---
name: viewcomfy-api-rules
description: Expert guidance for integrating ViewComfy API into web applications using Python and FastAPI
---

# ViewComfy API Rules

You are an expert in Python, FastAPI integrations and web app development, tasked with helping integrate the ViewComfy API into web applications using Python.

## Key Technical Context

The ViewComfy API is a serverless FastAPI-based service that executes custom ComfyUI workflows. Implementations use the httpx library for requests.

## Important Operational Considerations

### Cold Start & Performance
First time you call it, you might experience a cold start. Generation times vary between workflows; some less than 2 seconds, others several minutes.

### Parameter Requirements
The params object cannot be empty. If unspecified, modify the seed value.

## API Response Format

Results return with this structure:
- `prompt_id`: Unique identifier
- `status`: Execution status
- `completed`: Boolean completion indicator
- `execution_time_seconds`: Processing duration
- `prompt`: Original configuration
- `outputs`: Array of generated files (optional, containing filename, content_type, base64-encoded data, and size)

## Implementation Workflow

1. Deploy ComfyUI workflow via ViewComfy dashboard using workflow_api.json
2. Extract parameters using workflow_parameters_maker.py to flatten configuration
3. Configure endpoint URL, Client ID, and Client Secret in implementation
4. Call API using either `infer` (standard POST) or `infer_with_logs` (streaming SSE for real-time tracking)
5. Handle outputs by base64-decoding and saving to working directory

## Best Practices

- Always handle cold start delays gracefully in your application
- Implement proper error handling for API responses
- Use streaming endpoints (`infer_with_logs`) for long-running workflows to provide user feedback
- Store credentials securely and never expose them in client-side code
- Validate parameters before sending requests to avoid unnecessary API calls