LlamaIndex Integration

Introduction#

The Helicone LLM for LlamaIndex lets you send OpenAI‑compatible requests through the Helicone AI Gateway — no provider keys needed. Gain centralized routing, observability, and control across many models and providers.

Install#

pip install llama-index-llms-helicone

Usage#

from llama_index.llms.helicone import Heliconefrom llama_index.llms.openai_like.base import ChatMessagellm = Helicone(    api_key="<helicone-api-key>",    model="gpt-4o-mini",  # works across providers    is_chat_model=True,)message: ChatMessage = ChatMessage(role="user", content="Hello world!")response = llm.chat(messages=[message])print(str(response))

Parameters#

• model: OpenAI‑compatible model name routed via Helicone. See the model registry.
• api_base (optional): Base URL for Helicone AI Gateway (defaults to the package’s DEFAULT_API_BASE). Can also be set via HELICONE_API_BASE.
• api_key: Your Helicone API key. You can set via constructor or HELICONE_API_KEY.
• default_headers (optional): Add additional headers; the Authorization: Bearer <api_key> header is set automatically.

Environment Variables#

export HELICONE_API_KEY=sk-helicone-...# Optional overrideexport HELICONE_API_BASE=https://ai-gateway.helicone.ai/v1

Advanced Configuration#

from llama_index.llms.helicone import Heliconellm = Helicone(    model="gpt-4.1-mini",    api_key="<helicone-api-key>",    api_base="https://ai-gateway.helicone.ai/v1",    default_headers={        "Helicone-Session-Id": "demo-session",        "Helicone-User-Id": "user-123",        "Helicone-Property-Environment": "production",    },    temperature=0.2,    max_tokens=256,)

Notes#

• Authentication uses your Helicone API key; provider keys are not required when using the AI Gateway.
• All requests appear in the Helicone dashboard with full request/response visibility and cost tracking.
• Learn more about routing and model coverage:
  • Provider routing
  • Model registry