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March 15, 2026 · View on GitHub
Important
Hey there, LinGoose friend 🪿
First of all, thank you for being here. LinGoose has been a fun journey and I am proud of what it became.
The honest news: LinGoose is no longer under active development. Life got busy, the AI world moved fast, and I found myself wanting to build something new rather than patch something old.
That something new is Phero 🐜, a Go framework built from the ground up for multi-agent AI systems. Same values, better foundation, a lot more ambition.
LinGoose is not going anywhere. It will stay here, stable and available. But if you are starting something new, come join the ant colony.
🪿 LinGoose 
What is LinGoose?
LinGoose is a Go framework for building awesome AI/LLM applications.
- LinGoose is modular — You can import only the modules you need to build your application.
- LinGoose is an abstraction of features — You can choose your preferred implementation of a feature and/or create your own.
- LinGoose is a complete solution — You can use LinGoose to build your AI/LLM application from the ground up.
Did you know? A goose 🪿 fills its car 🚗 with goose-line ⛽!
🚀 Support the project by starring ⭐ the repository on GitHub and sharing it with your friends!
Quick start
mkdir example
cd example
go mod init example
- Create your first LinGoose application
package main
import (
"context"
"fmt"
"github.com/henomis/lingoose/llm/openai"
"github.com/henomis/lingoose/thread"
)
func main() {
myThread := thread.New().AddMessage(
thread.NewUserMessage().AddContent(
thread.NewTextContent("Tell me a joke about geese"),
),
)
err := openai.New().Generate(context.Background(), myThread)
if err != nil {
panic(err)
}
fmt.Println(myThread)
}
- Install the Go dependencies
go mod tidy
- Start the example application
export OPENAI_API_KEY=your-api-key
go run .
A goose fills its car with goose-line!
Reporting Issues
If you think you've found a bug, or something isn't behaving the way you think it should, please raise an issue on GitHub.
Contributing
We welcome contributions, Read our Contribution Guidelines to learn more about contributing to LinGoose
Blog posts and articles
- Anthropic's Claude Integration with Go and Lingoose
- Empowering Go: unveiling the synergy of AI and Q&A pipelines
- Leveraging Go and Redis for Efficient Retrieval Augmented Generation
Connect with the author
Join the community
License
© Simone Vellei, 2023~time.Now()
Released under the MIT License