llama-index-llms-helicone 0.1.1

llama-index llms helicone (OpenAI-compatible) integration

LlamaIndex LLMs Integration: Helicone

Installation

To install the required packages, run:

pip install llama-index-llms-helicone
pip install llama-index

Setup

Initialize Helicone

Set your Helicone API key via HELICONE_API_KEY (or pass directly). No provider API keys are needed when using the Helicone AI Gateway.

from llama_index.llms.helicone import Helicone
from llama_index.core.llms import ChatMessage

llm = Helicone(
    api_key="<helicone-api-key>",  # or set HELICONE_API_KEY env var
    model="gpt-4o-mini",  # works across providers via gateway
)

Generate Chat Responses

You can generate a chat response by sending a list of ChatMessage instances:

message = ChatMessage(role="user", content="Tell me a joke")
resp = llm.chat([message])
print(resp)

Streaming Responses

To stream responses, use the stream_chat method:

message = ChatMessage(role="user", content="Tell me a story in 250 words")
resp = llm.stream_chat([message])
for r in resp:
    print(r.delta, end="")

Complete with Prompt

You can also generate completions with a prompt using the complete method:

resp = llm.complete("Tell me a joke")
print(resp)

Streaming Completion

To stream completions, use the stream_complete method:

resp = llm.stream_complete("Tell me a story in 250 words")
for r in resp:
    print(r.delta, end="")

Model Configuration

To use a specific model, you can specify it during initialization. For example, to use Mistral's Mixtral model, you can set it like this:

from llama_index.llms.helicone import Helicone

llm = Helicone(model="gpt-4o-mini")
resp = llm.complete("Write a story about a dragon who can code in Rust")
print(resp)

Notes

• Default Helicone base URL is https://ai-gateway.helicone.ai/v1. Override with api_base or HELICONE_API_BASE if needed.
• Only HELICONE_API_KEY is required. The gateway routes to the correct provider based on the model string.