Retrieves detailed information about a specific machine learning application template from the catalog. The response includes the application’s metadata, documentation, tags, and a complete set of components with configuration options, compatible flavors, and deployment capabilities — all necessary for building and customizing an AI application.
API key for authentication. Make sure to include the word apikey, followed by a single space and then your token.
Example: apikey 1234$abcdef
Name of application in catalog
OK
Configurable components of the application
{
"model": {
"description": "Llama 3.2 1B is a multilingual large language model developed by Meta.",
"display_name": "Llama 3.2 1B",
"exposable": true,
"license_url": "https://example.com/license",
"parameters": {
"prefix_cache": {
"default_value": "1",
"description": "Controls automatic prefix caching; set to 1 to speed up inference for repetitive prompts, or 0 to disable for diverse inputs.",
"display_name": "prefix_cache",
"examples": ["0", "1"]
}
},
"readme": "Detailed documentation",
"required": true,
"suitable_flavors": [
{
"name": "inference-16vcpu-232gib-1xh100-80gb"
}
]
}
}URL to the application's cover image
"https://cdn.example.com"
Brief overview of the application
"This is a demo application"
Human-readable name of the application
"Llama-3.2-1B-Instruct"
Unique application identifier in the catalog
"demo-app"
Detailed documentation or instructions
"Detailed documentation"
Categorization key-value pairs
{
"category": "Model",
"model_docs_endpoint": "/docs",
"model_inference_engine": "vllm",
"model_owner": "Meta",
"model_type": "Text Generation"
}