The langchain-community package is in libs/community. It can be installed with pip install langchain-community, and exported members can be imported with code like

假设我们想为 Parrot Link AI 实现一个聊天模型。 我们将在 libs/community/langchain_community/chat_models/parrot_link.py 中创建一个新文件，代码如下

LangChain integrates with many model providers. While LangChain has its own message and model APIs, LangChain has also made it as easy as possible to explore other models by …

The langchain_community.llms module allows for seamless interaction with various large language models (LLMs) like OpenAI's GPT, Hugging Face Transformers, and others.

Get started using LangGraph to assemble LangChain components into full-featured applications. Chatbots: Build a chatbot that incorporates memory. Agents: Build an agent with LangGraph.js …

LangChain Community contains third-party integrations that implement the base interfaces defined in LangChain Core, making them ready-to-use in any LangChain application.

This article will walk through the fundamentals of building with LLMs and LangChain’s Python library. The only requirement is basic familiarity with Python, – no machine learning experience …

LangChain has published a guide on implementing new langchain-* integration packages and is recommending this in most cases to help decouple versioning and support varied testing …

We’ll walk you through key LangChain concepts, installation steps, and practical code examples to help you get started. Whether you’re looking to build chatbots, AI-powered search engines, …

By leveraging REST APIs, LangChain agents can fetch real-time information, interact with databases, or perform actions on behalf of users. In this practical guide, we’ll walk through …