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https://github.com/henomis/lingoose
🪿 LinGoose is a Go framework for building awesome AI/LLM applications.
https://github.com/henomis/lingoose
ai chatgpt embeddings go golang index llm openai pinecone pipeline prompt vector
Last synced: about 20 hours ago
JSON representation
🪿 LinGoose is a Go framework for building awesome AI/LLM applications.
- Host: GitHub
- URL: https://github.com/henomis/lingoose
- Owner: henomis
- License: mit
- Created: 2023-04-17T05:51:56.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-02T17:23:00.000Z (6 days ago)
- Last Synced: 2024-11-02T17:29:38.178Z (6 days ago)
- Topics: ai, chatgpt, embeddings, go, golang, index, llm, openai, pinecone, pipeline, prompt, vector
- Language: Go
- Homepage: https://lingoose.io
- Size: 1.17 MB
- Stars: 640
- Watchers: 10
- Forks: 53
- Open Issues: 11
-
Metadata Files:
- Readme: README.md
- Changelog: history/history.go
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
- awesome-ChatGPT-repositories - lingoose - 🪿 LinGoose it's a Go framework for developing LLMs-based application using pipelines (Prompts)
README
![lingoose](docs/static/lingoose-small.png)
# 🪿 LinGoose [![Build Status](https://github.com/henomis/lingoose/actions/workflows/checks.yml/badge.svg)](https://github.com/henomis/lingoose/actions/workflows/checks.yml) [![GoDoc](https://godoc.org/github.com/henomis/lingoose?status.svg)](https://godoc.org/github.com/henomis/lingoose) [![Go Report Card](https://goreportcard.com/badge/github.com/henomis/lingoose)](https://goreportcard.com/report/github.com/henomis/lingoose) [![GitHub release](https://img.shields.io/github/release/henomis/lingoose.svg)](https://github.com/henomis/lingoose/releases)
## What is LinGoose?
[LinGoose](https://github.com/henomis/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](https://github.com/henomis/lingoose) and sharing it with your friends!
## Quick start
1. [Initialise a new go module](https://golang.org/doc/tutorial/create-module)```sh
mkdir example
cd example
go mod init example
```2. Create your first LinGoose application
```go
package mainimport (
"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
```sh
go mod tidy
```4. Start the example application
```sh
export OPENAI_API_KEY=your-api-keygo 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](https://github.com/henomis/lingoose/issues) on GitHub.
## Contributing
We welcome contributions, Read our [Contribution Guidelines](https://github.com/henomis/lingoose/blob/main/CONTRIBUTING.md) to learn more about contributing to **LinGoose**
## Blog posts and articles
- [Anthropic's Claude Integration with Go and Lingoose](https://simonevellei.com/blog/posts/anthropic-claude-integration-with-go-and-lingoose/)
- [Empowering Go: unveiling the synergy of AI and Q&A pipelines](https://simonevellei.com/blog/posts/empowering-go-unveiling-the-synergy-of-ai-and-qa-pipelines/)
- [Leveraging Go and Redis for Efficient Retrieval Augmented Generation](https://simonevellei.com/blog/posts/leveraging-go-and-redis-for-efficient-retrieval-augmented-generation/)## Connect with the author
[![Twitter](https://img.shields.io/twitter/follow/simonevellei?label=Follow:%20Simone%20Vellei&style=social)](https://twitter.com/simonevellei) [![GitHub](https://img.shields.io/badge/Follow-henomis-green?logo=github&link=https%3A%2F%2Fgithub.com%2Fhenomis)](https://github.com/henomis) [![Linkedin](https://img.shields.io/badge/Connect-Simone%20Vellei-blue?logo=linkedin&link=https%3A%2F%2Fwww.linkedin.com%2Fin%2Fsimonevellei%2F)](https://www.linkedin.com/in/simonevellei/)
### Join the community
[![Discord](https://img.shields.io/badge/Discord-lingoose-blue?logo=discord&link=https%3A%2F%2Fdiscord.gg%2FmcKEQTKqGS)](https://discord.gg/mcKEQTKqGS)
## License
© Simone Vellei, 2023~`time.Now()`
Released under the [MIT License](LICENSE)