Documentation Index Fetch the complete documentation index at: https://mintlify.com/Helicone/helicone/llms.txt
Use this file to discover all available pages before exploring further.
Helicone supports 100+ LLM providers and integrates seamlessly with popular AI frameworks. Choose the integration method that works best for your setup.
Supported Providers Helicone works with all major LLM providers:
OpenAI GPT-4, GPT-3.5, and more
Azure OpenAI Enterprise OpenAI deployment
Google Vertex AI Gemini and PaLM models
AWS Bedrock Multiple model providers
Together AI Open source models
Integration Methods 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
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
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
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
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" ), }, )
Getting Your API Key To use any integration method, you’ll need a Helicone API key:
Generate API key
Go to Settings > API Keys and create a new key
Store securely
Add to your environment variables: export HELICONE_API_KEY = "sk-helicone-..."
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