AgenticGoKit ❤️ HuggingFace and OpenRouter

We’re excited to announce the release of AgenticGoKit v0.4.6 — a major update that expands how Go developers can build and experiment with agentic workflows.

With this release, AgenticGoKit now supports:

• Hugging Face — Access models through the new router API with OpenAI-compatible format
• OpenRouter — Use a wide variety of LLMs (GPT, Claude, Gemini, Llama) through a unified API

These integrations empower developers to build richer, more flexible AI agents without switching languages or managing complex SDKs.

What’s New

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Hugging Face Integration with New Router API

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AgenticGoKit now supports Hugging Face’s latest router-based architecture (router.huggingface.co), which provides:

• OpenAI-compatible format — Seamless migration from other providers
• Multiple API types — Inference API, Chat API, dedicated Endpoints, and self-hosted TGI
• Llama 3.2 models — Access to the latest open-source models
• Streaming support — Real-time token-by-token responses
• Advanced parameters — Fine-tune with temperature, top-p, top-k, and more

Quick Example

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import (
    "context"
    "github.com/kunalkushwaha/agenticgokit/core/vnext"
    _ "github.com/kunalkushwaha/agenticgokit/plugins/llm/huggingface"
)

config := &vnext.Config{
    Name:         "hf-assistant",
    SystemPrompt: "You are a helpful AI assistant.",
    LLM: vnext.LLMConfig{
        Provider:    "huggingface",
        Model:       "meta-llama/Llama-3.2-1B-Instruct",
        APIKey:      os.Getenv("HUGGINGFACE_API_KEY"),
        Temperature: 0.7,
        MaxTokens:   500,
    },
}

agent, _ := vnext.NewBuilder("hf-assistant").WithConfig(config).Build()
result, _ := agent.Run(context.Background(), "Explain machine learning")
fmt.Println(result.Content)

Available Models:

• meta-llama/Llama-3.2-1B-Instruct — Fast, efficient
• meta-llama/Llama-3.2-3B-Instruct — Better quality
• deepseek-ai/DeepSeek-R1 — Advanced reasoning
• Model routing with :fastest and :cheapest suffixes

HuggingFace Examples | HuggingFace vNext Quickstart

OpenRouter Integration

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OpenRouter provides a single interface to dozens of leading LLMs from OpenAI, Anthropic, Google, Meta, and more. With AgenticGoKit v0.4.6, you can:

• Access GPT-4, Claude 3, Gemini 2.0, Llama 3.1, and many others
• Compare models side-by-side for your use case
• Switch between providers with a single line of code
• Track usage with site analytics

Quick Example

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config := &vnext.Config{
    Name:         "openrouter-agent",
    SystemPrompt: "You are a helpful assistant.",
    LLM: vnext.LLMConfig{
        Provider:    "openrouter",
        Model:       "anthropic/claude-3-haiku",
        APIKey:      os.Getenv("OPENROUTER_API_KEY"),
        Temperature: 0.7,
        MaxTokens:   500,
    },
}

agent, _ := vnext.NewBuilder("openrouter-agent").WithConfig(config).Build()
result, _ := agent.Run(ctx, "What's the difference between REST and GraphQL?")

Popular Models Available:

• openai/gpt-4-turbo — Most capable GPT model
• anthropic/claude-3-haiku — Fast, cost-effective
• google/gemini-2.0-flash-exp:free — Free Google model
• meta-llama/llama-3.1-8b-instruct — Open-source Llama

OpenRouter Examples | OpenRouter vNext Quickstart

Why This Matters

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Building agentic systems in Go is now easier and more powerful than ever. By connecting to Hugging Face and OpenRouter, AgenticGoKit developers can:

• Rapidly prototype with different LLMs and compare performance
• Optimize costs by testing various model/provider combinations
• Build multi-agent systems using diverse model capabilities
• Access the latest models including Llama 3.2, Claude 3, Gemini 2.0
• Keep the speed and reliability of Go with type safety
• Switch providers easily without rewriting application logic

Key Features in v0.4.6

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Multiple API Types for HuggingFace

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1. Inference API — New router with OpenAI-compatible format
2. Chat API — Conversational models with legacy support
3. Inference Endpoints — Dedicated hosting for production
4. Text Generation Inference (TGI) — Self-hosted optimized inference

Streaming Support

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Both HuggingFace and OpenRouter now support real-time streaming:

stream, _ := agent.RunStream(ctx, "Write a story about AI")
for chunk := range stream.Chunks() {
    if chunk.Type == vnext.ChunkTypeDelta {
        fmt.Print(chunk.Delta)
    }
}

Advanced Configuration

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Fine-tune model behavior with provider-specific parameters:

LLM: vnext.LLMConfig{
    Provider:          "huggingface",
    Model:            "meta-llama/Llama-3.2-1B-Instruct",
    Temperature:      0.8,
    MaxTokens:        1000,
    TopP:             0.9,
    TopK:             50,
    RepetitionPenalty: 1.2,
}

Comprehensive Examples

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• 9 HuggingFace examples covering all API types
• 8 OpenRouter examples demonstrating various models
• Simple quickstart examples for both providers
• Migration guides for the new HuggingFace router API
• Complete documentation with troubleshooting tips

The Story: Breaking Free from LLM Lock-In

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The Challenge

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You’re building an AI agent in Go. You start with OpenAI’s GPT-4 because it’s the best. But then:

• Costs add up — Your prototype’s API bills are growing faster than your user base
• You’re locked in — What if you want to try Anthropic’s Claude? Or use open-source Llama models?
• Experimentation is hard — Testing different models means rewriting integration code
• Enterprise needs — Your client wants Azure OpenAI for compliance, but your code is OpenAI-specific

You’re stuck. Switching providers means days of refactoring.

The Solution

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AgenticGoKit v0.4.6 changes the game. With HuggingFace and OpenRouter support, you can now:

// Start with HuggingFace for experimentation
config.LLM.Provider = "huggingface"
config.LLM.Model = "meta-llama/Llama-3.2-1B-Instruct"

// Switch to OpenRouter to test Claude
config.LLM.Provider = "openrouter"
config.LLM.Model = "anthropic/claude-3-haiku"

// Move to production with OpenAI
config.LLM.Provider = "openai"
config.LLM.Model = "gpt-4-turbo"

Same code. Different providers. One line change.

The Impact

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With 5 supported providers (OpenAI, Azure OpenAI, HuggingFace, OpenRouter, Ollama), AgenticGoKit now gives you:

Build once. Deploy anywhere. Switch anytime.

Take Action: Try It Now

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Step 1: Install (30 seconds)

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go get github.com/kunalkushwaha/agenticgokit@latest

Step 2: Get an API Key (2 minutes)

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Pick one provider to start:

• HuggingFace (free tier): https://huggingface.co/settings/tokens
• OpenRouter (flexible): https://openrouter.ai/keys

Step 3: Run Your First Agent (1 minute)

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# HuggingFace - Free tier, open models
export HUGGINGFACE_API_KEY="hf_..."
cd examples/vnext/huggingface-quickstart
go run simple.go

# OR OpenRouter - 50+ models to choose from
export OPENROUTER_API_KEY="sk-or-..."
cd examples/vnext/openrouter-quickstart
go run main.go

That’s it. You’re running AI agents in Go.

What You Can Build Today

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1. Cost Optimizer Agent

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// Start cheap with HuggingFace Llama
config.LLM.Provider = "huggingface"
config.LLM.Model = "meta-llama/Llama-3.2-1B-Instruct"

// Upgrade to GPT-4 for complex queries
if complexQuery {
    config.LLM.Provider = "openai"
    config.LLM.Model = "gpt-4-turbo"
}

2. Multi-Model Research Assistant

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// Use OpenRouter to query multiple models
models := []string{
    "openai/gpt-4-turbo",
    "anthropic/claude-3-haiku",
    "google/gemini-2.0-flash-exp:free",
}

for _, model := range models {
    config.LLM.Model = model
    // Compare responses from different models
}

3. Privacy-First Local Agent

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// Start with Ollama for development
config.LLM.Provider = "ollama"
config.LLM.Model = "llama3.2"

// Switch to HuggingFace TGI for production
config.LLM.Provider = "huggingface"
config.LLM.BaseURL = "http://your-tgi-server:8080"

Learn More

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Quick Links:

• HuggingFace Quickstart — 9 examples
• OpenRouter Quickstart — 8 examples
• HuggingFace Migration Guide — New router API
• All Examples — 20+ working examples
• GitHub Discussions — Get help

Join the Community

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AgenticGoKit is open source and growing. We’d love your feedback:

• Found a bug? Open an issue
• Have an idea? Start a discussion
• Want to contribute? Check out our contributor guide
• Like what you see? Star us on GitHub

The Bottom Line

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AgenticGoKit v0.4.6 gives you freedom.

• Start with HuggingFace for free experimentation
• Switch to OpenRouter to test 50+ models
• Move to OpenAI for production quality
• Deploy to Azure OpenAI for enterprise compliance
• Or keep it local with Ollama

One codebase. Five providers. Endless possibilities.

# Get started now
go get github.com/kunalkushwaha/agenticgokit@latest

Happy building!

Questions? Join our community discussions or check out the documentation.