tmc/langchaingo

★ 9,236GoAudience · developerComplexity · 3/5Setup · moderate

Mindmap

mindmap
  root((LangChain Go))
    What it does
      Go LLM toolkit
      AI app framework
      LangChain port
    Providers
      OpenAI
      Google Gemini
      Ollama local
    Use cases
      Chatbots
      Document Q&A
      AI pipelines
    Setup
      Go module
      API key needed
      Community maintained

mindmap root((LangChain Go)) What it does Go LLM toolkit AI app framework LangChain port Providers OpenAI Google Gemini Ollama local Use cases Chatbots Document Q&A AI pipelines Setup Go module API key needed Community maintained

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Things people build with this

USE CASE 1

Build a chatbot in Go that connects to OpenAI and maintains conversation history across turns

USE CASE 2

Create a document question-answering tool in Go that loads text files and answers questions using an AI model

USE CASE 3

Swap an OpenAI backend for a local Ollama model without changing the core application logic

USE CASE 4

Wire together a multi-step AI pipeline in Go using composable LangChain-style building blocks

Tech stack

GoOpenAI APIGoogle GeminiOllama

Getting it running

Difficulty · moderate Time to first run · 30min

Requires an API key from your chosen provider (OpenAI, Google, etc.) or a running Ollama instance for local models.

No license terms are mentioned in the explanation.

In plain English

LangChain Go is a Go-language implementation of LangChain, a widely used toolkit originally written in Python for building applications that rely on large language models. Large language models are the AI systems that power things like ChatGPT and similar chat products. The library gives Go developers a way to connect to AI model providers, such as OpenAI, Google Gemini, and locally-run models via Ollama, and combine them into complete applications. The basic idea is composability: you wire together a model connection, some logic for handling prompts and responses, and optional memory or storage, to build things like chatbots, document question-answering tools, or any program that sends text to an AI and does something useful with the output. A short code snippet in the README shows the core pattern: initialize an OpenAI connection, send a prompt, and print the AI's response. The actual API covers much more than that single example. The project's documentation site and Go package reference contain the full details, and a folder of example programs in the repository covers more practical use cases including integration with Gemini and Ollama. The README is brief, pointing mainly to external resources and community blog posts. The project is community-maintained and actively looking for contributors. It describes itself as a port of Python's LangChain patterns into idiomatic Go, with support for multiple AI model providers through a shared interface, so you can swap providers without rewriting your application's core logic.

Copy-paste prompts

Prompt 1

Using tmc/langchaingo, show me the minimal Go code to initialize an OpenAI LLM client, send a prompt string, and print the response.

Prompt 2

With langchaingo, how do I build a simple document Q&A tool in Go that loads a plain text file and lets a user ask questions about it using a Gemini model?

Prompt 3

Show me how to swap the LLM provider in a langchaingo app from OpenAI to a local Ollama model with no changes to the prompt-handling logic.

Prompt 4

Using tmc/langchaingo, write a Go function that sends a streaming chat completion request to OpenAI and prints each token chunk as it arrives.

Prompt 5

How do I add langchaingo to a Go module with go get, and which environment variable do I set to provide an OpenAI API key?

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