vaklm was created to simplify intecctions with OpenAI-compatible APIs, providing a cleaner alternative to the verbose client.chat.completions.create pattern. This Python client offers a more intuitive interface while adding valuable reasoning capabilities to API responses.

vaklm is designed to make working with AI APIs more efficient and developer-friendly, providing an easy way to interact with OpenAI-compatible API endpoints while supporting reasoning capabilities.

Installation

pip install vaklm

Usage

Basic Usage

from vaklm import vaklm, VAKLMException

try: content, reasoning = vaklm( endpoint=“http://localhost:11434/v1/chat/completions”, model_name=“llama3.2:latest”, user_prompt=“Explain quantum computing in simple terms”, system_prompt=“You are a helpful AI assistant”, api_key=“YOUR_API_KEY”, temperature=0.7 ) print(“Content:”, content) print(“Reasoning:”, reasoning) except VAKLMException as e: print(f”Error: {str(e)}“)

Streaming Usagepython

from vaklm import vaklm

print(“\nStreaming example:”) try: for content, reasoning in vaklm( endpoint=“http://localhost:11434/v1/chat/completions”, model_name=“llama3.2:latest”, user_prompt=“Write a short story about a cat.”, system_prompt=“You are a creative writer.”, api_key=“YOUR_API_KEY”, stream=True, temperature=0.7 ): print(content, end=”, flush=True) if reasoning: print(f”\n[Reasoning: {reasoning}]”) except VAKLMException as e: print(f”Error: {str(e)}”)

## Features
- Supports both streaming and non-streaming responses
- Includes reasoning content in responses
- Automatic retry logic for failed requests
- Configurable temperature and max tokens
- System prompt support for context setting
- Comprehensive error handling

## Configuration
The `vaklm` function accepts the following parameters:

- `endpoint`: API endpoint URL (required)
- `model_name`: Model identifier (required)
- `user_prompt`: User's input message (required)
- `system_prompt`: Optional system context message
- `api_key`: API key for authentication
- `stream`: Whether to stream the response (default: False)
- `temperature`: Sampling temperature (0-2, default: 1.0)
- `max_tokens`: Maximum tokens to generate
- `timeout`: Request timeout in seconds (default: 30)
- `max_retries`: Maximum retry attempts (default: 3)
- `retry_delay`: Base delay between retries (default: 1.0)

## Error Handling
The client raises `VAKLMException` for general errors, with specific subclasses:
- `APIError`: For API-specific errors
- `StreamingError`: For streaming-specific errors

Always wrap calls in try/except blocks to handle potential errors.


`vaklm` provides a cleaner, more intuitive way to work with OpenAI-compatible APIs while adding valuable reasoning capabilities. By simplifying the API interaction pattern and adding features like automatic retries and streaming support, VAKLM helps developers focus on building great AI-powered applications rather than wrestling with API boilerplate. Give it a try in your next project and experience the difference!