openai-model-registry 0.6.1

Registry for OpenAI models with capability and parameter validation

OpenAI Model Registry

A Python package that provides information about OpenAI models and validates parameters before API calls.

📚 View the Documentation

What This Package Does

• Helps you avoid invalid API calls by validating parameters ahead of time
• Provides accurate information about model capabilities (context windows, token limits)
• Handles model aliases and different model versions
• Works offline with locally stored model information
• Keeps model information up-to-date with optional updates

Installation

pip install openai-model-registry

Simple Example

from openai_model_registry import ModelRegistry

# Get information about a model
registry = ModelRegistry.get_instance()
model = registry.get_capabilities("gpt-4o")

# Access model limits
print(f"Context window: {model.context_window} tokens")
print(f"Max output: {model.max_output_tokens} tokens")

# Check if parameter values are valid
model.validate_parameter("temperature", 0.7)  # Valid - no error
try:
    model.validate_parameter("temperature", 3.0)  # Invalid - raises ValueError
except ValueError as e:
    print(f"Error: {e}")

# Check model features
if model.supports_structured:
    print("This model supports Structured Output")

Practical Use Cases

Validating Parameters Before API Calls

def call_openai(model, messages, **params):
    # Validate parameters before making API call
    capabilities = registry.get_capabilities(model)
    for param_name, value in params.items():
        capabilities.validate_parameter(param_name, value)

    # Now make the API call
    return client.chat.completions.create(model=model, messages=messages, **params)

Managing Token Limits

def prepare_prompt(model_name, prompt, max_output=None):
    capabilities = registry.get_capabilities(model_name)

    # Use model's max output if not specified
    max_output = max_output or capabilities.max_output_tokens

    # Calculate available tokens for input
    available_tokens = capabilities.context_window - max_output

    # Ensure prompt fits within available tokens
    return truncate_prompt(prompt, available_tokens)

Key Features

• Model Information: Get context window size, token limits, and supported features
• Parameter Validation: Check if parameter values are valid for specific models
• Version Support: Works with date-based models (e.g., "o3-mini-2025-01-31")
• Offline Usage: Functions without internet using local registry data
• Updates: Optional updates to keep model information current

Command Line Usage

Update your local registry data:

openai-model-registry-update

Configuration

The registry uses local files for model information:

# Default locations (XDG Base Directory spec)
Linux: ~/.config/openai-model-registry/
macOS: ~/Library/Application Support/openai-model-registry/
Windows: %LOCALAPPDATA%\openai-model-registry\

You can specify custom locations:

import os

# Use custom registry files
os.environ["MODEL_REGISTRY_PATH"] = "/path/to/custom/models.yml"
os.environ["PARAMETER_CONSTRAINTS_PATH"] = "/path/to/custom/parameter_constraints.yml"

# Then initialize registry
from openai_model_registry import ModelRegistry
registry = ModelRegistry.get_instance()

Documentation

For more details, see:

• Getting Started Guide
• API Reference
• Examples

Development

# Install dependencies (requires Poetry)
poetry install

# Run tests
poetry run pytest

# Run linting
poetry run pre-commit run --all-files

License

MIT License - See LICENSE for details.