langchain-framework

What problem does it solve?

LangChain Framework provides a modular, reusable approach to building AI-powered applications by composing prompts, LLMs, memory, and tooling into cohesive chains, agents, and retrieval augmented generation pipelines, reducing engineering toil and accelerating delivery.

Core Features & Use Cases

• LCEL (LangChain Expression Language) for composing chains with a concise syntax.
• RAG with vector stores to retrieve and reason over documents.
• Agent framework with tools to orchestrate LLMs and external tools.
• Memory systems to maintain conversational context across interactions.
• LangSmith observability for tracing, logging, and evaluation.
• Use cases include building multi-step AI apps, document Q&A systems, and AI assistants with tools.

Quick Start

pip install langchain langchain-anthropic

• Set up LLM (e.g., Claude or OpenAI)
• Create a chain from prompts and LLM
• Invoke chain with input to get output