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Documentation Index

Fetch the complete documentation index at: https://docs.auriko.ai/llms.txt

Use this file to discover all available pages before exploring further.

Use Auriko as your LLM provider in LlamaIndex. This integration is Python-only. For TypeScript, use the Vercel AI SDK integration.

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Prerequisites

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Install

pip install "auriko[llamaindex]"

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Use SDK adapter

Use the AurikoLlamaIndexLLM adapter: 
from auriko.frameworks.llamaindex import AurikoLlamaIndexLLM

llm = AurikoLlamaIndexLLM(model="gpt-5.4")
AurikoLlamaIndexLLM supports chat, completion, streaming, async, per-call routing overrides, and Auriko error mapping. 
from auriko.frameworks.llamaindex import AurikoLlamaIndexLLM
from llama_index.core.llms import ChatMessage

llm = AurikoLlamaIndexLLM(model="gpt-5.4")

response = llm.chat([ChatMessage(role="user", content="What is 2+2?")])
print(response.message.content)

for chunk in llm.stream_chat([ChatMessage(role="user", content="Count to 5")]):
    print(chunk.delta, end="", flush=True)

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Configure options

ParameterTypeDefaultDescription
modelstr(required)Model ID
api_keystr | NoneAURIKO_API_KEY envAPI key
routingRoutingOptions | NoneNoneDefault routing configuration
api_basestr"https://api.auriko.ai/v1"API base URL
**kwargsPassed through to LlamaIndex’s OpenAI (e.g., temperature, max_tokens)

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Configure routing

Pass a RoutingOptions instance to set default routing: 
from auriko.frameworks.llamaindex import AurikoLlamaIndexLLM
from auriko.route_types import RoutingOptions

llm = AurikoLlamaIndexLLM(
    model="gpt-5.4",
    routing=RoutingOptions(optimize="cost"),
)
Per-call routing overrides the instance default: 
from auriko.route_types import RoutingOptions

response = llm.chat(
    [ChatMessage(role="user", content="Hello!")],
    routing=RoutingOptions(optimize="tps-focus"),
)
Access routing metadata from the response: 
response = llm.chat([ChatMessage(role="user", content="Hello!")])
metadata = response.additional_kwargs.get("routing_metadata")
if metadata:
    print(f"Provider: {metadata['provider']}")

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Configure manually

If you prefer to use LlamaIndex’s OpenAI class directly:
import os
from llama_index.llms.openai import OpenAI

llm = OpenAI(
    model="gpt-5.4",
    api_key=os.environ["AURIKO_API_KEY"],
    api_base="https://api.auriko.ai/v1",
)
For routing options, per-call overrides, and Auriko error mapping, use AurikoLlamaIndexLLM.

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Use AurikoAsyncOpenAI (experimental)

If your project pins a different llama-index-llms-openai version, pass AurikoAsyncOpenAI as the async_openai_client: 
from llama_index.llms.openai import OpenAI
from auriko import AurikoAsyncOpenAI

client = AurikoAsyncOpenAI()
llm = OpenAI(
    model="gpt-4o",
    async_openai_client=client,
    api_key="placeholder",
)
LlamaIndex’s OpenAI requires an api_key for construction. Pass any placeholder value.
Read client.last_routing_metadata after each call. See AurikoAsyncOpenAI for the full class reference.