LangChain
Framework for developing context-aware applications powered by large language models.
Why consider LangChain?
LangChain provides composable abstractions for building autonomous agents and LLM applications. It helps developers chain together interoperable components and third-party integrations across model providers.
Learn LangChain by building
Practical setup notes, real use cases, and copy-ready examples in one focused guide.
In this guide3 sections
Overview of LangChain
LangChain is the central open-source ecosystem for building cognitive architectures and agentic workflows. As stated in the official repository documentation at https://raw.githubusercontent.com/langchain-ai/langchain/master/README.md, LangChain is a framework for building agents and LLM-powered applications. It standardizes interaction patterns across major commercial and self-hosted model providers.
The framework emphasizes composable abstractions and broad ecosystem connectivity. According to the official documentation at https://raw.githubusercontent.com/langchain-ai/langchain/master/README.md, It helps you chain together interoperable components and third-party integrations to simplify AI application development for software engineers and data science teams.
Initialization and Chat Models
Using modern LangChain abstractions, developers can instantiate chat models with unified interfaces. As specified in the repository guide at https://raw.githubusercontent.com/langchain-ai/langchain/master/README.md, initialize and invoke a model with model = init_chat_model("openai:gpt-5.5"):
from langchain.chat_models import init_chat_modelmodel = init_chat_model("openai:gpt-5.5")result = model.invoke("Hello, world!")Licensing and Governance
LangChain is maintained under the permissive MIT License. According to the official license file at https://raw.githubusercontent.com/langchain-ai/langchain/master/LICENSE, the software is distributed under the MIT License. This permissive license ensures developers and organizations can build proprietary or open solutions without restrictive terms.
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