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🕵️‍♂️ Library designed for developers eager to explore the potential of Large Language Models (LLMs) and other generative AI through a clean, effective, and Go-idiomatic approach.

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Agency: The Go Way to AI

Library designed for developers eager to explore the potential of Large Language Models (LLMs) and other generative AI through a clean, effective, and Go-idiomatic approach.

Welcome to the agency! 🕵️‍♂️

Dracula-agent, mascot of the "agency" library.

💻 Quick Start

Install package:

go get github.com/neurocult/agency

Chat example:

package main

import (
	"bufio"
	"context"
	"fmt"
	"os"

	_ "github.com/joho/godotenv/autoload"

	"github.com/neurocult/agency"
	"github.com/neurocult/agency/providers/openai"
)

func main() {
	assistant := openai.
		New(openai.Params{Key: os.Getenv("OPENAI_API_KEY")}).
		TextToText(openai.TextToTextParams{Model: "gpt-3.5-turbo"}).
		SetPrompt("You are helpful assistant.")

	messages := []agency.Message{}
	reader := bufio.NewReader(os.Stdin)
	ctx := context.Background()

	for {
		fmt.Print("User: ")

		text, err := reader.ReadString('\n')
		if err != nil {
			panic(err)
		}

		input := agency.UserMessage(text)
		answer, err := assistant.SetMessages(messages).Execute(ctx, input)
		if err != nil {
			panic(err)
		}

		fmt.Println("Assistant: ", answer)

		messages = append(messages, input, answer)
	}
}

That's it!

See examples to find out more complex usecases including RAGs and multimodal operations.

🚀 Features

Pure Go: fast and lightweight, statically typed, no need to mess with Python or JavaScript

✨ Write clean code and follow clean architecture by separating business logic from concrete implementations

✨ Easily create custom operations by implementing simple interface

Compose operations together into processes with the ability to observe each step via interceptors

OpenAI API bindings (can be used for any openai-compatable API: text to text (completion), text to image, text to speech, speech to text

🤔 Why need Agency?

At the heart of Agency is the ambition to empower users to build autonomous agents. While perfect for all range of generative AI applications, from chat interfaces to complex data analysis, our library's ultimate goal is to simplify the creation of autonomous AI systems. Whether you're building individual assistant or coordinating agent swarms, Agency provides the tools and flexibility needed to bring these advanced concepts to life with ease and efficiency.

In the generative AI landscape, Go-based libraries are rare. The most notable is LangChainGo, a Go port of the Python LangChain. However, translating Python to Go can be clunky and may not fit well with Go's idiomatic style. Plus, some question LangChain's design, even in Python. This situation reveals a clear need for an idiomatic Go alternative.

Our goal is to fill this gap with a Go-centric library that emphasizes clean, simple code and avoids unnecessary complexities. Agency is designed with a small, robust core, easy to extend and perfectly suited to Go's strengths in static typing and performance. It's our answer to the lack of Go-native solutions in generative AI.

Tutorial

🛣 Roadmap

In the next versions:

  • Support for external function calls
  • Metadata (tokens used, audio duration, etc)
  • More provider-adapters, not only openai
  • Image to text operations
  • Powerful API for autonomous agents
  • Tagging and JSON output parser