Langchain Go
FreeGolang Langchain 
FreeFree tier
About Langchain Go
LangChain Go is the Go language implementation of LangChain, enabling developers to build applications with large language models through composability. It provides modular components such as agents, chains, document loaders, embeddings, LLMs, memory, output parsers, prompts, tools, vector stores, and callbacks. Designed to be the easiest way to write LLM-based programs in Go, it includes a simple API, comprehensive documentation, and practical examples for tasks like generating text, building chatbots, and integrating with various LLM providers.
Key Features
Composable architecture for building LLM applications with agents, chains, and tools
Native Go implementation with full support for LLMs, embeddings, and vector stores
Modular components including document loaders, text splitters, output parsers, and memory
Callbacks for integrating custom logic into LLM workflows
Supports multiple LLM providers via pluggable backends
Examples and documentation for rapid prototyping
Open source with an active community on Discord
Pros & Cons
Pros
- Open source with a permissive MIT license
- Leverages Go's performance and concurrency for scalable LLM applications
- Modular design allows easy mixing and matching of components
- Active community and Discord support
- Simple API surface similar to LangChain Python but idiomatic to Go
Cons
- Less mature than the Python LangChain ecosystem
- Smaller community and fewer third-party integrations compared to Python version
- Documentation and examples are still growing
- Some advanced LangChain features may not yet be available
Best For
Building conversational AI agents and chatbotsGenerating creative text, such as company names or storiesCreating document question-answering systemsDeveloping LLM-powered tools with composabilityRapid prototyping of LLM applications in Go
FAQ
What is LangChain Go?
LangChain Go is the Go language implementation of LangChain, designed to help developers build applications with large language models through composability.
How do I get started with LangChain Go?
Refer to the examples directory in the repository for sample code, and check the documentation site at tmc.github.io/langchaingo/.
How can I contribute to LangChain Go?
Contributions are welcome. Join the Discord server for discussions and see CONTRIBUTING.md for guidelines.