# ComfyUI-ImageToPrompt

A custom ComfyUI node that sends images to OpenAI-compatible vision APIs (like GPT-4 Vision, LLaVA, etc.) and returns the LLM's text response. Perfect for image analysis, captioning, and visual question answering workflows.

## Features

- 📷 **Upload images** via ComfyUI's image input nodes
- 🤖 **Send to any OpenAI-compatible API** (GPT-4 Vision, local LLaVA, llama.cpp, etc.)
- 💬 **Optional system and user prompts** for controlling the analysis
- ⚙️ **Configurable parameters**: temperature, max tokens, model selection
- 📝 **Text output** that can be used in downstream nodes or displayed in the UI
- 🔍 **Debug logging** to monitor API calls and responses

## Installation

### Prerequisites

- [ComfyUI](https://github.com/comfyanonymous/ComfyUI) installed and working

### Install via ComfyUI Manager (Recommended)

1. Open ComfyUI Manager
2. Search for "ComfyUI-ImageToPrompt"
3. Click Install
4. Restart ComfyUI

### Manual Installation

1. Navigate to your ComfyUI custom nodes directory:
   ```bash
   cd ComfyUI/custom_nodes/
   ```

2. Clone this repository:
   ```bash
   git clone https://github.com/yourusername/ComfyUI-ImageToPrompt.git
   ```

3. Install dependencies:
   ```bash
   cd ComfyUI-ImageToPrompt
   pip install -r requirements.txt
   ```

4. Restart ComfyUI

## Usage

1. **Add the node**: In ComfyUI, add the "Image to LLM Prompt" node (found under the "LLM" category)

2. **Connect an image**: Connect an image output (from LoadImage, etc.) to the node's image input

3. **Configure the API**:
   - `base_url`: Your OpenAI-compatible API endpoint (e.g., `http://localhost:8080/v1`)
   - `api_key`: Your API key (use `sk-test` for local servers that don't require authentication)
   - `model`: Model name (e.g., `gpt-4o`, `llava`, etc.)

4. **Add prompts (optional)**:
   - `system_prompt`: Instructions for the AI (e.g., "You are an expert art critic")
   - `user_prompt`: Specific question about the image (e.g., "Describe this image in detail")

5. **Adjust parameters (optional)**:
   - `temperature`: Controls randomness (0.0 = deterministic, 2.0 = very random)
   - `max_tokens`: Maximum response length

6. **Execute the workflow**: The LLM's response will appear in the node's output and can be passed to other nodes

## Example Workflow

```
LoadImage → ImageToLLMPrompt → (use text output in other nodes)
```

The node outputs a STRING that can be connected to:
- Text processing nodes
- Prompt nodes for image generation
- File writing nodes
- Any node that accepts STRING input

## API Compatibility

This node works with any OpenAI-compatible vision API endpoint, including:

- **OpenAI GPT-4 Vision** (`https://api.openai.com/v1`)
- **Local LLaVA servers** (via llama.cpp, ollama, etc.)
- **Azure OpenAI** with vision models
- **Other compatible backends**

## Configuration Examples

### OpenAI GPT-4 Vision
```
base_url: https://api.openai.com/v1
api_key: sk-your-actual-api-key
model: gpt-4o
```

### Local LLaVA (llama.cpp server)
```
base_url: http://localhost:8080/v1
api_key: sk-test
model: llava
```

## Troubleshooting

- **"LLM API call failed" errors**: Check that your base_url is correct and the server is running
- **Empty responses**: Verify your model supports vision/image inputs
- **Timeout errors**: Increase the timeout in the code or use a faster model
- **Node not appearing**: Restart ComfyUI and check the console for import errors

## Dependencies

- `openai` - OpenAI Python client library
- `pillow` - Python Imaging Library for image processing
- `numpy` - Array processing (typically already installed with ComfyUI)

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.