The open-source framework for developing applications powered by large language models.
Summary
LangChain is a powerful and flexible framework designed to simplify the development of applications that leverage the capabilities of large language models (LLMs). It provides a standardized interface for interacting with various LLMs, making it easier to build complex AI-powered workflows.
The core purpose of LangChain is to enable developers to move beyond simple LLM prompts and create sophisticated applications that can reason, plan, and interact with external data sources. It offers a modular and composable approach, allowing users to chain together different LLM calls and other tools to achieve desired outcomes.
Whether you're building chatbots, question-answering systems, summarization tools, or agents that can perform actions, LangChain provides the building blocks and abstractions necessary to accelerate your development process and build more robust and intelligent AI applications.
Key Features
- LLM Integration: Connects to a wide range of LLMs.
- Chains: Sequences of calls to LLMs and other utilities.
- Agents: LLMs that dynamically decide which actions to take.
- Memory: Persists state between chain/agent calls.
- Document Loaders: Integrates with various data sources.
- Vector Stores: Supports embedding and searching unstructured data.