Integrate LLM Data with Helicone

integration-helicone (Helicone AI Gateway)

You can run this example with:

npx promptfoo@latest init --example integration-helicone
cd integration-helicone

This example demonstrates how to use the Helicone AI Gateway provider in promptfoo to route requests through a self-hosted Helicone AI Gateway instance for unified provider access.

What This Example Shows

• Unified Interface: Use the same OpenAI-compatible syntax to access multiple providers
• Load Balancing: Smart routing based on provider availability and performance
• Self-Hosted Gateway: Full control over your LLM routing infrastructure
• Provider Comparison: Compare responses from different providers through a single interface
• Flexible Configuration: Easy switching between providers and models

Prerequisites

1. Helicone AI Gateway: A running instance (we'll start one locally)
2. API Keys: You'll need at least one provider API key:
   • OpenAI API key (recommended)
   • Anthropic API key (optional)
   • Groq API key (optional)

Setup

1. Set Environment Variables:

   # Set your provider API keys
   export OPENAI_API_KEY=your_openai_api_key_here
   export ANTHROPIC_API_KEY=your_anthropic_api_key_here  # Optional
   export GROQ_API_KEY=your_groq_api_key_here           # Optional
   

2. Start Helicone AI Gateway:

   # In a separate terminal, start the gateway
   npx @helicone/ai-gateway@latest
   

   The gateway will start on http://localhost:8080 by default.

3. Install promptfoo (if you haven't already):

   npm install -g promptfoo
   

Running the Example

From this directory, run:

promptfoo eval

This will:

• Send the same prompts to all three providers through the Helicone AI Gateway
• Compare responses and performance across providers
• Generate a detailed comparison report
• Show differences in model capabilities and response patterns

What Happens

1. Request Routing: Each request is sent to the local Helicone AI Gateway at http://localhost:8080
2. Provider Selection: The gateway routes each request to the appropriate provider (OpenAI, Anthropic, or Groq)
3. Unified Interface: All providers use the same OpenAI-compatible request/response format
4. Response Comparison: promptfoo compares the responses from each provider

Gateway Features

The Helicone AI Gateway provides several powerful features:

• Load Balancing: Automatic routing to the fastest/most reliable provider
• Caching: Built-in response caching to reduce costs and improve latency
• Rate Limiting: Configurable rate limits to prevent abuse
• Observability: Optional integration with Helicone's observability platform
• Self-Hosted: Full control over your infrastructure and data

Configuration Details

The example configuration includes:

Provider Setup

providers:
  - id: helicone:openai/gpt-4o-mini
    label: 'OpenAI via Helicone Gateway'
    config:
      temperature: 0.7
      max_tokens: 500

Key Features Demonstrated

1. Unified Interface: All providers use the same helicone:provider/model format
2. OpenAI Compatibility: Standard OpenAI parameters work across all providers
3. Easy Switching: Change providers by simply updating the model name
4. Local Gateway: All requests go through your self-hosted gateway instance

Customization

You can modify the configuration to:

1. Add More Providers: Include any providers supported by your Helicone AI Gateway
2. Change Models: Specify different models using the provider/model format
3. Custom Gateway: Point to a different Helicone AI Gateway instance
4. Router Configuration: Use custom routers for different environments

Example with Custom Gateway and Router

providers:
  - id: helicone:openai/gpt-4o
    config:
      baseUrl: http://my-gateway.company.com:8080
      router: production
      temperature: 0.5

Advanced Features

Using Different Gateway Endpoints

Route to different environments using routers:

providers:
  - id: helicone:openai/gpt-4o
    config:
      router: production

  - id: helicone:openai/gpt-4o-mini
    config:
      router: development

Custom Gateway Configuration

If you're running your own Helicone AI Gateway with custom configuration:

providers:
  - id: helicone:custom-provider/custom-model
    config:
      baseUrl: http://localhost:9000
      headers:
        Custom-Header: value

Troubleshooting

Common Issues

1. Authentication Error: Verify your HELICONE_API_KEY is correct
2. Provider API Key Missing: Ensure you have valid API keys for the providers you're testing
3. No Data in Dashboard: Check that requests are successfully completing

Debug Mode

For detailed request logging:

LOG_LEVEL=debug promptfoo eval

Learn More

• Helicone Documentation
• promptfoo Helicone Provider Guide
• promptfoo Documentation

Next Steps

1. Explore the Dashboard: Review the analytics in your Helicone dashboard
2. Set Up Alerts: Configure cost and usage alerts in Helicone
3. Optimize Costs: Use caching and rate limiting to reduce expenses
4. Scale Testing: Add more providers and test cases for comprehensive evaluation