent_rows"] += parent_count
+                stats["child_rows"] += child_count
+            else:
+                print(f"📁 {folder_name} ⊘ 无数据入库")
+                stats["skipped"] += 1
+                
+        except Exception as e:
+            print(f"📁 {folder_name} ❌ {str(e)}")
+            stats["failed"] += 1
+    
+    return stats
+
+
+def main():
+    """主函数"""
+    try:
+        print(f"🔍 开始导入 Milvus...")
+        print(f"📂 根目录: {ROOT_FOLDER}")
+        print(f"🔗 Milvus: {settings.MILVUS_HOST}:{settings.MILVUS_PORT}")
+        print(f"📊 Parent Collection: {PARENT_COLLECTION_NAME}")
+        print(f"📊 Child Collection: {CHILD_COLLECTION_NAME}")
+        print("-" * 60)
+        
+        stats = process_folder(ROOT_FOLDER)
+        
+        print("\n" + "=" * 60)
+        print(f"✅ 成功: {stats['success']} | ❌ 失败: {stats['failed']} | ⊘ 跳过: {stats['skipped']}")
+        print(f"📊 Parent 行数: {stats['parent_rows']} | Child 行数: {stats['child_rows']}")
+        print("=" * 60)
+        
+    except Exception as e:
+        print(f"❌ 错误: {str(e)}")
+
+
+if __name__ == "__main__":
+    main()

src/app/scripts/base_in_minio.py

@@ -0,0 +1,116 @@
+"""
+将每个子文件夹中的原始文件、JSON、MD 上传至 MinIO。
+上传路径规则（object_name）：
+- 原始文件: /base/{id}{原始扩展名}
+- Markdown : /base/{id}.md
+- JSON     : /base/{id}.json
+"""
+from __future__ import annotations
+
+import json
+from pathlib import Path
+from typing import Tuple
+
+from minio.error import S3Error
+
+from app.config.minio_client import get_minio_client
+from app.config.setting import settings
+
+# 目标路径前缀
+PREFIX = "sampledata/base"
+
+# 根目录配置：每个子文件夹包含 1 个原始文件 + 1 个 .md + 1 个 .json
+ROOT_FOLDER = r"C:\Users\ZengChao\Desktop\新建文件夹"
+
+
+def find_files(subfolder: Path) -> Tuple[Path, Path, Path]:
+    """返回 (original_file, md_file, json_file)，找不到则抛异常。"""
+    json_files = list(subfolder.glob("*.json"))
+    if not json_files:
+        raise FileNotFoundError("未找到 json 文件")
+    json_file = json_files[0]
+
+    md_files = list(subfolder.glob("*.md"))
+    if not md_files:
+        raise FileNotFoundError("未找到 md 文件")
+    md_file = md_files[0]
+
+    original_file = None
+    for f in subfolder.iterdir():
+        if f.is_file() and f.suffix not in {".json", ".md"}:
+            original_file = f
+            break
+    if original_file is None:
+        raise FileNotFoundError("未找到原始文件")
+
+    return original_file, md_file, json_file
+
+
+def upload_file(client, bucket: str, object_name: str, file_path: Path) -> None:
+    """上传文件到 MinIO，使用 put_object。"""
+    with file_path.open("rb") as fp:
+        result=client.put_object(
+            bucket_name=bucket,
+            object_name=object_name,
+            data=fp,
+            length=file_path.stat().st_size,
+        )
+    # print(f"    ✅ 上传成功: {result.object_name} (源文件: {file_path.name})")
+
+
+def main() -> None:
+    root = Path(ROOT_FOLDER)
+    if not root.is_dir():
+        raise NotADirectoryError(f"不是有效的目录: {root}")
+
+    client = get_minio_client()
+    bucket = settings.MINIO_BUCKET_NAME
+
+    # 确保桶存在
+    if not client.bucket_exists(bucket):
+        client.make_bucket(bucket)
+
+    stats = {"success": 0, "failed": 0, "skipped": 0}
+
+    for subfolder in sorted(root.iterdir()):
+        if not subfolder.is_dir():
+            continue
+        folder_name = subfolder.name
+        try:
+            original_file, md_file, json_file = find_files(subfolder)
+
+            with open(json_file, "r", encoding="utf-8") as f:
+                data = json.load(f)
+            doc = data.get("doc") or {}
+            doc_id = doc.get("id")
+            if not doc_id:
+                raise ValueError("JSON 中缺少 doc.id")
+
+            # 目标路径：/桶名/sampledata/base/...
+            file_obj = f"{PREFIX}/{doc_id}{original_file.suffix}"
+            md_obj = f"{PREFIX}/{doc_id}.md"
+            json_obj = f"{PREFIX}/{doc_id}.json"
+
+            upload_file(client, bucket, file_obj, original_file)
+            upload_file(client, bucket, md_obj, md_file)
+            upload_file(client, bucket, json_obj, json_file)
+
+            print(f"📁 {folder_name} ✅ 已上传: {file_obj}, {md_obj}, {json_obj}")
+            stats["success"] += 1
+        except (FileNotFoundError, ValueError) as e:
+            print(f"📁 {folder_name} ⊘ {e}")
+            stats["skipped"] += 1
+        except S3Error as e:
+            print(f"📁 {folder_name} ❌ MinIO 错误: {e}")
+            stats["failed"] += 1
+        except Exception as e:
+            print(f"📁 {folder_name} ❌ {e}")
+            stats["failed"] += 1
+
+    print("\n" + "=" * 60)
+    print(f"✅ 成功: {stats['success']} | ❌ 失败: {stats['failed']} | ⊘ 跳过: {stats['skipped']}")
+    print("=" * 60)
+
+
+if __name__ == "__main__":
+    main()

src/app/scripts/base_info_in_database.py

@@ -0,0 +1,290 @@
+"""
+将JSON文件中的文档信息导入数据库
+读取文件夹下的JSON文件，填充 t_samp_document_main 和 t_samp_standard_base_info 两张表
+"""
+from __future__ import annotations
+
+import asyncio
+import json
+from datetime import datetime
+from pathlib import Path
+from typing import Any, Dict, Optional
+
+from sqlalchemy import text
+
+from app.config.database import get_async_sessionmaker, get_async_engine
+from app.config.setting import settings
+
+
+# 默认创建人/修改人ID
+DEFAULT_USER_ID = "ed6a79d3-0083-4d81-8b48-fc522f686f74"
+
+# 根目录配置
+ROOT_FOLDER = r"C:\Users\ZengChao\Desktop\新建文件夹"
+
+
+def parse_date(date_str: Optional[str]) -> Optional[str]:
+    """解析日期字符串为数据库格式"""
+    if not date_str:
+        return None
+    try:
+        # 如果已经是 YYYY-MM-DD 格式，直接返回
+        if isinstance(date_str, str) and len(date_str) == 10:
+            return date_str
+        return None
+    except Exception:
+        return None
+
+
+async def insert_document_main(session, doc_data: Dict[str, Any], title: str, file_extension: str, file_url: str, md_url: str, json_url: str, folder_name: str = "") -> bool:
+    """
+    插入文档主表 t_samp_document_main
+    
+    Args:
+        session: 数据库会话
+        doc_data: JSON中的doc数据
+        title: 文档标题（原始文件名）
+        file_extension: 文件扩展名
+        file_url: 原始文件URL
+        md_url: Markdown文件URL
+        json_url: JSON文件URL
+        folder_name: 文件夹名称，用于错误打印
+    
+    Returns:
+        是否插入成功
+    """
+    try:
+        doc_id = doc_data.get("id")
+        
+        sql = text("""
+            INSERT INTO t_samp_document_main (
+                id, title, conversion_status, whether_to_enter,
+                file_url, md_url, json_url, file_extension,
+                created_by, created_time, updated_by, updated_time,
+                source_type
+            ) VALUES (
+                :id, :title, :conversion_status, :whether_to_enter,
+                :file_url, :md_url, :json_url, :file_extension,
+                :created_by, :created_time, :updated_by, :updated_time,
+                :source_type
+            )
+        """)
+        
+        await session.execute(sql, {
+            "id": doc_id,
+            "title": title,
+            "conversion_status": 2,  # 2-完成
+            "whether_to_enter": 0,   # 0-未入库
+            "file_url": file_url,
+            "md_url": md_url,
+            "json_url": json_url,
+            "file_extension": file_extension,
+            "created_by": DEFAULT_USER_ID,
+            "created_time": datetime.now(),
+            "updated_by": DEFAULT_USER_ID,
+            "updated_time": datetime.now(),
+            "source_type": "basis",
+        })
+        
+        return True
+    except Exception as e:
+        print(f"📁 {folder_name} ❌ 插入主表失败: {e}")
+        return False
+
+
+async def insert_standard_base_info(session, doc_data: Dict[str, Any], folder_name: str = "") -> bool:
+    """
+    插入标准基础信息表 t_samp_standard_base_info
+    
+    Args:
+        session: 数据库会话
+        doc_data: JSON中的doc数据
+        folder_name: 文件夹名称，用于错误打印
+    
+    Returns:
+        是否插入成功
+    """
+    try:
+        doc_id = doc_data.get("id")
+        
+        # 处理 drafting_unit：按 、 分隔，第一个为主编单位，其余为参编单位
+        drafting_unit_raw = doc_data.get("drafting_unit", "") or ""
+        if drafting_unit_raw:
+            units = [u.strip() for u in drafting_unit_raw.split("、") if u.strip()]
+            drafting_unit = units[0] if units else None
+            participating_units = "、".join(units[1:]) if len(units) > 1 else None
+        else:
+            drafting_unit = None
+            participating_units = None
+        
+        sql = text("""
+            INSERT INTO t_samp_standard_base_info (
+                id, chinese_name, english_name, standard_number,
+                issuing_authority, release_date, implementation_date,
+                drafting_unit, approving_department, participating_units,
+                document_type, professional_field, engineering_phase, validity,
+                reference_basis, source_url,
+                created_by, created_time, updated_by, updated_time
+            ) VALUES (
+                :id, :chinese_name, :english_name, :standard_number,
+                :issuing_authority, :release_date, :implementation_date,
+                :drafting_unit, :approving_department, :participating_units,
+                :document_type, :professional_field, :engineering_phase, :validity,
+                :reference_basis, :source_url,
+                :created_by, :created_time, :updated_by, :updated_time
+            )
+        """)
+        
+        await session.execute(sql, {
+            "id": doc_id,
+            "chinese_name": doc_data.get("chinese_name"),
+            "english_name": doc_data.get("english_name"),
+            "standard_number": doc_data.get("standard_number"),
+            "issuing_authority": doc_data.get("issuing_authority"),
+            "release_date": parse_date(doc_data.get("release_date")),
+            "implementation_date": parse_date(doc_data.get("implementation_date")),
+            "drafting_unit": drafting_unit,
+            "approving_department": doc_data.get("approving_department"),
+            "participating_units": participating_units,
+            "document_type": doc_data.get("document_type"),
+            "professional_field": doc_data.get("professional_field"),
+            "engineering_phase": doc_data.get("engineering_phase"),
+            "validity": doc_data.get("validity"),
+            "reference_basis": doc_data.get("reference_basis"),
+            "source_url": doc_data.get("source_url"),
+            "created_by": DEFAULT_USER_ID,
+            "created_time": datetime.now(),
+            "updated_by": DEFAULT_USER_ID,
+            "updated_time": datetime.now(),
+        })
+        
+        return True
+    except Exception as e:
+        print(f"📁 {folder_name} ❌ 插入基础信息表失败: {e}")
+        return False
+
+
+async def process_folder(root_folder: str | Path) -> Dict[str, int]:
+    """
+    处理文件夹结构，导入数据库
+    
+    Args:
+        root_folder: 根目录路径
+    
+    Returns:
+        统计信息字典
+    """
+    root_folder = Path(root_folder)
+    if not root_folder.is_dir():
+        raise NotADirectoryError(f"不是有效的文件夹: {root_folder}")
+    
+    SessionMaker = get_async_sessionmaker()
+    
+    stats = {"success": 0, "failed": 0, "skipped": 0}
+    
+    # 遍历子文件夹
+    for subfolder in sorted(root_folder.iterdir()):
+        if not subfolder.is_dir():
+            continue
+        
+        folder_name = subfolder.name
+        
+        # 查找JSON文件
+        json_files = list(subfolder.glob("*.json"))
+        if not json_files:
+            print(f"📁 {folder_name} ⊘ (无JSON文件)")
+            stats["skipped"] += 1
+            continue
+        
+        json_path = json_files[0]
+        
+        try:
+            # 读取JSON
+            with open(json_path, "r", encoding="utf-8") as f:
+                data = json.load(f)
+            
+            doc_data = data.get("doc")
+            if not doc_data or not doc_data.get("id"):
+                print(f"📁 {folder_name} ❌ (JSON格式错误或缺少doc/id)")
+                stats["failed"] += 1
+                continue
+            
+            doc_id = doc_data.get("id")
+            
+            # 查找原始文件（非 .json 和 .md 的文件）
+            all_files = list(subfolder.glob("*"))
+            original_file = None
+            for f in all_files:
+                if f.is_file() and f.suffix not in [".json", ".md"]:
+                    original_file = f
+                    break
+            
+            if not original_file:
+                print(f"📁 {folder_name} ❌ (未找到原始文件)")
+                stats["failed"] += 1
+                continue
+            
+            # 获取文件信息
+            title = original_file.stem  # 文件名（不含扩展名）
+            file_extension = original_file.suffix  # 扩展名（含点）
+            
+            # 构造 URL
+            file_url = f"/base/{doc_id}{file_extension}"
+            md_url = f"/base/{doc_id}.md"
+            json_url = f"/base/{doc_id}.json"
+            
+            # 插入数据库
+            async with SessionMaker() as session:
+                try:
+                    # 先插入主表
+                    if not await insert_document_main(session, doc_data, title, file_extension, file_url, md_url, json_url, folder_name):
+                        await session.rollback()
+                        stats["failed"] += 1
+                        continue
+                    
+                    # 再插入基础信息表
+                    if not await insert_standard_base_info(session, doc_data, folder_name):
+                        await session.rollback()
+                        stats["failed"] += 1
+                        continue
+                    
+                    await session.commit()
+                    print(f"📁 {folder_name} ✅")
+                    stats["success"] += 1
+                    
+                except Exception as e:
+                    await session.rollback()
+                    print(f"📁 {folder_name} ❌ ({str(e)})")
+                    stats["failed"] += 1
+                
+        except Exception as e:
+            print(f"📁 {folder_name} ❌ ({str(e)})")
+            stats["failed"] += 1
+    
+    return stats
+
+
+async def main():
+    """主函数"""
+    try:
+        print(f"🔍 开始导入数据库...")
+        print(f"📂 根目录: {ROOT_FOLDER}")
+        print(f"🔗 数据库: {settings.DATABASE_URL}")
+        print("-" * 60)
+        
+        stats = await process_folder(ROOT_FOLDER)
+        
+        print("\n" + "=" * 60)
+        print(f"✅ 成功: {stats['success']} | ❌ 失败: {stats['failed']} | ⊘ 跳过: {stats['skipped']}")
+        print("=" * 60)
+        
+    except Exception as e:
+        print(f"❌ 错误: {str(e)}")
+    finally:
+        # 关闭数据库引擎，避免事件循环关闭警告
+        engine = get_async_engine()
+        await engine.dispose()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

src/app/scripts/base_info_json_generation.py

@@ -0,0 +1,397 @@
+"""
+根据Excel和文件夹编号生成StandardBaseInfo信息并保存为JSON。
+并在同一个JSON里补充 md 切分结果（parent / children），每条只保留：
+- parent_id
+- index
+- hierarchy
+- text
+"""
+from __future__ import annotations
+
+import json
+import re
+import uuid
+import hashlib
+from datetime import datetime
+from pathlib import Path
+from typing import Any, Optional, List, Dict, Tuple
+
+import pandas as pd
+
+from app.models import StandardBaseInfo  # noqa: F401  # 仅用于类型/一致性，脚本不强依赖
+
+
+# ==================== 配置参数 ====================
+EXCEL_FILE = r"C:\Users\ZengChao\Desktop\id.xlsx"      # ✅ Excel文件路径
+ROOT_FOLDER = r"C:\Users\ZengChao\Desktop\新建文件夹"   # ✅ 根文件夹路径
+SHEET_INDEX = 0                                        # 目标sheet索引（0为第一个sheet）
+
+PARENT_MAX_CHARS = 6000                                # ✅ 父段最大长度（超长切片）
+CHILD_INDEX_START = 0                                  # ✅ children.index 起始
+# ================================================
+
+
+# ====================
+# Markdown 切分逻辑（按你之前的逻辑抽出来）
+# ====================
+
+BLANK_SPLIT_RE = re.compile(r"\n\s*\n+")
+H1_RE = re.compile(r"^#\s+(.+?)\s*$", re.MULTILINE)
+
+
+def split_md_by_blank_lines(md: str) -> List[str]:
+    md = md.replace("\r\n", "\n").replace("\r", "\n")
+    parts = BLANK_SPLIT_RE.split(md)
+    return [p.strip() for p in parts if p.strip()]
+
+
+def is_heading_chunk(chunk: str):
+    first_line = chunk.split("\n", 1)[0].strip()
+    m = re.match(r"^(#{1,6})\s+(.+?)\s*$", first_line)
+    if not m:
+        return None
+    return len(m.group(1)), m.group(2).strip()
+
+
+def outline_path_str(path: List[str]) -> str:
+    return " > ".join(path)
+
+
+def guess_doc_name_from_filename(file_name: str) -> str:
+    return Path(file_name).stem
+
+
+def split_md_by_h1_sections(md: str) -> List[Tuple[str, str]]:
+    """
+    按 '# 一级标题' 切成父段：
+    return: [(h1_title, section_text), ...]
+    - 如果最开始有内容（第一个#之前），将其作为 "__PREAMBLE__" 段
+    - section_text 包含该 # 行本身 + 直到下一个 # 之前的所有内容
+    - 如果全文没有任何 #，则返回一个默认段 ("__NO_H1__", 全文)
+    """
+    md = md.replace("\r\n", "\n").replace("\r", "\n")
+    matches = list(H1_RE.finditer(md))
+    if not matches:
+        txt = md.strip()
+        if not txt:
+            return []
+        return [("__NO_H1__", txt)]
+
+    sections: List[Tuple[str, str]] = []
+
+    first_match_start = matches[0].start()
+    preamble = md[:first_match_start].strip()
+    if preamble:
+        sections.append(("__PREAMBLE__", preamble))
+
+    for i, m in enumerate(matches):
+        title = m.group(1).strip()
+        start = m.start()
+        end = matches[i + 1].start() if i + 1 < len(matches) else len(md)
+        sec = md[start:end].strip()
+        if sec:
+            sections.append((title, sec))
+    return sections
+
+
+def make_parent_id(doc_name: str, h1_title: str, parent_seq: int) -> int:
+    """
+    生成稳定 parent_id（父段组ID）
+    同一个 # 一级标题段无论父表切成几条记录，都共享同一个 parent_id
+    """
+    raw = f"{doc_name}|{parent_seq}|{h1_title}".encode("utf-8")
+    return int(hashlib.sha1(raw).hexdigest()[:16], 16) & ((1 << 63) - 1)
+
+
+def split_text_by_max_chars(text: str, max_chars: int) -> List[str]:
+    """
+    父段过长时切片：
+    - 优先在最大长度附近的空行边界切割（用按空行拆分再拼接的方式实现）
+    - 单个段落超过max_chars时才硬切
+    """
+    text = (text or "").strip()
+    if not text:
+        return []
+    if len(text) <= max_chars:
+        return [text]
+
+    chunks = split_md_by_blank_lines(text)
+    result: List[str] = []
+    current_slice = ""
+
+    for chunk in chunks:
+        if len(chunk) > max_chars:
+            if current_slice.strip():
+                result.append(current_slice.strip())
+                current_slice = ""
+            start = 0
+            while start < len(chunk):
+                result.append(chunk[start:start + max_chars].strip())
+                start += max_chars
+        else:
+            test_slice = current_slice + "\n\n" + chunk if current_slice else chunk
+            if len(test_slice) <= max_chars:
+                current_slice = test_slice
+            else:
+                if current_slice.strip():
+                    result.append(current_slice.strip())
+                current_slice = chunk
+
+    if current_slice.strip():
+        result.append(current_slice.strip())
+
+    return [s for s in result if s]
+
+
+def build_parent_and_children_rows(
+    md_text: str,
+    file_name: str,
+    parent_max_chars: int = PARENT_MAX_CHARS,
+    child_index_start: int = CHILD_INDEX_START,
+) -> Tuple[List[Dict[str, Any]], List[Dict[str, Any]]]:
+    """
+    输出你最终要的极简结构：
+    parent:   [{parent_id,index,hierarchy,text}, ...]
+    children: [{parent_id,index,hierarchy,text}, ...]
+    """
+    doc_name = guess_doc_name_from_filename(file_name)
+
+    # 1) 父段：按 H1
+    parent_sections = split_md_by_h1_sections(md_text)
+
+    # parent_id stable mapping
+    parent_seq_to_parent_id: Dict[int, int] = {}
+    for parent_seq, (h1_title, _sec_text) in enumerate(parent_sections):
+        parent_seq_to_parent_id[parent_seq] = make_parent_id(
+            doc_name=doc_name,
+            h1_title=h1_title,
+            parent_seq=parent_seq,
+        )
+
+    # 2) children：在各父段内部按空行切，并维护 hierarchy（outline_path）
+    children: List[Dict[str, Any]] = []
+    child_index = child_index_start
+
+    for parent_seq, (_h1_title, sec_text) in enumerate(parent_sections):
+        parent_id = parent_seq_to_parent_id[parent_seq]
+
+        chunks = split_md_by_blank_lines(sec_text)
+        heading_path: List[str] = []
+
+        for chunk in chunks:
+            heading_info = is_heading_chunk(chunk)
+            if heading_info:
+                level, title = heading_info
+                parent_path = heading_path[: level - 1]
+                hierarchy = outline_path_str(parent_path)
+                heading_path = parent_path + [title]
+            else:
+                hierarchy = outline_path_str(heading_path)
+
+            children.append(
+                {
+                    "index": child_index,
+                    "parent_id": int(parent_id),
+                    "hierarchy": hierarchy,
+                    "text": chunk,
+                }
+            )
+            child_index += 1
+
+    # 3) parents：父段过长按 max_chars 切片，但 parent_id 不变
+    parents: List[Dict[str, Any]] = []
+    parent_row_index = 0  # 这里用“父表行顺序index”，保证唯一、可追溯
+
+    for parent_seq, (h1_title, sec_text) in enumerate(parent_sections):
+        parent_id = parent_seq_to_parent_id[parent_seq]
+
+        slices = split_text_by_max_chars(sec_text, parent_max_chars)
+        # hierarchy：父表层级（你之前逻辑）
+        if h1_title == "__PREAMBLE__":
+            hierarchy = doc_name
+        elif h1_title == "__NO_H1__":
+            hierarchy = ""
+        else:
+            hierarchy = h1_title
+
+        for _slice_idx, slice_text in enumerate(slices):
+            parents.append(
+                {
+                    "index": parent_row_index,
+                    "parent_id": int(parent_id),
+                    "hierarchy": hierarchy,
+                    "text": slice_text,
+                }
+            )
+            parent_row_index += 1
+
+    return parents, children
+
+
+# ====================
+# 主业务：Excel + 文件夹遍历
+# ====================
+
+class StandardInfoGenerator:
+    """从Excel生成标准信息的生成器类。"""
+
+    COLUMN_MAPPING = {
+        "编号": "standard_number",
+        "中文名": "chinese_name",
+        "英文名": "english_name",
+        "文件类型": "document_type",
+        "专业领域": "professional_field",
+        "状态": "validity",
+        "发布单位": "issuing_authority",
+        "发布时间": "release_date",
+        "实施日期": "implementation_date",
+        "文件来源网站": "source_url",
+        "起草单位": "drafting_unit",
+        "批准部门": "approving_department",
+        "工程阶段": "engineering_phase",
+        "参考依据": "reference_basis",
+    }
+
+    def __init__(self, excel_path: str | Path, sheet_index: int = 2):
+        self.excel_path = Path(excel_path)
+        self.sheet_index = sheet_index
+        self._load_excel()
+
+    def _load_excel(self) -> None:
+        if not self.excel_path.exists():
+            raise FileNotFoundError(f"Excel文件不存在: {self.excel_path}")
+
+        self.df = pd.read_excel(self.excel_path, sheet_name=self.sheet_index)
+        print(f"✅ 已加载Excel文件: {self.excel_path}，共{len(self.df)}行数据。")
+        self.df.set_index("id", inplace=True, drop=False)
+
+    def _parse_date(self, value: Any) -> Optional[str]:
+        if pd.isna(value):
+            return None
+
+        if isinstance(value, str) and value.strip():
+            try:
+                parsed = pd.to_datetime(value)
+                return parsed.strftime("%Y-%m-%d")
+            except Exception:
+                return None
+
+        if hasattr(value, "strftime"):
+            return value.strftime("%Y-%m-%d")
+
+        return None
+
+    def get_standard_info_by_code(self, code: str) -> Optional[dict[str, Any]]:
+        try:
+            code_str = str(code).strip()
+            df_with_str_id = self.df.copy()
+            df_with_str_id.index = df_with_str_id.index.astype(str).str.strip()
+            row = df_with_str_id.loc[code_str]
+        except KeyError:
+            return None
+
+        if hasattr(row, "to_dict"):
+            row_dict = row.to_dict()
+        else:
+            row_dict = row.to_frame().T.iloc[0].to_dict()
+
+        result: Dict[str, Any] = {
+            "id": str(uuid.uuid4()),
+        }
+
+        for excel_col, model_field in self.COLUMN_MAPPING.items():
+            if excel_col in row_dict:
+                value = row_dict[excel_col]
+
+                if model_field in ("release_date", "implementation_date"):
+                    value = self._parse_date(value)
+                elif pd.isna(value):
+                    value = None
+                elif isinstance(value, str):
+                    value = value.strip() if value else None
+
+                result[model_field] = value
+
+        return result
+
+    def process_folder_structure(self, root_folder: str | Path) -> dict[str, list[str]]:
+        root_folder = Path(root_folder)
+        if not root_folder.is_dir():
+            raise NotADirectoryError(f"不是有效的文件夹: {root_folder}")
+
+        results = {"success": [], "failed": [], "skipped": []}
+
+        for subfolder in sorted(root_folder.iterdir()):
+            if not subfolder.is_dir():
+                continue
+
+            folder_name = subfolder.name
+            standard_info = self.get_standard_info_by_code(folder_name)
+
+            if standard_info is None:
+                print(f"📄 {folder_name} ❌ (id未在Excel中找到)")
+                results["skipped"].append(folder_name)
+                continue
+
+            try:
+                md_files = list(subfolder.glob("*.md"))
+                if not md_files:
+                    print(f"📄 {folder_name} ❌ (文件夹中无.md文件)")
+                    results["skipped"].append(folder_name)
+                    continue
+
+                md_path = md_files[0]
+                output_path = md_path.with_suffix(".json")
+
+                with open(md_path, "r", encoding="utf-8") as f:
+                    md_text = f.read()
+
+                parents, children = build_parent_and_children_rows(
+                    md_text=md_text,
+                    file_name=md_path.name,
+                    parent_max_chars=PARENT_MAX_CHARS,
+                    child_index_start=CHILD_INDEX_START,
+                )
+
+                # doc 节点：放“全局信息”（你要的“各种信息”）
+                info_to_save = {
+                    k: v.isoformat() if isinstance(v, datetime) else v
+                    for k, v in standard_info.items()
+                }
+
+                out_json = {
+                    "doc": {
+                        # 你自己的标准信息（各种信息）
+                        **info_to_save,
+                    },
+                    "parent": parents,
+                    "children": children,
+                }
+
+                with open(output_path, "w", encoding="utf-8") as f:
+                    json.dump(out_json, f, ensure_ascii=False, indent=2)
+
+                print(f"📄 {folder_name} ✅ (已生成: {output_path.name})")
+                results["success"].append(folder_name)
+
+            except Exception as e:
+                print(f"📄 {folder_name} ❌ ({str(e)})")
+                results["failed"].append(f"{folder_name} ({str(e)})")
+
+        return results
+
+
+def main():
+    try:
+        generator = StandardInfoGenerator(EXCEL_FILE, sheet_index=SHEET_INDEX)
+        results = generator.process_folder_structure(ROOT_FOLDER)
+
+        print("\n" + "=" * 60)
+        print(f"✅ 成功: {len(results['success'])} | ❌ 失败: {len(results['failed'])} | ⊘ 跳过: {len(results['skipped'])}")
+        print("=" * 60)
+    except Exception as e:
+        print(f"❌ 错误: {str(e)}")
+
+
+if __name__ == "__main__":
+    main()

src/app/scripts/based_on_json_generation.py

@@ -1,222 +0,0 @@
-"""根据Excel和文件夹编号生成StandardBaseInfo信息并保存为JSON。"""
-from __future__ import annotations
-
-import json
-import uuid
-from datetime import datetime
-from pathlib import Path
-from typing import Any, Optional
-
-import pandas as pd
-
-from app.models import StandardBaseInfo
-
-
-# ==================== 配置参数 ====================
-# 修改这些参数以配置脚本行为
-EXCEL_FILE = r"C:\Users\ZengChao\Desktop\id.xlsx"  # ✅ Excel文件路径
-ROOT_FOLDER = r"C:\Users\ZengChao\Desktop\新建文件夹"               # ✅ 根文件夹路径
-SHEET_INDEX = 0  # 目标sheet索引（0为第一个sheet）
-# ================================================
-
-
-class StandardInfoGenerator:
-    """从Excel生成标准信息的生成器类。"""
-
-    # Excel第三个sheet列名映射到StandardBaseInfo字段
-    COLUMN_MAPPING = {
-        "编号": "standard_number",
-        "中文名": "chinese_name",
-        "英文名": "english_name",
-        "文件类型": "document_type",
-        "专业领域": "professional_field",
-        "状态": "validity",
-        "发布单位": "issuing_authority",
-        "发布时间": "release_date",
-        "实施日期": "implementation_date",
-        "文件来源网站": "source_url",
-        "起草单位": "drafting_unit",
-        "批准部门": "approving_department",
-        "工程阶段": "engineering_phase",
-        "参考依据": "reference_basis",
-        "录入人": "created_by",
-    }
-
-    def __init__(self, excel_path: str | Path, sheet_index: int = 2):
-        """
-        初始化生成器。
-        
-        Args:
-            excel_path: Excel文件路径
-            sheet_index: 目标sheet索引（0为第一个sheet，默认2为第三个）
-        """
-        self.excel_path = Path(excel_path)
-        self.sheet_index = sheet_index
-        self._load_excel()
-
-    def _load_excel(self) -> None:
-        """加载Excel文件第三个sheet。"""
-        if not self.excel_path.exists():
-            raise FileNotFoundError(f"Excel文件不存在: {self.excel_path}")
-
-        self.df = pd.read_excel(self.excel_path, sheet_name=self.sheet_index)
-        print(f"✅ 已加载Excel文件: {self.excel_path}，共{len(self.df)}行数据。")
-        print(self.df)
-        # 将id列设为索引便于查找
-        self.df.set_index("id", inplace=True, drop=False)
-
-    def _parse_date(self, value: Any) -> Optional[str]:
-        """
-        解析日期值为ISO格式字符串。
-        
-        Args:
-            value: 日期值（可能是字符串、日期对象等）
-            
-        Returns:
-            ISO格式的日期字符串或None
-        """
-        if pd.isna(value):
-            return None
-        
-        if isinstance(value, str) and value.strip():
-            try:
-                # 尝试解析 YYYY/MM/DD 格式
-                parsed = pd.to_datetime(value)
-                return parsed.strftime("%Y-%m-%d")
-            except Exception:
-                return None
-        
-        if hasattr(value, "strftime"):  # datetime/date对象
-            return value.strftime("%Y-%m-%d")
-        
-        return None
-
-    def get_standard_info_by_code(self, code: str) -> Optional[dict[str, Any]]:
-        """
-        根据id查询Excel中的标准信息。
-        
-        Args:
-            code: 文件夹名（对应id列）
-            
-        Returns:
-            StandardBaseInfo字典或None（未找到时）
-        """
-        try:
-            # 将DataFrame的id列转换为字符串，然后查找匹配项
-            code_str = str(code).strip()
-            df_with_str_id = self.df.copy()
-            df_with_str_id.index = df_with_str_id.index.astype(str).str.strip()
-            row = df_with_str_id.loc[code_str]
-        except KeyError:
-            return None
-
-        # 转字典处理缺失值
-        if hasattr(row, "to_dict"):
-            row_dict = row.to_dict()
-        else:
-            row_dict = row.to_frame().T.iloc[0].to_dict()
-
-        # 映射列到StandardBaseInfo字段
-        result = {
-            "id": str(uuid.uuid4()),  # 生成新的UUID作为主键
-            "created_time": datetime.now(),
-        }
-
-        for excel_col, model_field in self.COLUMN_MAPPING.items():
-            if excel_col in row_dict:
-                value = row_dict[excel_col]
-                
-                # 处理日期字段
-                if model_field in ("release_date", "implementation_date"):
-                    value = self._parse_date(value)
-                # 处理空值
-                elif pd.isna(value):
-                    value = None
-                # 处理字符串并去除空白
-                elif isinstance(value, str):
-                    value = value.strip() if value else None
-                
-                result[model_field] = value
-
-        return result
-
-    def process_folder_structure(
-        self,
-        root_folder: str | Path
-    ) -> dict[str, list[str]]:
-        """
-        遍历根文件夹，根据文件夹名（编号）生成JSON文件。
-        
-        Args:
-            root_folder: 根文件夹路径
-            
-        Returns:
-            处理结果统计字典
-        """
-        root_folder = Path(root_folder)
-        if not root_folder.is_dir():
-            raise NotADirectoryError(f"不是有效的文件夹: {root_folder}")
-
-        results = {"success": [], "failed": [], "skipped": []}
-
-        # 遍历根文件夹下的所有子文件夹
-        for subfolder in sorted(root_folder.iterdir()):
-            if not subfolder.is_dir():
-                continue
-
-            folder_name = subfolder.name
-            
-            # 尝试将文件夹名（id）作为编号查询
-            standard_info = self.get_standard_info_by_code(folder_name)
-
-            if standard_info is None:
-                print(f"📄 {folder_name} ❌ (id未在Excel中找到)")
-                results["skipped"].append(folder_name)
-                continue
-
-            try:
-                # 查找md文件
-                md_files = list(subfolder.glob("*.md"))
-                
-                if not md_files:
-                    print(f"📄 {folder_name} ❌ (文件夹中无.md文件)")
-                    results["skipped"].append(folder_name)
-                    continue
-                
-                # 使用找到的md文件名（替换扩展名为.json）
-                output_path = md_files[0].with_suffix(".json")
-                
-                # 将datetime对象转换为字符串
-                info_to_save = {
-                    k: v.isoformat() if isinstance(v, datetime) else v
-                    for k, v in standard_info.items()
-                }
-                
-                with open(output_path, "w", encoding="utf-8") as f:
-                    json.dump(info_to_save, f, ensure_ascii=False, indent=2)
-
-                print(f"📄 {folder_name} ✅")
-                results["success"].append(folder_name)
-            except Exception as e:
-                print(f"📄 {folder_name} ❌ ({str(e)})")
-                results["failed"].append(f"{folder_name} ({str(e)})")
-
-        return results
-
-
-def main():
-    """主函数：处理文件夹结构并生成JSON。"""
-    try:
-        generator = StandardInfoGenerator(EXCEL_FILE, sheet_index=SHEET_INDEX)
-        results = generator.process_folder_structure(ROOT_FOLDER)
-        
-        # 打印统计结果
-        print("\n" + "=" * 60)
-        print(f"✅ 成功: {len(results['success'])} | ❌ 失败: {len(results['failed'])} | ⊘ 跳过: {len(results['skipped'])}")
-        print("=" * 60)
-    except Exception as e:
-        print(f"❌ 错误: {str(e)}")
-
-
-if __name__ == "__main__":
-    main()

src/app/scripts/ceshi.py

@@ -0,0 +1,85 @@
+"""
+测试 MinIO 上传功能 - 上传 md 文件
+"""
+from __future__ import annotations
+
+import uuid
+from pathlib import Path
+from minio import Minio
+from minio.error import S3Error
+
+from app.config.minio_client import get_minio_client
+from app.config.setting import settings
+
+
+def upload_md_files(folder_path: str | Path) -> None:
+    """
+    上传指定文件夹中的所有 .md 文件到 MinIO
+    
+    Args:
+        folder_path: 包含 md 文件的文件夹路径
+    """
+    folder_path = Path(folder_path)
+    if not folder_path.is_dir():
+        print(f"❌ 文件夹不存在: {folder_path}")
+        return
+    
+    try:
+        client = get_minio_client()
+        bucket_name = settings.MINIO_BUCKET_NAME
+        base_path = settings.MINIO_BASE_PATH
+        
+        # 获取所有 md 文件
+        md_files = list(folder_path.glob("**/*.md"))
+        if not md_files:
+            print(f"⚠️  文件夹中没有 .md 文件: {folder_path}")
+            return
+        
+        print(f"📁 找到 {len(md_files)} 个 .md 文件")
+        
+        # 遍历并上传
+        success_count = 0
+        for md_file in md_files:
+            try:
+                # 构造对象名称 - 用 UUID 替代文件名，保留扩展名
+                relative_path = md_file.relative_to(folder_path)
+                file_ext = md_file.suffix
+                object_name = f"{base_path}/ceshi/{uuid.uuid4()}{file_ext}"
+                
+                # 读取文件内容并上传
+                with open(md_file, "rb") as f:
+                    result=client.put_object(
+                        bucket_name=bucket_name,
+                        object_name=object_name,
+                        data=f,
+                        length=md_file.stat().st_size,
+                    )
+                
+                print(f"✅ 上传成功: {result.object_name} (源文件: {md_file.name})")
+                success_count += 1
+                
+            except S3Error as e:
+                print(f"❌ 上传失败 {md_file.name}: {e}")
+            except Exception as e:
+                print(f"❌ 错误 {md_file.name}: {e}")
+        
+        print(f"\n📊 上传完成: {success_count}/{len(md_files)} 个文件")
+        
+    except ValueError as e:
+        print(f"❌ 配置错误: {e}")
+    except Exception as e:
+        print(f"❌ 连接错误: {e}")
+
+
+if __name__ == "__main__":
+    # 使用示例 - 修改路径为实际的文件夹路径
+    # 例如: C:\Users\ZengChao\Desktop\新建文件夹
+    test_folder = r"C:\Users\ZengChao\Desktop\新建文件夹"
+    
+    print(f"🔍 开始上传 md 文件到 MinIO...")
+    print(f"📂 文件夹: {test_folder}")
+    print(f"🪣 桶: {settings.MINIO_BUCKET_NAME}")
+    print(f"🔗 端点: {settings.MINIO_ENDPOINT}")
+    print("-" * 60)
+    
+    upload_md_files(test_folder)

uv.lock

@@ -10,6 +10,40 @@ resolution-markers = [
     "python_full_version < '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
 ]
 
+[[package]]
+name = "aiomysql"
+version = "0.3.2"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "pymysql" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/29/e0/302aeffe8d90853556f47f3106b89c16cc2ec2a4d269bdfd82e3f4ae12cc/aiomysql-0.3.2.tar.gz", hash = "sha256:72d15ef5cfc34c03468eb41e1b90adb9fd9347b0b589114bd23ead569a02ac1a", size = 108311, upload-time = "2025-10-22T00:15:21.278Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/4c/af/aae0153c3e28712adaf462328f6c7a3c196a1c1c27b491de4377dd3e6b52/aiomysql-0.3.2-py3-none-any.whl", hash = "sha256:c82c5ba04137d7afd5c693a258bea8ead2aad77101668044143a991e04632eb2", size = 71834, upload-time = "2025-10-22T00:15:15.905Z" },
+]
+
+[[package]]
+name = "annotated-types"
+version = "0.7.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89", size = 16081, upload-time = "2024-05-20T21:33:25.928Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" },
+]
+
+[[package]]
+name = "anyio"
+version = "4.12.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "idna" },
+    { name = "typing-extensions", marker = "python_full_version < '3.13'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/96/f0/5eb65b2bb0d09ac6776f2eb54adee6abe8228ea05b20a5ad0e4945de8aac/anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703", size = 228685, upload-time = "2026-01-06T11:45:21.246Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c", size = 113592, upload-time = "2026-01-06T11:45:19.497Z" },
+]
+
 [[package]]
 name = "argon2-cffi"
 version = "25.1.0"
@@ -119,6 +153,81 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/ae/3a/dbeec9d1ee0844c679f6bb5d6ad4e9f198b1224f4e7a32825f47f6192b0c/cffi-2.0.0-cp314-cp314t-win_arm64.whl", hash = "sha256:0a1527a803f0a659de1af2e1fd700213caba79377e27e4693648c2923da066f9", size = 184195, upload-time = "2025-09-08T23:23:43.004Z" },
 ]
 
+[[package]]
+name = "charset-normalizer"
+version = "3.4.4"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/13/69/33ddede1939fdd074bce5434295f38fae7136463422fe4fd3e0e89b98062/charset_normalizer-3.4.4.tar.gz", hash = "sha256:94537985111c35f28720e43603b8e7b43a6ecfb2ce1d3058bbe955b73404e21a", size = 129418, upload-time = "2025-10-14T04:42:32.879Z" }
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