LinGoose is an innovative Go framework designed specifically for creating remarkable AI and LLM applications. This powerful tool empowers developers, allowing them to harness the potential of artificial intelligence with ease and efficiency.

Key Features:

• Modular Architecture: Import only the modules essential for your application, ensuring a lightweight and streamlined development process.
• Feature Abstraction: LinGoose offers flexibility by allowing you to select your preferred implementation of a feature or create custom solutions tailored to your needs.
• Complete Development Solution: From inception to deployment, LinGoose provides all the components necessary to build robust AI/LLM applications from the ground up.

Quick Start Example

Creating your first application with LinGoose is straightforward. Here's a quick example:

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)
}

To run this application, make sure to set your OpenAI API key:

export OPENAI_API_KEY=your-api-key
go run .

This example outputs a fun joke about geese, showcasing LinGoose's capabilities to interact with AI seamlessly.

Community and Contributions

LinGoose encourages community involvement and welcomes contributions. If you encounter any issues or have ideas for improvement, please report them on our GitHub issues page. For those interested in contributing, kindly review our Contribution Guidelines.

Learn More

Explore insightful articles and blog posts that delve into using Go with AI and LinGoose:

• 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 Us

Join our vibrant community on Discord and stay updated by following the author, Simone Vellei, on Twitter or on GitHub. Share your experiences and insights as we venture into the future of AI development together!

Join the Movement

Star ⭐ the LinGoose repository on GitHub to support this cutting-edge project and spread the word!