# Base RAG 简洁的RAG基础库,支持多种embedding模型和Chroma向量数据库。 ## 安装 ```bash pip install base-rag ``` ## 使用 ```python from base_rag import BaseRAG class MyRAG(BaseRAG): def ingest(self, file_path: str): documents = self.load_and_split_documents(file_path) self.add_documents_to_vector_store(documents) def query(self, question: str) -> str: docs = self.similarity_search(question) return f"找到 {len(docs)} 个相关文档" # OpenAI API config = { "type": "openai", "model": "text-embedding-3-small", "api_key": "your-api-key" } # 本地模型 config = { "type": "local", "model_name": "sentence-transformers/all-MiniLM-L6-v2" } rag = MyRAG(embedding_config=config) rag.ingest("document.txt") result = rag.query("问题") ```