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title, type, tags, sources, last_updated
title type tags sources last_updated
LangChain entity
llm
framework
rag
document-loading
RAG从入门到精通系列1基础RAG
2026-04-16

Basic Information

  • Type: LLM Application Framework
  • Source: RAG从入门到精通系列1基础RAG

Definition

LangChain is a framework for building LLM applications, providing over 160 different document loaders for loading data from various sources, as well as components for building RAG pipelines.

Key Features

  • Document Loaders: 160+ loaders for various data sources
  • Chain Abstraction: Link retrieval and generation components together
  • Retriever Interface: Unified abstraction for retrieval components
  • PromptTemplate: Template system for constructing prompts
  • Integration: Works with various LLMs (Qwen, GPT-4, Claude, etc.) and vector databases (Qdrant, Chroma, Pinecone, etc.)

Applications in RAG

  • Loading external documents via document loaders
  • Splitting documents into chunks (Splits)
  • Creating retrievers from vector stores
  • Chaining retrieval and generation into a unified pipeline
  • Converting raw AIMessage outputs to clean string results
  • RAGLangChain is commonly used to build RAG pipelines
  • LlamaIndexAlternative framework for building LLM applications
  • 向量数据库Vector stores integrated with LangChain
  • QdrantVector database mentioned in RAG tutorials
  • QwenLLM often used with LangChain