simplemodelrouter 0.1.1

A Python library for interfacing with various LLM inference endpoints

SimpleModelRouter

A Python library for interfacing with various Large Language Model (LLM) inference endpoints, including OpenAI, Anthropic, and Ollama. The library provides a unified, async-first interface for interacting with different LLM providers.

Features

• Support for multiple LLM providers:
  • OpenAI (GPT-3.5, GPT-4)
  • Anthropic (Claude)
  • Ollama (Local models)
• Async HTTP support using httpx
• Streaming responses for real-time text generation
• Unified interface across providers
• Type hints and comprehensive documentation
• Configurable API endpoints and models
• Error handling and retries
• Resource cleanup and connection management

Installation

Using pip

pip install simplemodelrouter

Using Poetry (recommended)

poetry add simplemodelrouter

For development:

# Clone the repository
git clone https://github.com/yourusername/simplemodelrouter.git
cd simplemodelrouter

# Install Poetry if you haven't already
curl -sSL https://install.python-poetry.org | python3 -

# Install dependencies including development tools
poetry install

Quick Start

import asyncio
from simplemodelrouter import OpenAIProvider, Message

async def main():
    provider = OpenAIProvider(api_key="your-api-key")
    messages = [Message(role="user", content="Hello!")]
    
    response = await provider.chat(messages)
    print(response.message.content)
    
    await provider.close()

asyncio.run(main())

Detailed Usage

Provider Configuration

Each provider can be configured with:

• API key (required for OpenAI and Anthropic)
• Base URL (optional, for custom deployments)
• Default model (optional)

# OpenAI with custom configuration
openai = OpenAIProvider(
    api_key="your-api-key",
    base_url="https://api.custom-deployment.com/v1",
    default_model="gpt-4"
)

# Anthropic with default configuration
anthropic = AnthropicProvider(
    api_key="your-api-key"
)

# Ollama for local deployment
ollama = OllamaProvider(
    base_url="http://localhost:11434",
    default_model="llama2"
)

Chat Interface

The chat interface supports conversations with multiple messages:

messages = [
    Message(role="system", content="You are a helpful assistant."),
    Message(role="user", content="What's the weather like?"),
    Message(role="assistant", content="I don't have access to current weather data."),
    Message(role="user", content="What can you help me with?")
]

response = await provider.chat(
    messages=messages,
    temperature=0.7,
    stream=False
)

Streaming Responses

All providers support streaming for both chat and completion endpoints:

async for chunk in await provider.chat(messages, stream=True):
    print(chunk.message.content, end="", flush=True)

async for chunk in await provider.complete(prompt, stream=True):
    print(chunk.text, end="", flush=True)

Error Handling

The library provides consistent error handling across providers:

try:
    response = await provider.chat(messages)
except httpx.HTTPStatusError as e:
    print(f"API error: {e.response.status_code}")
except httpx.RequestError as e:
    print(f"Network error: {str(e)}")
finally:
    await provider.close()

Resource Management

Always close providers when done to clean up resources:

try:
    provider = OpenAIProvider(api_key="your-api-key")
    # ... use provider ...
finally:
    await provider.close()

Or use async context managers (coming soon):

async with OpenAIProvider(api_key="your-api-key") as provider:
    response = await provider.chat(messages)

Examples

Check out the examples/ directory for more detailed examples:

• chat_comparison.py: Compare responses from different providers
• streaming_example.py: Demonstrate streaming capabilities
• error_handling.py: Show error handling scenarios

Development

1. Clone the repository:

   git clone https://github.com/yourusername/simplemodelrouter.git
   cd simplemodelrouter
   

2. Install Poetry:

   curl -sSL https://install.python-poetry.org | python3 -
   

3. Install dependencies:

   poetry install
   

4. Activate the virtual environment:

   poetry shell
   

5. Run tests:

   poetry run pytest
   

6. Format code:

   poetry run black simplemodelrouter
   poetry run isort simplemodelrouter
   

7. Type check:

   poetry run mypy simplemodelrouter
   

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License