GoAI is a powerful Go library that seamlessly integrates multiple LLM providers, vector embeddings, and vector storage capabilities. Built for developers who want a clean, unified interface for AI operations.

🤖 Multiple LLM Providers

• OpenAI
• Anthropic Claude
• AWS Bedrock

📊 Vector Operations

• Efficient embeddings generation
• PostgreSQL vector storage
• Similarity search

🛠 Developer Experience

• Consistent interfaces
• Streaming support
• Type-safe operations

go get github.com/shaharia-lab/goai

You can find more examples in the _examples directory which you can run simply by go run _examples/simple_chat.go

package main

import (
   "github.com/shaharia-lab/goai"
   "log"
   "os"
)

func main() {
    // Initialize LLM
    client := goai.NewAnthropicClient(os.Getenv("ANTHROPIC_API_KEY"))
    provider := goai.NewAnthropicLLMProvider(goai.AnthropicProviderConfig{
        Client: client,
    })

    // Configure request
    llm := goai.NewLLMRequest(goai.NewRequestConfig(
        goai.WithMaxToken(200),
        goai.WithTemperature(0.7),
    ), provider)

    // Generate response
    response, err := llm.Generate([]goai.LLMMessage{
        {Role: goai.UserRole, Text: "Explain quantum computing"},
    })

    if err != nil {
        panic(err)
    }
    
    log.Println(response)
}

Visit our documentation for detailed guides on:

• Getting Started
• LLM Integration
• Embedding Generation
• Vector Operations
• MCP (Model Context Protocol) Server in Go
• API Reference

We welcome contributions! See our Contributing Guide for details.

Review our Security Policy for reporting vulnerabilities.

MIT License - see LICENSE for details.

Built with ❤️ by Shaharia Lab and Contributors