ComfyUI-EACloudNodes

KO | EN

gitlite — search

#javascript #python #hacktoberfest #ai #golang #go #machine-learning #rust #docker #macos #kubernetes #awesome-list #vue #pytorch

ComfyUI-EACloudNodes

(★ 9)

A collection of ComfyUI custom nodes for interacting with various cloud services, such as LLM providers Groq and OpenRouter. These nodes are designed to work with any ComfyUI instance, including cloud-hosted environments (such as MimicPC) where users may have limited system access.

ComfyUI-EACloudNodes Latest Version Download

Download Latest Version (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# ComfyUI-EACloudNodes

A collection of [ComfyUI](https://github.com/comfyanonymous/ComfyUI) custom nodes for interacting with various cloud services, such as LLM providers Groq and OpenRouter. These nodes are designed to work with any ComfyUI instance, including cloud-hosted environments where users may have limited system access.

**Note:** All nodes have been updated to ComfyUI v3 spec for enhanced reliability, validation, and features while maintaining backward compatibility with v1.

## Installation

Use [ComfyUI-Manager](https://github.com/ltdrdata/ComfyUI-Manager) or to manually install:

1. Clone this repository into your ComfyUI custom_nodes folder:
  ```bash
cd ComfyUI/custom_nodes
git clone https://github.com/EnragedAntelope/ComfyUI-EACloudNodes
  ```
2. Install required packages:
  ```bash
cd ComfyUI-EACloudNodes
pip install -r requirements.txt
  ```
3. Restart ComfyUI

## Current Nodes

### Common Features Across LLM Nodes
The following parameters are available in both OpenRouter and Groq nodes:

#### Common Parameters:
- `api_key`: ⚠️ Your API key (Note: key will be visible in workflows)
- `model`: Model selection (dropdown or identifier)
- `system_prompt`: Optional system context setting
- `user_prompt`: Main prompt/question for the model
- `temperature`: Controls response randomness (0.0-2.0)
- `top_p`: Nucleus sampling threshold (0.0-1.0)
- `frequency_penalty`: Token frequency penalty (-2.0 to 2.0)
- `presence_penalty`: Token presence penalty (-2.0 to 2.0)
- `response_format`: Choose between text or JSON object output
- `seed_mode`: Control reproducibility (Fixed, Random, Increment, Decrement)
- `max_retries`: Maximum retry attempts (0-5) for recoverable errors
- `image_input`: Optional image for vision-capable models
- `additional_params`: Optional JSON object for extra model parameters

#### Common Outputs:
- `response`: The model's generated text or JSON response
- `status`: Detailed information about the request, including model used and token counts
- `help`: Static help text with usage information and repository URL

### Groq Chat (v3)

Interact with Groq's API for ultra-fast inference with various LLM models. **Now fully compatible with ComfyUI v3 spec!**

#### Features:
- **ComfyUI v3 compatible** - Enhanced reliability and validation
- **Dynamic model fetching** - Model list automatically fetched from Groq API (5-min cache)
- High-speed inference with Groq's optimized hardware
- Comprehensive model selection including production and preview models
- Support for vision-capable models (Llama-4 Maverick and Scout)
- Real-time token usage tracking
- Automatic retry mechanism with exponential backoff
- Enhanced input validation
- Detailed tooltips for all parameters
- Debug mode for troubleshooting
- **ComfyUI v3 compatible** - Enhanced reliability and validation
- High-speed inference with Groq's optimized hardware
- Comprehensive model selection including production and preview models
- Support for vision-capable models (Llama-4 Maverick and Scout)
- Real-time token usage tracking
- Automatic retry mechanism with exponential backoff
- Enhanced input validation
- Detailed tooltips for all parameters
- Debug mode for troubleshooting

#### Available Models:

**Note:** Model list is dynamically fetched from Groq API when you provide your API key. Categories below are maintained for reference. Use ComfyUI's Refresh button to update the model list.

**Production Models** (Stable, recommended for production use):

**Production Models** (Stable, recommended for production use):
- `llama-3.1-8b-instant` - Fast 8B parameter model (560 T/sec)
- `llama-3.3-70b-versatile` - **Default** - Powerful 70B model (280 T/sec)
- `meta-llama/llama-guard-4-12b` - Safety and moderation model (1200 T/sec)
- `openai/gpt-oss-120b` - Large open-source GPT (500 T/sec)
- `openai/gpt-oss-20b` - Efficient open-source GPT (1000 T/sec)
- `whisper-large-v3` - Speech recognition model
- `whisper-large-v3-turbo` - Faster speech recognition

**Production Systems** (Agentic systems with tools):
- `groq/compound` - Multi-model system with tools
- `groq/compound-mini` - Lightweight agentic system

**Preview Models** (Experimental, for evaluation only):
- `meta-llama/llama-4-scout-17b-16e-instruct` - **Vision** (750 T/sec)
- `meta-llama/llama-prompt-guard-2-22m` - Prompt injection detection
- `meta-llama/llama-prompt-guard-2-86m` - Enhanced prompt guard
- `openai/gpt-oss-safeguard-20b` - Safety-focused model (1000 T/sec)
- `canopylabs/orpheus-arabic-saudi` - Arabic text-to-speech
- `canopylabs/orpheus-v1-english` - English text-to-speech
- `qwen/qwen3-32b` - Qwen 32B model (400 T/sec)

#### Parameters:
- `api_key`: ⚠️ Your Groq API key (Get from [console.groq.com/keys](https://console.groq.com/keys))
- `model`: Select from available models or choose "Manual Input" for custom models
- `manual_model`: Enter custom model identifier (only used when "Manual Input" is selected)
- `system_prompt`: Optional system context (disable for vision models)
- `user_prompt`: Main prompt/question for the model
- `send_system`: Toggle system prompt sending (must be 'no' for vision models)
- `temperature`: Controls response randomness (0.0-2.0)
  - Lower (0.0-0.3): More focused and deterministic
  - Higher (0.7-2.0): More creative and varied
- `top_p`: Nucleus sampling threshold (0.0-1.0)
  - Lower (0.0-0.3): More focused vocabulary
  - Higher (0.7-1.0): More diverse word selection
- `max_completion_tokens`: Maximum tokens to generate (1-131,072, varies by model)
- `frequency_penalty`: Reduce token frequency repetition (-2.0 to 2.0)
- `presence_penalty`: Encourage topic diversity (-2.0 to 2.0)
- `response_format`: Choose between "text" or "json_object" output
- `seed_mode`: Control reproducibility
  - `fixed`: Use seed_value for consistent outputs
  - `random`: New random seed each time
  - `increment`: Increase seed by 1 each run
  - `decrement`: Decrease seed by 1 each run
- `seed_value`: Seed for 'fixed' mode (0-9007199254740991)
- `max_retries`: Auto-retry attempts for recoverable errors (0-5)
- `debug_mode`: Enable detailed error messages and request debugging
- `image_input`: Optional image for vision models (Llama-4 only)
- `additional_params`: Extra model parameters in JSON format

#### Outputs:
- `response`: The model's generated text or JSON response
- `status`: Detailed request information including model, seed, and token counts
- `help`: Comprehensive help text with usage information

#### Vision Model Usage:
1. Select a vision-capable model (auto-detected from Groq API):
   - `meta-llama/llama-4-scout-17b-16e-instruct` (known vision model)
   - Other models with 'vision', 'vl', or '-4-' in their ID are auto-detected
2. Connect an image to the `image_input` parameter
3. Set `send_system` to "no" (vision models don't accept system prompts)
4. Describe what you want to know about the image in `user_prompt`
1. Select a vision-capable model:
   - `meta-llama/llama-4-maverick-17b-128e-instruct`
   - `meta-llama/llama-4-scout-17b-16e-instruct`
2. Connect an image to the `image_input` parameter
3. Set `send_system` to "no" (vision models don't accept system prompts)
4. Describe what you want to know about the image in `user_prompt`

#### Production vs Preview Models:
- **Production Models**: Stable, reliable, meet high standards for speed/quality. Recommended for production use.
- **Preview Models**: Experimental, intended for evaluation only. May be deprecated with short notice.

### OpenRouter Chat (v3)

Interact with OpenRouter's API to access various AI models for text and vision tasks. **Now fully compatible with ComfyUI v3 spec!**

#### Features:
- **ComfyUI v3 compatible** - Enhanced reliability and validation
- Access to multiple AI providers through a single API
- Comprehensive free model selection
- Vision model support (Llama 3.2, Llama 4 variants)
- JSON output support
- Automatic retry mechanism with exponential backoff
- Enhanced input validation
- Detailed tooltips for all parameters
- Debug mode for troubleshooting

#### Available Free Models:
**Meta Llama Models:**
- meta-llama/llama-3.3-70b-instruct:free - **Default**
- meta-llama/llama-3.3-8b-instruct:free
- meta-llama/llama-3.2-3b-instruct:free
- meta-llama/llama-3.2-1b-instruct:free
- meta-llama/llama-3.1-8b-instruct:free
- meta-llama/llama-4-maverick:free (**Vision**)
- meta-llama/llama-4-scout:free (**Vision**)
- meta-llama/llama-3.2-90b-vision-instruct:free (**Vision**)

**Google Models:**
- google/gemini-2.0-flash-exp:free
- google/gemma-3-27b-it:free
- google/gemma-2-27b-it:free
- google/gemma-2-9b-it:free
- google/gemma-2-2b-it:free
- google/gemini-flash-1.5-8b-exp:free

**Mistral Models:**
- mistralai/mistral-small-3.1:free
- mistralai/ministral-8b:free
- mistralai/ministral-3b:free
- mistralai/mistral-saba-24b:free
- mistralai/mistral-nemo:free
- mistralai/mistral-7b-instruct:free

**Qwen Models:**
- qwen/qwen3-72b:free
- qwen/qwen-2.5-72b-instruct:free
- qwen/qwen-2.5-coder-32b-instruct:free
- qwen/qwen-2.5-7b-instruct:free
- qwen/qwen-2-7b-instruct:free
- qwen/qwen2.5-vl-32b-instruct:free (**Vision**)
- qwen/qwen2-vl-7b-instruct:free (**Vision**)
- qwen/qvq-72b-preview:free (**Vision**)

**Microsoft Models:**
- microsoft/phi-4:free
- microsoft/phi-3.5-mini-128k-instruct:free
- microsoft/phi-3-medium-128k-instruct:free

**DeepSeek Models:**
- deepseek/deepseek-r1-zero:free
- deepseek/deepseek-r1-distill-llama-70b:free
- deepseek/deepseek-r1-distill-llama-8b:free
- deepseek/deepseek-r1-distill-qwen-32b:free
- deepseek/deepseek-r1-distill-qwen-14b:free
- deepseek/deepseek-r1-distill-qwen-7b:free
- deepseek/deepseek-r1-distill-qwen-1.5b:free
- deepseek/deepseek-chat:free
- deepseek/deepseek-reasoner:free
- deepseek/deepseek-coder:free
- sophosympatheia/deephermes-3-405b:free

**Nvidia Models:**
- nvidia/llama-3.1-nemotron-70b-instruct:free
- nvidia/nemotron-nano-12b-v2-vl:free (**Vision**)

**Other Models:**
- openchat/openchat-8b:free
- openchat/openchat-7b:free
- anthropic/claude-sonnet-4.5:free
- sophosympatheia/rogue-rose-103b-v0.6.0:free
- sophosympatheia/midnight-rose-70b-v1.0.5:free
- huggingfaceh4/zephyr-7b-beta:free

#### Parameters:
- `api_key`: ⚠️ Your OpenRouter API key (Get from [https://openrouter.ai/keys](https://openrouter.ai/keys))
- `model`: Select from free models or choose "Manual Input" for custom models
- `manual_model`: Enter custom model identifier (only used when "Manual Input" is selected)
- `base_url`: OpenRouter API endpoint URL (default: https://openrouter.ai/api/v1/chat/completions)
- `system_prompt`: Optional system context setting
- `user_prompt`: Main prompt/question for the model (required)
- `send_system`: Toggle system prompt on/off
- `temperature`: Controls response randomness (0.0-2.0)
  - Lower (0.0-0.3): More focused and deterministic
  - Higher (0.7-2.0): More creative and varied
- `top_p`: Nucleus sampling threshold (0.0-1.0)
- `top_k`: Vocabulary limit (1-1000)
- `max_tokens`: Maximum tokens to generate (1-32,768)
- `frequency_penalty`: Reduce token frequency repetition (-2.0 to 2.0)
- `presence_penalty`: Encourage topic diversity (-2.0 to 2.0)
- `repetition_penalty`: OpenRouter-specific repetition penalty (1.0-2.0, 1.0=off)
- `response_format`: Choose between "text" or "json_object" output
- `seed_mode`: Control reproducibility (Fixed, Random, Increment, Decrement)
- `seed_value`: Seed for 'fixed' mode (0-9007199254740991)
- `max_retries`: Auto-retry attempts for recoverable errors (0-5)
- `debug_mode`: Enable detailed error messages and request debugging
- `image_input`: Optional image for vision models (max 2048x2048)
- `additional_params`: Extra model parameters in JSON format

#### Outputs:
- `response`: The model's generated text or JSON response
- `status`: Detailed request information including model, seed, and token counts
- `help`: Comprehensive help text with usage information

#### Vision Model Usage:
1. Select a vision-capable model (marked with **Vision** above)
2. Connect an image to the `image_input` parameter
3. Describe what you want to know about the image in `user_prompt`
4. Vision-capable models include:
   - Meta Llama: llama-4-maverick, llama-4-scout, llama-3.2-90b-vision
   - Qwen: qwen2.5-vl-32b, qwen2-vl-7b, qvq-72b-preview
   - Nvidia: nemotron-nano-12b-v2-vl

### OpenRouter Models Node
Query and filter available models from OpenRouter's API.

#### Features:
- Retrieve complete list of available models
- Filter models using custom search terms (e.g., 'free', 'gpt', 'claude')
- Sort models by name, pricing, or context length
- Detailed model information including pricing and context length
- Easy-to-read formatted output

#### Parameters:
- `api_key`: ⚠️ Your OpenRouter API key (Note: key will be visible in workflows)
- `filter_text`: Text to filter models
- `sort_by`: Sort models by name, pricing, or context length
- `sort_order`: Choose ascending or descending sort order

## Usage Guide

### Basic Text Generation
1. Add an LLM node (OpenRouter or Groq) to your workflow
2. Set your API key
3. Choose a model
4. (Optional) Set system prompt for context/behavior
5. Enter your prompt in the `user_prompt` field
6. Connect the node's output to view results

### Vision Analysis
1. Add an LLM node to your workflow
2. Choose a vision-capable model
3. Connect an image output to the `image_input`
4. For Groq vision models, set 'send_system' to 'no'
5. Add your prompt about the image in `user_prompt`
6. Connect outputs to view response and status

### Advanced Usage
- Use `system_prompt` to set context or behavior
- Adjust temperature and other parameters to control response style
- Select `json_object` format for structured outputs
- Monitor token usage via the status output
- Chain multiple nodes for complex workflows
- Use seed_mode for reproducible outputs (Fixed) or controlled variation (Increment/Decrement)
- Use `additional_params` to set model-specific parameters in JSON format:
  ```json
  {
    "min_p": 0.1,
    "stop": ["\n\n"]
  }
  ```

### Parameter Optimization Tips
- **Temperature**:
  - Lower (0.1-0.3): More focused, deterministic responses
  - Higher (0.7-1.0): More creative outputs
- **Top-p**:
  - Lower (0.1-0.3): More predictable word choices
  - Higher (0.7-1.0): More diverse vocabulary
- **Penalties**:
  - Use `presence_penalty` to reduce topic repetition
  - Use `frequency_penalty` to reduce word repetition
- **Seed Mode**:
  - `fixed`: Use for reproducible outputs (same seed + params = same output)
  - `random`: Use for varied responses each time
  - `increment/decrement`: Use for controlled variation across runs
- **Token Management**:
  - Monitor token usage in status output to optimize costs
  - Adjust `max_completion_tokens` to control response length

### Error Handling
Both nodes provide detailed error messages for common issues:
- Missing or invalid API keys
- Model compatibility issues
- Image size and format requirements
- JSON format validation
- Token limits and usage
- API rate limits and automatic retries
- Parameter validation errors

Enable `debug_mode` in the Groq node for detailed troubleshooting information.

## Version History

### v2.0.0 (Current)
- **MAJOR UPDATE**: All nodes converted to ComfyUI v3 spec
- **Groq Node v3**:
  - Updated models list to latest production and preview models
  - Added new production models: groq/compound, groq/compound-mini
  - Added new preview models: qwen/qwen3-32b
  - Set llama-3.3-70b-versatile as default model
  - Enhanced input validation with validate_inputs method
  - Improved tooltips with detailed explanations for all parameters
  - Better error messages and debug mode support
  - Fixed output labels to use proper display_name syntax
- **OpenRouter Node v3**:
  - Converted to v3 spec with enhanced validation
  - Updated free models list to current 50+ offerings (January 2025)
  - Organized models by provider: Meta, Google, Mistral, Qwen, Microsoft, DeepSeek, Nvidia, Others
  - Set meta-llama/llama-3.3-70b-instruct:free as default model
  - Added comprehensive tooltips for all parameters
  - Enhanced error handling and debug mode
  - Better vision model detection and validation
  - Updated vision models list with all current vision-capable models
  - Fixed output labels to use proper display_name syntax
- **OpenRouter Models Node v3**:
  - Converted to v3 spec
  - Enhanced validation and error handling
  - Improved tooltip documentation
  - Fixed output labels to use proper display_name syntax
- **Architecture**:
  - All nodes use stateless design with class methods
  - Class-level seed tracking for reproducibility
  - Maintained full backward compatibility with v1 API
  - Combined v3 entry point for all nodes
  - Corrected combo input syntax (removed invalid enum classes)
  - Proper output definition using display_name parameter
- **Documentation**:
  - Comprehensive README updates for all v3 nodes
  - Updated OpenRouter model list with all 50+ current free models
  - Production vs preview model guidance
  - Enhanced parameter optimization tips
  - Detailed vision model usage instructions with current models

### v1.3.0
- Groq node v3 conversion (initial v3 work)

### Previous Versions
- See git history for earlier changes

## Technical Details

### ComfyUI v3 Compatibility
All nodes have been fully migrated to ComfyUI v3 spec:
- Uses `comfy_api.latest` for enhanced reliability
- Implements `define_schema()` with comprehensive input/output definitions
- Stateless design with class methods (`execute()`, `validate_inputs()`)
- Proper `comfy_entrypoint()` function for v3 registration
- Combined extension class that registers all nodes
- Maintains full v1 compatibility through legacy NODE_CLASS_MAPPINGS
- Graceful fallback when v3 API is unavailable

### API Compatibility
- **Groq**: OpenAI-compatible API endpoint
- **OpenRouter**: Multi-provider aggregation API
- Both support standard OpenAI message format
- Vision models use base64-encoded images in message content

## Contributing

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

## Support

For issues, questions, or feature requests:
- Open an issue on [GitHub](https://github.com/EnragedAntelope/ComfyUI-EACloudNodes/issues)
- Check existing issues for solutions
- Enable debug mode for detailed error information

## License

[License](https://github.com/EnragedAntelope/ComfyUI-EACloudNodes/blob/main/LICENSE)

ComfyUI-EACloudNodes

ComfyUI-EACloudNodes Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

ComfyUI-EACloudNodes

ComfyUI-EACloudNodes Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

Download README