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Helicone supports 100+ LLM providers and integrates seamlessly with popular AI frameworks. Choose the integration method that works best for your setup.

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Supported Providers

Helicone works with all major LLM providers:

OpenAI

GPT-4, GPT-3.5, and more

Anthropic

Claude models

Azure OpenAI

Enterprise OpenAI deployment

Google Vertex AI

Gemini and PaLM models

AWS Bedrock

Multiple model providers

Together AI

Open source models

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Integration Methods

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Proxy Integration

The simplest way to integrate. Just change your API base URL: 
from openai import OpenAI

client = OpenAI(
    api_key=os.getenv("OPENAI_API_KEY"),
    base_url="https://oai.helicone.ai/v1",
    default_headers={
        "Helicone-Auth": f"Bearer {os.getenv('HELICONE_API_KEY')}",
    },
)
Benefits:
  • No code changes beyond configuration
  • Works with any SDK
  • Real-time logging
  • Full request/response capture

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Async Integration

Log requests asynchronously without affecting latency: 
import { HeliconeAsyncLogger } from '@helicone/helicone';
import { OpenAI } from 'openai';

const logger = new HeliconeAsyncLogger({
  apiKey: process.env.HELICONE_API_KEY,
  providers: {
    openAI: OpenAI,
  },
});
logger.init();

const openai = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY,
});

// Use OpenAI normally - logging happens in the background
Benefits:
  • Zero latency impact
  • Uses your existing provider keys
  • Background processing

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Gateway Integration

Route through multiple providers with failover and load balancing: 
const openai = new OpenAI({
  apiKey: process.env.HELICONE_API_KEY,
  baseURL: "https://ai-gateway.helicone.ai",
});

// Use multiple models with automatic fallback
const response = await openai.chat.completions.create({
  model: "claude-3-7-sonnet-20250219/anthropic,gpt-4o-mini",
  messages: [{ role: "user", content: "Hello!" }],
});
Benefits:
  • Automatic failover between providers
  • Load balancing
  • Single API key for all providers
  • Cost optimization

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Framework Integrations

Helicone integrates with popular AI frameworks:

LangChain

Full chain observability

Vercel AI SDK

Streaming and edge support

LlamaIndex

RAG pipeline tracking

Instructor

Structured output logging

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Quick Start by Provider

from openai import OpenAI

client = OpenAI(
    api_key=os.getenv("OPENAI_API_KEY"),
    base_url="https://oai.helicone.ai/v1",
    default_headers={
        "Helicone-Auth": f"Bearer {os.getenv('HELICONE_API_KEY')}",
    },
)
Full OpenAI guide →
from anthropic import Anthropic

client = Anthropic(
    api_key=os.getenv("ANTHROPIC_API_KEY"),
    base_url="https://anthropic.helicone.ai",
    default_headers={
        "Helicone-Auth": f"Bearer {os.getenv('HELICONE_API_KEY')}",
    },
)
Full Anthropic guide →
from openai import AzureOpenAI

client = AzureOpenAI(
    api_key=os.getenv("AZURE_OPENAI_API_KEY"),
    base_url="https://oai.helicone.ai/v1",
    azure_endpoint=os.getenv("AZURE_OPENAI_ENDPOINT"),
    api_version="2024-02-01",
    default_headers={
        "Helicone-Auth": f"Bearer {os.getenv('HELICONE_API_KEY')}",
        "Helicone-Target-URL": os.getenv("AZURE_OPENAI_ENDPOINT"),
    },
)

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Getting Your API Key

To use any integration method, you’ll need a Helicone API key:
1

Sign up

Create an account at helicone.ai
2

Generate API key

Go to Settings > API Keys and create a new key
3

Store securely

Add to your environment variables:
export HELICONE_API_KEY="sk-helicone-..."

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Next Steps

OpenAI Integration

Complete setup guide for OpenAI

Anthropic Integration

Integrate with Claude models

Custom Headers

Add metadata and properties

Caching

Enable request caching

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