indoxrouter

IndoxRouter

A unified client for various AI providers, including OpenAI, anthropic, Google, and Mistral.

Features

• Unified API: Access multiple AI providers through a single API
• Simple Interface: Easy-to-use methods for chat, completion, embeddings, image generation, and text-to-speech
• Error Handling: Standardized error handling across providers
• Authentication: Secure cookie-based authentication

Installation

pip install indoxrouter

Usage

Initialization

from indoxrouter import Client

# Initialize with API key
client = Client(api_key="your_api_key")

# Using environment variables
# Set INDOX_ROUTER_API_KEY environment variable
import os
os.environ["INDOX_ROUTER_API_KEY"] = "your_api_key"
client = Client()

Authentication

IndoxRouter uses cookie-based authentication with JWT tokens. The client handles this automatically by:

• Taking your API key and exchanging it for JWT tokens using the server's authentication endpoints
• Storing the JWT tokens in cookies
• Using the cookies for subsequent requests
• Automatically refreshing tokens when they expire

# Authentication is handled automatically when creating the client
client = Client(api_key="your_api_key")

Chat Completions

response = client.chat(
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Tell me a joke."}
    ],
    model="openai/gpt-4o-mini",  # Provider/model format
    temperature=0.7
)

print(response["data"])

Text Completions

response = client.completion(
    prompt="Once upon a time,",
    model="openai/gpt-4o-mini",
    max_tokens=100
)

print(response["data"])

Embeddings

response = client.embeddings(
    text=["Hello world", "AI is amazing"],
    model="openai/text-embedding-3-small"
)

print(f"Dimensions: {len(response['data'][0]['embedding'])}")
print(f"First embedding: {response['data'][0]['embedding'][:5]}...")

Image Generation

# OpenAI Image Generation
response = client.images(
    prompt="A serene landscape with mountains and a lake",
    model="openai/dall-e-3",
    size="1024x1024",
    quality="standard",  # Options: standard, hd
    style="vivid"  # Options: vivid, natural
)

print(f"Image URL: {response['data'][0]['url']}")


# Access base64 encoded image data
if "b64_json" in response["data"][0]:
    b64_data = response["data"][0]["b64_json"]
    # Use the base64 data (e.g., to display in HTML or save to file)

Text-to-Speech

# Generate audio from text
response = client.text_to_speech(
    input="Hello, welcome to IndoxRouter!",
    model="openai/tts-1",
    voice="alloy",  # Options: alloy, echo, fable, onyx, nova, shimmer
    response_format="mp3",  # Options: mp3, opus, aac, flac
    speed=1.0  # Range: 0.25 to 4.0
)

print(f"Audio generated successfully: {response['success']}")
print(f"Audio data available: {'data' in response}")

Streaming Responses

for chunk in client.chat(
    messages=[{"role": "user", "content": "Write a short story."}],
    model="openai/gpt-4o-mini",
    stream=True
):
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

Getting Available Models

# Get all providers and models
providers = client.models()
for provider in providers:
    print(f"Provider: {provider['name']}")
    for model in provider["models"]:
        print(f"  - {model['id']}: {model['description'] or ''}")

# Get models for a specific provider
openai_provider = client.models("openai")
print(f"OpenAI models: {[m['id'] for m in openai_provider['models']]}")

License

This project is licensed under the MIT License - see the LICENSE file for details.