Get APIs

Public endpoints for discovery and metadata

Public GET APIs

These public endpoints allow you to programmatically discover available models, get schemas, and download integration code - all without authentication.

GET /api/models

List all models →

GET /api/schema/:cat/:sub

Get model schema →

GET /api/openai-function/:cat/:sub

Download OpenAI function →

GET /api/comfyui-node/:cat/:sub

Download ComfyUI node →

Get All Models

GET/api/models

Retrieve a complete list of all available AI models with their categories, subcategories, and endpoints.

Request

curl -X GET https://api.genvrresearch.com/api/models

Response

{
  "success": true,
  "count": 25,
  "data": [
    {
      "name": "Flux Dev",
      "category": "imagegen",
      "subcategory": "flux_dev",
      "description": "High-quality image generation",
      "endpoint": {
        "generate": "/api/v1/generate",
        "status": "/api/v1/status",
        "response": "/api/v1/response"
      },
      "documentation": "https://api.genvrresearch.com/imagegen/flux_dev",
      "preview": "https://app.genvrresearch.com/imagegen/flux_dev"
    },
    // ... more models
  ],
  "message": "Models retrieved successfully"
}

Response Fields

name- Model display name

category- Model category (e.g., "imagegen")

subcategory- Model identifier (e.g., "flux_dev")

documentation- Link to full API documentation

preview- Link to live demo

Get Model Schema

GET/api/schema/:category/:subcategory

Retrieve the input schema and parameter definitions for a specific model.

Request

curl -X GET https://api.genvrresearch.com/api/schema/imagegen/flux_dev

Response

{
  "success": true,
  "data": {
    "category": "imagegen",
    "subcategory": "flux_dev",
    "parameters": {
      "required": [
        {
          "name": "prompt",
          "type": "string",
          "description": "Text description of the image to generate"
        }
      ],
      "optional": [
        {
          "name": "aspect_ratio",
          "type": "enum",
          "default": "1:1",
          "allowedValues": ["1:1", "16:9", "21:9", "4:5", "9:16"],
          "description": "Image aspect ratio"
        },
        {
          "name": "num_outputs",
          "type": "integer",
          "default": 1,
          "minimum": 1,
          "maximum": 4,
          "description": "Number of images to generate"
        }
      ]
    }
  },
  "message": "Schema retrieved successfully"
}

Download OpenAI Function

GET/api/openai-function/:category/:subcategory

Download a ready-to-use OpenAI function schema with complete implementation for a specific model.

Example

curl -X GET https://api.genvrresearch.com/api/openai-function/imagegen/flux_dev \
  -o flux_dev_openai_function.py

Returns

A Python file containing:

• OpenAI function definition (JSON schema)
• Complete execution function
• GenVR API integration code
• Usage example with OpenAI SDK

Download ComfyUI Node

GET/api/comfyui-node/:category/:subcategory

Download a custom ComfyUI node with complete GenVR API integration for a specific model.

Example

curl -X GET https://api.genvrresearch.com/api/comfyui-node/imagegen/flux_dev \
  -o genvr_imagegen_flux_dev_comfyui.py

Returns

A Python file containing:

• ComfyUI node class definition
• Dynamic input/output schema
• Complete GenVR API integration
• Error handling and status logging
• Installation instructions

Use Cases

Dynamic Model Selection

Fetch the list of available models to build dynamic UI dropdowns or model selectors in your application.

Form Generation

Use the schema endpoint to automatically generate input forms with validation based on each model's parameters.

Model Discovery

Allow users to explore and discover new models programmatically without visiting the documentation.

Validation & Testing

Validate user inputs against the schema before sending requests to ensure all required parameters are provided.

Example Usage

JavaScript Example

// Get all available models
const modelsResponse = await fetch('https://api.genvrresearch.com/api/models');
const modelsData = await modelsResponse.json();

console.log(`Found ${modelsData.count} models`);

// Get schema for a specific model
const category = modelsData.data[0].category;
const subcategory = modelsData.data[0].subcategory;

const schemaResponse = await fetch(
  `https://api.genvrresearch.com/api/schema/${category}/${subcategory}`
);
const schemaData = await schemaResponse.json();

console.log('Required parameters:', schemaData.data.parameters.required);
console.log('Optional parameters:', schemaData.data.parameters.optional);

// Build request dynamically based on schema
const requestBody = {
  uid: 'YOUR_USER_ID',
  category: category,
  subcategory: subcategory,
};

// Add required parameters
schemaData.data.parameters.required.forEach(param => {
  requestBody[param.name] = getValueForParameter(param);
});

// Make the generation request
const generateResponse = await fetch('https://api.genvrresearch.com/api/v1/generate', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer YOUR_API_KEY'
  },
  body: JSON.stringify(requestBody)
});