What is LangChain?

LangChain is a modular and flexible framework for building applications with LLMs. It offers abstractions like chains, agents, and memory.

It supports many LLM providers including OpenAI, Anthropic, Google, and open-source models.

Core Components

LangChain's core components include Models, Prompts, Chains, and Memory. These components combine to form complex AI workflows.

Each component can be used independently or combined to create powerful pipelines.

RAG (Retrieval-Augmented Generation)

Building RAG applications with LangChain is straightforward. You can load documents into a vector database and provide context-enriched answers to user questions.

Document loading and splitting Vector storage and indexing Context retrieval with similarity search Answer generation with LLM

Agents and Tool Usage

LangChain agents enable LLMs to use tools. You can have your AI assistant perform web searches, make API calls, or query databases.

LangChain Expression Language

LangChain's own expression language (LCEL) lets you define your chains declaratively. This language supports features like parallel execution, streaming, and error handling.