检索器重构

rag_indexer/__init__.py

@@ -9,52 +9,52 @@ Offline RAG Indexer module.
 - 父文档存储（PostgreSQL）
 
 示例用法：
-    >>> from rag_indexer import IndexBuilder, SplitterType
+    >>> from rag_indexer import IndexBuilder, IndexBuilderConfig, SplitterType
     >>> 
-    >>> builder = IndexBuilder(
+    >>> config = IndexBuilderConfig(
     ...     collection_name="my_docs",
     ...     splitter_type=SplitterType.PARENT_CHILD,
-    ...     qdrant_url="http://localhost:6333"
     ... )
+    >>> builder = IndexBuilder(config)
     >>> 
-    >>> builder.build_from_file("document.pdf")
+    >>> # 或直接传参（向后兼容）
+    >>> builder = IndexBuilder(collection_name="my_docs")
+    >>> 
+    >>> await builder.build_from_file("document.pdf")
 """
 
+from .IndexBuilder import IndexBuilder, IndexBuilderConfig, DocstoreConfig
 from .loaders import DocumentLoader
-from .splitters import (
-    SplitterType,
-    get_splitter,
-    ParentChildSplitter,
-)
-from .embedders import LlamaCppEmbedder
-from .vector_store import QdrantVectorStore
-from .builder import IndexBuilder
+from .splitters import SplitterType, get_splitter
 
-# 导出存储相关类（从新的 store 包）
-from .store import (
+# 从 rag_core 重新导出常用组件
+from rag_core import (
+    LlamaCppEmbedder,
+    QdrantVectorStore,
     PostgresDocStore,
     create_docstore,
 )
 
-
-
 __version__ = "2.0.0"
 
 __all__ = [
-    # 核心类
-    "DocumentLoader",
+    # 核心构建器与配置
     "IndexBuilder",
+    "IndexBuilderConfig",
+    "DocstoreConfig",
+    
+    # 加载器
+    "DocumentLoader",
     
     # 切分相关
     "SplitterType",
     "get_splitter",
-    "ParentChildSplitter",
     
-    # 嵌入和向量存储
+    # 嵌入与向量存储
     "LlamaCppEmbedder",
     "QdrantVectorStore",
     
-    # 存储（新的 store 包）
+    # 文档存储
     "PostgresDocStore",
     "create_docstore",
-]
+]