llms.txt

# OpenAI Model Registry

> Python library and CLI for OpenAI model capabilities, parameter validation, pricing data, and provider management (OpenAI, Azure). Includes GPT-5 family, automated updates, and comprehensive model metadata.

Installation: `pip install openai-model-registry`. Python 3.10+ required. Auto-updates model data from GitHub releases.

## Python API Complete Reference

```python
from openai_model_registry import ModelRegistry, ModelCapabilities, WebSearchBilling
registry = ModelRegistry()  # Auto-loads latest data

# Core model access
caps = registry.get_capabilities("gpt-5")  # Returns ModelCapabilities
models_dict = registry.models  # Dict[str, ModelCapabilities] - all models

# ModelCapabilities properties (all available attributes):
caps.model_name           # str: registry model name
caps.openai_model_name    # str: OpenAI API model name
caps.context_window       # int: max context tokens
caps.max_output_tokens    # int: max output tokens
caps.deprecation          # DeprecationInfo: deprecation status/dates
caps.supports_vision      # bool: image inputs
caps.supports_functions   # bool: function calling
caps.supports_streaming   # bool: streaming responses
caps.supports_structured  # bool: structured outputs
caps.supports_web_search  # bool: web search capability
caps.supports_audio      # bool: audio inputs
caps.supports_json_mode   # bool: JSON mode
caps.pricing             # PricingInfo: cost per token
caps.input_modalities    # List[str]: ['text', 'image', 'audio']
caps.output_modalities   # List[str]: ['text', 'image', 'audio']
caps.min_version         # ModelVersion: minimum API version
caps.aliases            # List[str]: alternative model names
caps.inline_parameters   # Dict[str, Any]: parameter constraints
caps.web_search_billing  # WebSearchBilling: web search costs
caps.is_sunset          # bool: model is sunset
caps.is_deprecated      # bool: model is deprecated/sunset

# Parameter validation
registry.validate_parameters("gpt-4o", {"temperature": 0.7, "max_tokens": 1000})
caps.validate_parameter("temperature", 0.7)  # Single parameter
caps.validate_parameters({"temperature": 0.7, "max_tokens": 1000})  # Multiple

# Constraint access
constraint = caps.get_constraint("temperature")  # NumericConstraint/EnumConstraint/ObjectConstraint
constraint = registry.get_parameter_constraint("numeric_constraints.temperature")

# Pricing details
pricing = caps.pricing  # PricingInfo object
pricing.scheme          # str: "per_token"
pricing.unit           # str: "1M tokens"
pricing.input_cost_per_unit   # float: input cost per unit
pricing.output_cost_per_unit  # float: output cost per unit
pricing.currency       # str: "USD"

# Web search billing (if available)
ws_billing = caps.web_search_billing  # WebSearchBilling or None
ws_billing.call_fee_per_1000          # float: fee per 1000 calls
ws_billing.content_token_policy       # "included_in_call_fee" or "billed_at_model_rate"
ws_billing.currency                   # str: "USD"
ws_billing.notes                      # Optional[str]

# Data management
registry.list_providers()             # List[str]: available providers
registry.dump_effective()             # Dict: full merged dataset
registry.get_data_info()             # Dict: data sources/versions
registry.get_data_version()          # Optional[str]: current data version
registry.clear_cache()               # Clear cached data
registry.get_raw_data_paths()        # Dict: paths to data files
registry.get_bundled_data_content("models.yaml")  # str: file content
registry.get_raw_model_data("gpt-5") # Dict: raw model data without overrides

# Updates
registry.check_for_updates()         # RefreshResult: update status
registry.check_data_updates()        # bool: updates available
registry.get_update_info()           # UpdateInfo: detailed update info
registry.update_data(force=True)     # bool: apply updates
registry.manual_update_workflow()    # bool: interactive update

# Deprecation handling
registry.assert_model_active("gpt-5")  # Raises ModelSunsetError if sunset
headers = registry.get_sunset_headers("gpt-5")  # Dict: HTTP deprecation headers
```

## CLI Complete Command Reference

```bash
# Model commands
omr models list [OPTIONS]
  --format {table,json,yaml}    # Output format
  --filter TEXT                 # Filter by model name pattern
  --columns LIST               # Comma-separated column names
  --show-deprecated           # Include deprecated models
  --show-sunset              # Include sunset models
  --provider {openai,azure}   # Provider to use

omr models get MODEL [OPTIONS]
  --format {table,json,yaml}   # Output format
  --parameters-only           # Show only parameters
  --effective                 # Show effective (merged) data
  --raw                      # Show raw data without overrides
  --provider {openai,azure}   # Provider to use

# Data commands
omr data paths                 # Show all data file locations
omr data env                   # Show environment variables
omr data dump [OPTIONS]
  --format {json,yaml}         # Output format
  --provider {openai,azure}    # Provider to use
  --effective                  # Show merged data (default)
  --raw                       # Show raw data without overrides

# Provider commands
omr providers list             # List available providers
omr providers current          # Show current provider

# Update commands
omr update check              # Check for available updates
omr update apply              # Apply available updates
omr update refresh            # Force refresh from remote
omr update show-config        # Show update configuration

# Cache commands
omr cache info               # Show cache information
omr cache clear [FILES...]   # Clear cache files

# Global options (all commands)
--help-json                  # JSON help output
--provider {openai,azure}    # Override provider
--verbose                    # Verbose output
--debug                     # Debug output

# Environment variable usage
OMR_PROVIDER=azure omr models list
OMR_DEBUG=1 omr models get gpt-5
OMR_MODEL_REGISTRY_PATH=/custom/path omr data dump

# JSON automation examples
omr models list --format json | jq '.[] | select(.name | contains("gpt-5"))'
omr models get gpt-4o --format json --parameters-only | jq '.parameters'
omr data dump --format json | jq '.models | keys | length'  # Count models
```

## Environment Variables

- `OMR_PROVIDER`: Set provider (openai, azure)
- `OMR_MODEL_REGISTRY_PATH`: Custom data file path
- `OMR_DATA_DIR`: Custom data directory
- `OMR_DISABLE_DATA_UPDATES`: Disable auto-updates
- `OMR_DATA_VERSION_PIN`: Pin to specific data version

## Model Coverage

GPT-5 family: gpt-5, gpt-5-mini, gpt-5-nano, gpt-5-chat-latest
GPT-4o family: gpt-4o, gpt-4o-mini, gpt-4o-search-preview variants
GPT-4.1 family: gpt-4.1, gpt-4.1-mini, gpt-4.1-nano (1M context)
O-series: o1, o3, o4-mini (reasoning models with reasoning_effort parameter)
Legacy: gpt-4-turbo, gpt-3.5-turbo variants with deprecation tracking

## Error Handling

```python
from openai_model_registry import (
    ModelNotSupportedError,
    ParameterValidationError,
    ModelSunsetError
)

try:
    caps = registry.get_capabilities("invalid-model")
except ModelNotSupportedError as e:
    print(f"Model not found: {e}")

try:
    registry.validate_parameters("gpt-4o", temperature=2.5)  # Invalid
except ParameterValidationError as e:
    print(f"Invalid parameter: {e}")
```

## Data Structure

Models stored in `data/models.yaml` with provider overrides in `data/overrides.yaml`. Schema includes:
- context_window, max_output_tokens, supports_streaming
- input_modalities, output_modalities
- pricing (scheme, unit, input_cost_per_unit, output_cost_per_unit)
- parameters (inline constraints: temperature, max_tokens, etc.)
- deprecation info, release_date, description

## Resources

- [Python API Reference](https://yaniv-golan.github.io/openai-model-registry/api/model-registry/): Complete API documentation
- [CLI Commands](https://yaniv-golan.github.io/openai-model-registry/user-guide/cli/): Full CLI reference
- [Basic Usage Example](examples/basic_usage.py): Working Python code
- [CLI Integration Example](examples/cli_integration.py): Subprocess patterns

## Optional

- [Advanced Usage](https://yaniv-golan.github.io/openai-model-registry/user-guide/advanced-usage/): Provider overrides, data inspection
- [Testing Guide](https://yaniv-golan.github.io/openai-model-registry/user-guide/testing/): Mock patterns, pyfakefs usage