[!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.<br/>

• 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

1. Initialise a new go module

mkdir example
cd example
go mod init example

2. 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)
}

3. Install the Go dependencies

go mod tidy

4. 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