Langchain documentation. See full list on github.
- Langchain documentation. Learn how to use langchain, a library for building language applications with LLMs and tools. Learn how to use LangChain's Python and JavaScript libraries, integrations, methods, and tools to create end-to-end applications with LLMs. They then used LangGraph to structure the multi-agent orchestration by deploying modular sub agents. Browse the classes, functions, and methods for agents, tools, output parsers, and more. The Vodafone implementation uses LangChain modular document loaders, vector integration, and support for multiple LLMs (OpenAI, LLaMA 3, and Gemini) to rapidly prototype and benchmark these pipelines. Below is a detailed walkthrough of LangChain’s main modules, their roles, and code examples, following the latest . Learn how to use LangChain's components, integrations, and orchestration framework with tutorials, guides, and API reference. LangChain is a Python library that simplifies every stage of the LLM application lifecycle: development, productionization, and deployment. Its architecture allows developers to integrate LLMs with external data, prompt engineering, retrieval-augmented generation (RAG), semantic search, and agent workflows. Jul 4, 2025 ยท LangChain is a modular framework designed to build applications powered by large language models (LLMs).