Merge pull request #2 from Limbicnation/feature/lora-integration

Feature/lora integration

CLAUDE.md

@@ -88,3 +88,31 @@ comfy node publish --confirm
 1. Add entry to `config/templates.yaml` following existing format
 2. Add style key to `INPUT_TYPES()` style combo list in `prompt_generator_node.py`
 3. Optionally add to `DEFAULT_STYLES` dict for fallback when YAML unavailable
+
+- **Current version**: `1.1.1` - Added dynamic LoRA model selection and prioritization. (2026-02-02)
+- **LoRA Training**: Trained QLoRA on Qwen3-4B-Instruct-2507 using the Limbicnation Video Diffusion Prompt dataset.
+- **Quantization**: Merged LoRA and converted to Q8_0 GGUF for Ollama.
+- **Integration**: `PromptGeneratorNode` now auto-discovers and prioritizes models containing `lora` or `limbicnation` keywords.
+
+### Creating a LoRA-Enhanced Model
+
+1. Fine-tune a LoRA on the [Limbicnation/Images-Diffusion-Prompt-Style](https://huggingface.co/datasets/Limbicnation/Images-Diffusion-Prompt-Style) dataset (750 prompts)
+
+2. Export as `.safetensors` (non-quantized recommended)
+
+3. Create the Ollama model:
+
+   ```bash
+   # Edit config/Modelfile.limbicnation with your adapter path
+   ollama create qwen3-limbicnation -f config/Modelfile.limbicnation
+   ```
+
+4. Restart ComfyUI - the new model will appear in the dropdown
+
+### Modelfile Template
+
+See `config/Modelfile.limbicnation` for a pre-configured template with:
+
+- Limbicnation system prompt
+- Optimal temperature/top_p settings
+- ADAPTER placeholder for your LoRA

config/Modelfile.limbicnation

@@ -0,0 +1,33 @@
+# Limbicnation LoRA Modelfile Template
+# 
+# This Modelfile creates an Ollama model with the Limbicnation image prompt style LoRA.
+# 
+# Usage:
+#   1. Fine-tune your LoRA using the 750 prompts from Limbicnation/Images-Diffusion-Prompt-Style
+#   2. Export as .safetensors (non-quantized recommended)
+#   3. Update the ADAPTER path below
+#   4. Run: ollama create qwen3-limbicnation -f Modelfile.limbicnation
+#   5. Test: ollama run qwen3-limbicnation "Generate a cinematic forest prompt"
+
+# Base model - use the same model you fine-tuned the LoRA on
+FROM qwen3:4b
+
+# LoRA adapter path (update this to your fine-tuned adapter)
+# ADAPTER /path/to/limbicnation-lora.safetensors
+
+# System prompt for image prompt generation
+SYSTEM """You are an expert AI Image Prompt Engineer specializing in the "Limbicnation" aesthetic.
+Your prompts emphasize: cinematic lighting, intricate textures, evocative atmosphere, dramatic compositions.
+
+When generating image prompts:
+1. Use rich, sensory language
+2. Include quality tokens: photorealistic, 8k, detailed, masterpiece
+3. Specify lighting and atmosphere
+4. Add negative prompts when requested
+5. Format for Flux, Z Image, or Stable Diffusion models
+"""
+
+# Optimal parameters for prompt generation
+PARAMETER temperature 0.7
+PARAMETER top_p 0.9
+PARAMETER num_ctx 4096

nodes/prompt_generator_node.py

@@ -191,14 +191,64 @@ Format the response as a single, detailed sci-fi prompt."""
         }
     }
     
+    # Class-level cache for available models
+    _cached_models = None
+    _cache_time = 0
+    
     def __init__(self):
         """Initialize the node and load style templates."""
         self.style_templates = self._load_templates()
         self.timeout = 120
     
+    @classmethod
+    def _get_available_models(cls) -> list:
+        """
+        Fetch available Ollama models with caching.
+        Prioritizes LoRA-enhanced models (containing 'lora', 'limbicnation', 'fine').
+        """
+        import time
+        
+        # Cache for 60 seconds
+        if cls._cached_models and (time.time() - cls._cache_time) < 60:
+            return cls._cached_models
+        
+        default_models = ["qwen3:8b", "qwen3:4b", "llama3.2:latest"]
+        
+        if not OLLAMA_API_AVAILABLE:
+            return default_models
+        
+        try:
+            result = ollama.list()
+            models = [m['name'] for m in result.get('models', []) if 'name' in m]
+            
+            if not models:
+                return default_models
+            
+            # Sort: LoRA/fine-tuned models first, then alphabetically
+            lora_keywords = ['lora', 'limbicnation', 'fine', 'style', 'prompt']
+            
+            def sort_key(name):
+                name_lower = name.lower()
+                is_lora = any(kw in name_lower for kw in lora_keywords)
+                return (0 if is_lora else 1, name)
+            
+            models = sorted(models, key=sort_key)
+            
+            cls._cached_models = models
+            cls._cache_time = time.time()
+            
+            print(f"[PromptGenerator] Found {len(models)} Ollama models")
+            return models
+            
+        except Exception as e:
+            print(f"[PromptGenerator] Could not fetch models: {e}")
+            return default_models
+    
     @classmethod
     def INPUT_TYPES(cls) -> Dict[str, Any]:
         """Define input parameters for the node."""
+        available_models = cls._get_available_models()
+        
         return {
             "required": {
                 "description": ("STRING", {
@@ -210,6 +260,10 @@ Format the response as a single, detailed sci-fi prompt."""
                            "abstract", "cyberpunk", "sci-fi"], {
                     "default": "cinematic"
                 }),
+                "model": (available_models, {
+                    "default": available_models[0] if available_models else "qwen3:8b",
+                    "tooltip": "Select Ollama model. LoRA-enhanced models appear first."
+                }),
             },
             "optional": {
                 "emphasis": ("STRING", {
@@ -239,9 +293,6 @@ Format the response as a single, detailed sci-fi prompt."""
                     "label_on": "Show Reasoning",
                     "label_off": "Hide Reasoning"
                 }),
-                "model": ("STRING", {
-                    "default": "qwen3:8b"
-                }),
             }
         }
     
@@ -250,6 +301,7 @@ Format the response as a single, detailed sci-fi prompt."""
     FUNCTION = "generate"
     CATEGORY = "text/generation"
     OUTPUT_NODE = False
+
     
     def _load_templates(self) -> Dict[str, Any]:
         """Load style templates from YAML file or use defaults."""

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-prompt-generator"
-description = "Generate Stable Diffusion prompts using Qwen3-8B via Ollama with 7 style presets"
-version = "1.0.5"
+description = "Generate Stable Diffusion prompts using Qwen/Ollama with LoRA support and 7 style presets"
+version = "1.1.2"
 license = {file = "LICENSE"}
 readme = "README.md"
 requires-python = ">=3.10"