feat: consolidate style system to 9 styles across both nodes
This commit is contained in:
limbicnation
@@ -17,4 +17,3 @@ NODE_DISPLAY_NAME_MAPPINGS = {
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}
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__all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]
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@@ -0,0 +1,87 @@
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# Code Review: ComfyUI-PromptGenerator
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## Executive Summary
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The codebase is well-structured with good error handling and graceful degradation patterns. However, there is a **critical inconsistency** in the style system between the two nodes, plus several architectural concerns worth addressing.
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---
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## 🚨 Critical Issues
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### 1. Style System Inconsistency (High Priority)
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**Problem:** The two nodes have completely different style options:
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| Node | Available Styles |
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|------|------------------|
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| `PromptGeneratorNode` | cinematic, anime, photorealistic, fantasy, abstract, cyberpunk, sci-fi, video_wan (8 styles) |
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| `StyleApplierNode` | cinematic, still_image (2 styles via `StylePreset.get_style_choices()`) |
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The `style_presets.py` module only defines 2 styles, while `config/templates.yaml` and `DEFAULT_STYLES` define 8 styles.
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**Impact:** Users expect consistency. If they select "anime" style in PromptGenerator, they cannot use StyleApplier with "anime" - it will fail validation.
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**Recommendation:** Either:
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- Expand `STYLE_DEFINITIONS` in `style_presets.py` to include all 8 styles
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- Or consolidate to use templates.yaml as the single source of truth
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---
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## ⚠️ Architectural Concerns
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### 2. Triple Source of Truth for Styles
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The codebase has three different places defining styles:
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1. `config/templates.yaml` - YAML templates
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2. `DEFAULT_STYLES` dict in Python (`prompt_generator_node.py`)
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3. `style_presets.py` - StyleKeywords dataclass
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**Recommendation:** Consolidate to a single source. The YAML file is user-editable and should be the authoritative source.
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### 3. Unused `style_presets.py` Module
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The `StylePreset` class is only used by `StyleApplierNode`. The main `PromptGeneratorNode` uses its own `DEFAULT_STYLES` dict and YAML templates.
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---
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## 🔧 Code Quality Issues
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### 4. Missing Style Validation in `generate()`
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In `generate()`, there's no validation that the selected style exists - it silently falls back to cinematic.
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### 5. Inconsistent Error Messages
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- `PromptGeneratorNode` returns emoji-prefixed messages: `"⚠️ Please enter an image description."`
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- `StyleApplierNode` returns bracket-prefixed: `"[StyleApplier] Error: Unknown style..."`
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**Recommendation:** Standardize error message format.
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### 6. Hardcoded Values
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- `chunk_timeout = 30` is hardcoded in streaming
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- Model list in `_get_available_models()` has hardcoded defaults
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---
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## ✅ Positive Patterns
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1. **Graceful Degradation:** Excellent use of optional imports with fallbacks
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2. **Streaming Implementation:** Well-designed background thread approach for timeout enforcement
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3. **Cold Start Detection:** Smart 1.3x timeout multiplier for unloaded models
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4. **Model Caching:** 60-second cache prevents UI freezes
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5. **LoRA Prioritization:** Good sorting logic to surface fine-tuned models first
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---
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## 📋 Recommendations Priority List
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| Priority | Issue | Action |
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|----------|-------|--------|
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| P0 | Style inconsistency | Sync `style_presets.py` with 8 styles or consolidate |
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| P1 | Triple source of truth | Make templates.yaml the single source |
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| P2 | Silent style fallback | Add validation/warning when style not found |
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| P3 | Error message format | Standardize across nodes |
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| P4 | Hardcoded values | Move to config/constants |
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@@ -71,12 +71,14 @@ class PromptGeneratorNode:
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ComfyUI node for generating Stable Diffusion prompts using Qwen3-8B via Ollama.
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Features:
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- 7 style presets (cinematic, anime, photorealistic, fantasy, abstract, cyberpunk, sci-fi)
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- 9 style presets loaded from templates.yaml (single source of truth)
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- Temperature and Top-P sampling controls
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- Optional focus area (emphasis) and mood inputs
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- Reasoning toggle to show/hide model's thinking process
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"""
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CHUNK_TIMEOUT = 30
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# Default style templates (fallback when YAML not available)
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DEFAULT_STYLES = {
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"cinematic": {
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@@ -210,6 +212,24 @@ Format the response as a single, detailed sci-fi prompt.""",
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"description": "Minimalist template optimized for WanVideo LoRA",
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"template": "Generate a video prompt for: {{ description }}{% if emphasis %} with focus on {{ emphasis }}{% endif %}{% if mood %}, mood is {{ mood }}{% endif %}",
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},
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"still_image": {
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"name": "Still Image (Photography)",
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"description": "Sharp, realistic photography with technical camera specifications",
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"template": """Write a detailed Stable Diffusion prompt for: {{ description }}
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Style: Generate a professional photography still image with sharp focus.
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{% if emphasis %}Focus particularly on: {{ emphasis }}{% endif %}
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{% if mood %}Mood/Atmosphere: {{ mood }}{% endif %}
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Include specific details about:
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- Camera settings (ISO 100, f/2.8 aperture, sharp optics)
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- Natural or studio lighting
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- Realistic textures and fine details
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- Clean, balanced composition
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- Professional photography qualities
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Format the response as a single, detailed photography prompt.""",
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},
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}
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# Class-level cache for available models
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@@ -264,10 +284,25 @@ Format the response as a single, detailed sci-fi prompt.""",
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print(f"[PromptGenerator] Could not fetch models: {e}")
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return default_models
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@classmethod
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def _get_style_list(cls) -> list:
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"""Get style list from templates.yaml, falling back to DEFAULT_STYLES keys."""
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template_path = Path(__file__).parent.parent / "config" / "templates.yaml"
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if YAML_AVAILABLE and template_path.exists():
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try:
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with open(template_path, "r") as f:
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templates = yaml.safe_load(f)
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if templates:
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return list(templates.keys())
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except Exception:
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pass
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return list(cls.DEFAULT_STYLES.keys())
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@classmethod
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def INPUT_TYPES(cls) -> Dict[str, Any]:
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"""Define input parameters for the node."""
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available_models = cls._get_available_models()
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available_styles = cls._get_style_list()
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return {
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"required": {
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@@ -280,17 +315,12 @@ Format the response as a single, detailed sci-fi prompt.""",
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},
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),
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"style": (
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[
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"cinematic",
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"anime",
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"photorealistic",
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"fantasy",
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"abstract",
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"cyberpunk",
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"sci-fi",
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"video_wan",
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],
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{"default": "cinematic"},
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available_styles,
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{
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"default": available_styles[0]
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if available_styles
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else "cinematic"
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},
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),
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"model": (
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available_models,
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@@ -395,9 +425,13 @@ Format the response as a single, detailed sci-fi prompt.""",
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mood: Optional[str] = None,
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) -> str:
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"""Render a Jinja2 template with the given variables."""
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template_data = self.style_templates.get(
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style, self.DEFAULT_STYLES.get("cinematic")
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)
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template_data = self.style_templates.get(style)
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if template_data is None:
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print(
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f"[PromptGenerator] Warning: style '{style}' not found in templates, "
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f"falling back to 'cinematic'"
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)
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template_data = self.DEFAULT_STYLES.get("cinematic")
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# Handle YAML format with 'template' key
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if isinstance(template_data, dict) and "template" in template_data:
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@@ -484,7 +518,7 @@ Format the response as a single, detailed sci-fi prompt.""",
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chunks = []
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start = time.monotonic()
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first_chunk_timeout = min(timeout * 0.6, 90)
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chunk_timeout = 30
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chunk_timeout = self.CHUNK_TIMEOUT
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got_first_chunk = False
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try:
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@@ -604,7 +638,7 @@ Format the response as a single, detailed sci-fi prompt.""",
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Tuple containing the generated prompt string
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"""
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if not description.strip():
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return ("⚠️ Please enter an image description.",)
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return ("[PromptGenerator] Please enter an image description.",)
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# Render the template
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prompt = self._render_template(
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@@ -666,7 +700,7 @@ Format the response as a single, detailed sci-fi prompt.""",
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print(f"[PromptGenerator] Generated {len(output)} characters")
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return (output,)
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else:
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return ("⚠️ Generation returned empty result.",)
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return ("[PromptGenerator] Generation returned empty result.",)
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print("[PromptGenerator] Streaming failed, falling back to subprocess")
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@@ -680,7 +714,7 @@ Format the response as a single, detailed sci-fi prompt.""",
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)
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if result.returncode != 0:
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return (f"⚠️ Ollama error: {result.stderr}",)
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return (f"[PromptGenerator] Ollama error: {result.stderr}",)
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output = result.stdout.strip()
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@@ -696,11 +730,13 @@ Format the response as a single, detailed sci-fi prompt.""",
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)
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return (output,)
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else:
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return ("⚠️ Generation returned empty result.",)
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return ("[PromptGenerator] Generation returned empty result.",)
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except subprocess.TimeoutExpired:
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return (f"⚠️ Generation timed out after {timeout}s",)
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return (f"[PromptGenerator] Generation timed out after {timeout}s",)
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except FileNotFoundError:
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return ("⚠️ Ollama not found. Install from: https://ollama.ai",)
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return (
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"[PromptGenerator] Ollama not found. Install from: https://ollama.ai",
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)
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except Exception as e:
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return (f"⚠️ Error: {str(e)}",)
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return (f"[PromptGenerator] Error: {str(e)}",)
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+29
-19
@@ -9,52 +9,61 @@ from typing import Tuple
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class StyleApplierNode:
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"""
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ComfyUI node for applying Cinematic or Still Image style keywords to prompts.
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Inputs:
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- prompt: Base prompt text
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- style: "cinematic" or "still_image"
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- position: Where to add keywords ("prefix", "suffix", or "wrap")
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- emphasis: Optional emphasis level ("low", "medium", "high")
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- include_technical: Include camera/technical specs
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Outputs:
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- styled_prompt: The prompt with style keywords added
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- style_keywords: Just the style keywords (for reference)
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"""
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@classmethod
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def INPUT_TYPES(cls):
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"""Define input parameters for the node."""
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from style_presets import StylePreset
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return {
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"required": {
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"prompt": ("STRING", {
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"multiline": True,
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"default": "",
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"placeholder": "Enter your base prompt..."
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}),
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"prompt": (
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"STRING",
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{
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"multiline": True,
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"default": "",
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"placeholder": "Enter your base prompt...",
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},
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),
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"style": (StylePreset.get_style_choices(), {"default": "cinematic"}),
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},
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"optional": {
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"position": (["suffix", "prefix", "wrap"], {"default": "suffix"}),
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"emphasis": (["medium", "low", "high"], {"default": "medium"}),
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"include_technical": ("BOOLEAN", {"default": True}),
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}
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},
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}
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RETURN_TYPES = ("STRING", "STRING",)
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RETURN_NAMES = ("styled_prompt", "style_keywords",)
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RETURN_TYPES = (
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"STRING",
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"STRING",
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)
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RETURN_NAMES = (
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"styled_prompt",
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"style_keywords",
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)
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FUNCTION = "apply_style"
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CATEGORY = "text/generation"
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def apply_style(
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self,
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prompt: str,
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style: str,
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position: str = "suffix",
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emphasis: str = "medium",
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include_technical: bool = True
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include_technical: bool = True,
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) -> Tuple[str, str]:
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"""Apply style keywords to a prompt."""
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from style_presets import StylePreset
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@@ -66,14 +75,15 @@ class StyleApplierNode:
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# Validate style
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available_styles = StylePreset.get_style_choices()
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if style not in available_styles:
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return (f"[StyleApplier] Error: Unknown style '{style}'. Available: {available_styles}", "")
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return (
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f"[StyleApplier] Error: Unknown style '{style}'. Available: {available_styles}",
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"",
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)
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# Get style keywords
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try:
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style_keywords = StylePreset().get_style_prompt(
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style=style,
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emphasis=emphasis,
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include_technical=include_technical
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style=style, emphasis=emphasis, include_technical=include_technical
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)
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except ValueError as e:
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return (f"[StyleApplier] Error getting style: {e}", "")
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@@ -0,0 +1,36 @@
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# Social Media Posts - v1.1.6 Bug Fix Release
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## LinkedIn Post
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---
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**Fixed the 120s timeout issue in ComfyUI Prompt Generator (v1.1.6)**
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If you've been hitting "Generation Timed Out 120s" errors with the ComfyUI Prompt Generator node - this is now resolved.
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The root cause: the blocking `ollama.generate()` call had no way to handle slow model responses or cold starts gracefully.
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What changed in v1.1.6:
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- Replaced blocking API call with streaming + per-chunk timeouts
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- Added cold start detection with automatic timeout multiplier
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- Integrated ComfyUI ProgressBar so you can see generation progress in real time
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Update via ComfyUI Manager or pull the latest from GitHub.
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https://github.com/Limbicnation/ComfyUI-PromptGenerator
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#ComfyUI #StableDiffusion #Ollama #AIArt #OpenSource #BugFix
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---
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## YouTube Reply to @luci0c4s3
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---
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> @luci0c4s3: "Getting Generation Timed 120s as an error each time I run the node."
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**Reply:**
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Hey! This was a known issue and it's been fixed in v1.1.6. The blocking Ollama call was replaced with streaming + per-chunk timeouts, which eliminates the 120s timeout error. Cold starts also get extra time automatically now. Update via ComfyUI Manager or grab the latest from GitHub: https://github.com/Limbicnation/ComfyUI-PromptGenerator
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---
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+276
-36
@@ -1,13 +1,13 @@
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"""
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Style Presets Module for ComfyUI
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Modular style system for prompt generation with Cinematic and Still Image modes.
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Modular style system for prompt generation with keyword sets for each style.
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Usage in ComfyUI nodes:
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from style_presets import StylePreset
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# Get style choices for INPUT_TYPES dropdown
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choices = StylePreset.get_style_choices() # ("cinematic", "still_image")
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choices = StylePreset.get_style_choices()
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# Get style keywords as a prompt string
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preset = StylePreset()
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style_prompt = preset.get_style_prompt("cinematic")
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@@ -20,38 +20,54 @@ from enum import Enum
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class StyleMode(Enum):
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"""Enumeration of available style modes."""
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CINEMATIC = "cinematic"
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STILL_IMAGE = "still_image"
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ANIME = "anime"
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PHOTOREALISTIC = "photorealistic"
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FANTASY = "fantasy"
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ABSTRACT = "abstract"
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CYBERPUNK = "cyberpunk"
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SCI_FI = "sci-fi"
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VIDEO_WAN = "video_wan"
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@dataclass
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class StyleKeywords:
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"""Container for style-specific keywords and descriptors."""
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primary: List[str] = field(default_factory=list)
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lighting: List[str] = field(default_factory=list)
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technical: List[str] = field(default_factory=list)
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composition: List[str] = field(default_factory=list)
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texture: List[str] = field(default_factory=list)
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def to_prompt_string(self, separator: str = ", ") -> str:
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"""Convert all keywords to a single prompt string."""
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all_keywords = (
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self.primary + self.lighting + self.technical +
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self.composition + self.texture
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self.primary
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+ self.lighting
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+ self.technical
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+ self.composition
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+ self.texture
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)
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return separator.join(all_keywords)
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def to_list(self) -> List[str]:
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"""Return all keywords as a flat list (ComfyUI-compatible)."""
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return (
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self.primary + self.lighting + self.technical +
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self.composition + self.texture
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self.primary
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+ self.lighting
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+ self.technical
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+ self.composition
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+ self.texture
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)
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@dataclass
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class StyleDefinition:
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"""Complete style definition with metadata and keywords."""
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name: str
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description: str
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keywords: StyleKeywords
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@@ -64,23 +80,251 @@ STYLE_DEFINITIONS: Dict[StyleMode, StyleDefinition] = {
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description="Film-like visuals with dramatic lighting and anamorphic qualities",
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keywords=StyleKeywords(
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primary=["cinematic shot", "film grain", "movie still", "dramatic scene"],
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lighting=["dramatic lighting", "volumetric light", "rim lighting", "chiaroscuro", "golden hour"],
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technical=["anamorphic lens", "shallow depth of field", "bokeh", "35mm film", "wide aspect ratio"],
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composition=["rule of thirds", "leading lines", "dynamic composition", "cinematic framing"],
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texture=["rich color grading", "film texture", "atmospheric haze"]
|
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)
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lighting=[
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"dramatic lighting",
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"volumetric light",
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"rim lighting",
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"chiaroscuro",
|
||||
"golden hour",
|
||||
],
|
||||
technical=[
|
||||
"anamorphic lens",
|
||||
"shallow depth of field",
|
||||
"bokeh",
|
||||
"35mm film",
|
||||
"wide aspect ratio",
|
||||
],
|
||||
composition=[
|
||||
"rule of thirds",
|
||||
"leading lines",
|
||||
"dynamic composition",
|
||||
"cinematic framing",
|
||||
],
|
||||
texture=["rich color grading", "film texture", "atmospheric haze"],
|
||||
),
|
||||
),
|
||||
StyleMode.STILL_IMAGE: StyleDefinition(
|
||||
name="Still Image (Photography)",
|
||||
description="Sharp, realistic photography with technical camera specifications",
|
||||
keywords=StyleKeywords(
|
||||
primary=["professional photography", "high resolution", "sharp focus", "studio quality"],
|
||||
lighting=["natural lighting", "soft diffused light", "studio lighting", "balanced exposure"],
|
||||
technical=["f/2.8 aperture", "ISO 100", "sharp optics", "full frame sensor", "RAW quality"],
|
||||
composition=["centered composition", "clean framing", "balanced layout", "professional angle"],
|
||||
texture=["realistic textures", "fine details", "crisp definition", "accurate colors"]
|
||||
)
|
||||
)
|
||||
primary=[
|
||||
"professional photography",
|
||||
"high resolution",
|
||||
"sharp focus",
|
||||
"studio quality",
|
||||
],
|
||||
lighting=[
|
||||
"natural lighting",
|
||||
"soft diffused light",
|
||||
"studio lighting",
|
||||
"balanced exposure",
|
||||
],
|
||||
technical=[
|
||||
"f/2.8 aperture",
|
||||
"ISO 100",
|
||||
"sharp optics",
|
||||
"full frame sensor",
|
||||
"RAW quality",
|
||||
],
|
||||
composition=[
|
||||
"centered composition",
|
||||
"clean framing",
|
||||
"balanced layout",
|
||||
"professional angle",
|
||||
],
|
||||
texture=[
|
||||
"realistic textures",
|
||||
"fine details",
|
||||
"crisp definition",
|
||||
"accurate colors",
|
||||
],
|
||||
),
|
||||
),
|
||||
StyleMode.ANIME: StyleDefinition(
|
||||
name="Anime",
|
||||
description="Vibrant anime-style illustration with dynamic colors",
|
||||
keywords=StyleKeywords(
|
||||
primary=[
|
||||
"anime style",
|
||||
"manga illustration",
|
||||
"cel shading",
|
||||
"vibrant colors",
|
||||
],
|
||||
lighting=[
|
||||
"soft glow",
|
||||
"dramatic backlighting",
|
||||
"ambient light",
|
||||
"bloom effect",
|
||||
],
|
||||
technical=[
|
||||
"clean linework",
|
||||
"flat color areas",
|
||||
"high contrast",
|
||||
"detailed eyes",
|
||||
],
|
||||
composition=[
|
||||
"dynamic pose",
|
||||
"expressive composition",
|
||||
"layered background",
|
||||
],
|
||||
texture=["smooth gradients", "soft skin tones", "vivid saturation"],
|
||||
),
|
||||
),
|
||||
StyleMode.PHOTOREALISTIC: StyleDefinition(
|
||||
name="Photorealistic",
|
||||
description="High-detail realistic images with natural lighting",
|
||||
keywords=StyleKeywords(
|
||||
primary=[
|
||||
"photorealistic",
|
||||
"ultra realistic",
|
||||
"lifelike detail",
|
||||
"high fidelity",
|
||||
],
|
||||
lighting=[
|
||||
"natural lighting",
|
||||
"golden hour",
|
||||
"soft shadows",
|
||||
"ambient occlusion",
|
||||
],
|
||||
technical=[
|
||||
"DSLR quality",
|
||||
"85mm lens",
|
||||
"shallow depth of field",
|
||||
"8K resolution",
|
||||
],
|
||||
composition=["rule of thirds", "natural framing", "environmental portrait"],
|
||||
texture=[
|
||||
"realistic skin texture",
|
||||
"fine material detail",
|
||||
"natural imperfections",
|
||||
],
|
||||
),
|
||||
),
|
||||
StyleMode.FANTASY: StyleDefinition(
|
||||
name="Fantasy",
|
||||
description="Magical elements and themes with ethereal atmosphere",
|
||||
keywords=StyleKeywords(
|
||||
primary=["fantasy art", "magical scene", "mythical", "enchanted"],
|
||||
lighting=[
|
||||
"ethereal glow",
|
||||
"mystical light rays",
|
||||
"bioluminescence",
|
||||
"aurora",
|
||||
],
|
||||
technical=["digital painting", "matte painting", "concept art quality"],
|
||||
composition=[
|
||||
"epic scale",
|
||||
"layered depth",
|
||||
"grand vista",
|
||||
"ornate framing",
|
||||
],
|
||||
texture=[
|
||||
"iridescent surfaces",
|
||||
"crystalline detail",
|
||||
"ancient stonework",
|
||||
"enchanted flora",
|
||||
],
|
||||
),
|
||||
),
|
||||
StyleMode.ABSTRACT: StyleDefinition(
|
||||
name="Abstract",
|
||||
description="Artistic abstract compositions with creative expression",
|
||||
keywords=StyleKeywords(
|
||||
primary=["abstract art", "non-representational", "artistic composition"],
|
||||
lighting=["color field lighting", "gradient transitions", "luminous forms"],
|
||||
technical=["mixed media", "generative art", "high dynamic range"],
|
||||
composition=[
|
||||
"visual rhythm",
|
||||
"asymmetric balance",
|
||||
"flowing forms",
|
||||
"geometric patterns",
|
||||
],
|
||||
texture=[
|
||||
"paint strokes",
|
||||
"textured layers",
|
||||
"organic forms",
|
||||
"splatter effects",
|
||||
],
|
||||
),
|
||||
),
|
||||
StyleMode.CYBERPUNK: StyleDefinition(
|
||||
name="Cyberpunk",
|
||||
description="Neon lights, high technology, and urban dystopia",
|
||||
keywords=StyleKeywords(
|
||||
primary=[
|
||||
"cyberpunk",
|
||||
"neon noir",
|
||||
"dystopian future",
|
||||
"high tech low life",
|
||||
],
|
||||
lighting=[
|
||||
"neon glow",
|
||||
"holographic reflections",
|
||||
"LED strips",
|
||||
"rain-soaked neon",
|
||||
],
|
||||
technical=[
|
||||
"ray tracing",
|
||||
"volumetric fog",
|
||||
"chromatic aberration",
|
||||
"lens flare",
|
||||
],
|
||||
composition=[
|
||||
"urban canyon",
|
||||
"vertical composition",
|
||||
"dense layering",
|
||||
"vanishing point",
|
||||
],
|
||||
texture=[
|
||||
"wet asphalt reflections",
|
||||
"rust and chrome",
|
||||
"holographic surfaces",
|
||||
"circuit patterns",
|
||||
],
|
||||
),
|
||||
),
|
||||
StyleMode.SCI_FI: StyleDefinition(
|
||||
name="Sci-Fi",
|
||||
description="Futuristic technology and space exploration scenes",
|
||||
keywords=StyleKeywords(
|
||||
primary=[
|
||||
"science fiction",
|
||||
"futuristic",
|
||||
"space opera",
|
||||
"advanced technology",
|
||||
],
|
||||
lighting=["starlight", "plasma glow", "engine flare", "atmospheric entry"],
|
||||
technical=[
|
||||
"hard surface modeling",
|
||||
"concept art",
|
||||
"matte painting",
|
||||
"photobashing",
|
||||
],
|
||||
composition=[
|
||||
"epic scale",
|
||||
"orbital view",
|
||||
"dramatic perspective",
|
||||
"vast emptiness",
|
||||
],
|
||||
texture=[
|
||||
"polished metal",
|
||||
"energy fields",
|
||||
"alien materials",
|
||||
"hull plating",
|
||||
],
|
||||
),
|
||||
),
|
||||
StyleMode.VIDEO_WAN: StyleDefinition(
|
||||
name="Video (WanVideo)",
|
||||
description="Minimalist keywords optimized for WanVideo LoRA",
|
||||
keywords=StyleKeywords(
|
||||
primary=["video shot", "motion capture", "fluid movement"],
|
||||
lighting=["cinematic lighting", "natural light"],
|
||||
technical=["smooth motion", "24fps", "high resolution video"],
|
||||
composition=["dynamic camera", "tracking shot"],
|
||||
texture=["temporal consistency", "clean frames"],
|
||||
),
|
||||
),
|
||||
}
|
||||
|
||||
|
||||
@@ -101,40 +345,37 @@ def get_available_styles() -> List[str]:
|
||||
|
||||
class StylePreset:
|
||||
"""ComfyUI-compatible style preset class."""
|
||||
|
||||
|
||||
def __init__(self):
|
||||
self._styles = STYLE_DEFINITIONS
|
||||
|
||||
|
||||
@staticmethod
|
||||
def get_style_choices() -> Tuple[str, ...]:
|
||||
"""Get available style choices as tuple (ComfyUI dropdown format)."""
|
||||
return tuple(mode.value for mode in StyleMode)
|
||||
|
||||
|
||||
def get_style_keywords(self, style: str) -> List[str]:
|
||||
"""Get style keywords as a list."""
|
||||
return get_style_keywords(style).to_list()
|
||||
|
||||
|
||||
def get_style_prompt(
|
||||
self,
|
||||
style: str,
|
||||
emphasis: Optional[str] = None,
|
||||
include_technical: bool = True
|
||||
self, style: str, emphasis: Optional[str] = None, include_technical: bool = True
|
||||
) -> str:
|
||||
"""Get a formatted style prompt string."""
|
||||
keywords = get_style_keywords(style)
|
||||
|
||||
|
||||
parts = []
|
||||
parts.extend(keywords.primary)
|
||||
parts.extend(keywords.lighting)
|
||||
parts.extend(keywords.composition)
|
||||
parts.extend(keywords.texture)
|
||||
|
||||
|
||||
if include_technical:
|
||||
parts.extend(keywords.technical)
|
||||
|
||||
|
||||
if emphasis:
|
||||
parts.insert(0, f"emphasis on {emphasis}")
|
||||
|
||||
|
||||
return ", ".join(parts)
|
||||
|
||||
|
||||
@@ -145,6 +386,5 @@ __all__ = [
|
||||
"StylePreset",
|
||||
"get_style_keywords",
|
||||
"get_available_styles",
|
||||
"STYLE_DEFINITIONS"
|
||||
"STYLE_DEFINITIONS",
|
||||
]
|
||||
|
||||
|
||||
Reference in New Issue
Block a user