Metadata-Version: 2.4
Name: aihuber
Version: 0.2.0
Summary: ⚡ Python AI SDK - OpenAI, MistralAI, Anthropic, Google Gemini, XAI Grok, Hugging Face
Project-URL: homepage, https://github.com/sylvainmouquet/aihuber
Project-URL: documentation, https://github.com/sylvainmouquet/aihuber
Project-URL: repository, https://github.com/sylvainmouquet/aihuber
Project-URL: changelog, https://github.com/sylvainmouquet/aihuber/releases
Author-email: Sylvain Mouquet <sylvain.mouquet@gmail.com>
License: MIT
License-File: LICENSE
Keywords: llm,python
Classifier: Development Status :: 5 - Production/Stable
Classifier: Framework :: Pytest
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.13
Requires-Dist: asgi-lifespan>=2.1.0
Requires-Dist: jinja2>=3.1.6
Requires-Dist: nest-asyncio>=1.6.0
Requires-Dist: proxycraft
Description-Content-Type: text/markdown

# AIHuber

__aihuber__ is the easiest and quickest way to communicate with AI providers. 
Free and open-source.


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## ✨ Features

__aihuber__ is compatible with main AI providers :

### Chat completion (Text generation)

##### AI Providers Comparison

| AI Provider | Buffering sync & async | Streaming (sync & async) | Endpoint                                                                                                                     |
|-------------|------------------------|--------------------------|------------------------------------------------------------------------------------------------------------------------------|
| OpenAI | ✅ | ✅ | `https://api.openai.com/v1/chat/completions`                                                                                 |
| Mistral AI | ✅ | ✅ | `https://api.mistral.ai/v1/chat/completions`                                                                                 |
| Anthropic | ✅ | ✅ | `https://api.anthropic.com/v1/messages`                                                                                      |
| Google (Gemini) | ❌ | ❌ | `https://generativelanguage.googleapis.com/v1/models/{model}:generateContent`                                                |
| Cohere | ✅ | ✅ | `https://api.cohere.com/v2/chat`                                                                                             |
| Together AI | ✅ | ✅ | `https://api.together.xyz/v1/chat/completions`                                                                               |
| Replicate | ❌ | ❌ | `https://api.replicate.com/v1/predictions`                                                                                   |
| Hugging Face | ❌ | ❌ | `https://api-inference.huggingface.co/models/{model_id}`                                                                     |
| Azure OpenAI | ❌ | ❌ | `https://{your-resource-name}.openai.azure.com/openai/deployments/{deployment-name}/chat/completions?api-version=2024-02-01` |
| AWS Bedrock | ❌ | ❌ | `https://bedrock-runtime.{region}.amazonaws.com/model/{model-id}/invoke`                                                     |
| Perplexity | ✅ | ✅ | `https://api.perplexity.ai/chat/completions`                                                                                 |
| xAI (Grok) | ❌ | ❌ | `https://api.x.ai/v1/chat/completions`                                                                                       |

## Legend

- ✅ = Available
- ❌ = Not Available
- Text in parentheses = Specific service/model name

## 🚀 Quick Start

## Installation

```bash
pip install aihuber
```

Or with uv:

```bash
uv add aihuber
```

### Basic Usage

```python
import asyncio
import os

from dotenv import load_dotenv

from aihuber import LLM, Message
from pydantic import SecretStr

load_dotenv()

MISTRAL_AI_TOKEN = SecretStr(os.getenv("MISTRAL_AI_TOKEN"))  # type: ignore


async def main():
    """Chat completion example with asynchronous"""
    llm = LLM(model="mistral:mistral-small-latest", api_key=MISTRAL_AI_TOKEN)

    messages = [
        Message(role="system", content="You are a helpful Python developer assistant."),
        Message(role="user", content="Give me 10 numbers from 0"),
    ]

    async_chat_completion = await llm.chat_completion_async(messages, stream=True)
    async for chunk in async_chat_completion:
        print(chunk)

if __name__ == "__main__":
    asyncio.run(main())
```

## 🐳 Docker Usage


```bash
docker build -t aihuber -f dockerfiles/aihuber.Dockerfile .
docker run  -p 8080:8080 aihuber
```

## 📄 License

[MIT](LICENSE)