# Configuration Examples for AI Video Prompt Expander ## LM Studio Configuration ``` Backend: lm_studio Endpoint: http://localhost:1234/v1 Model: llama3 (or whatever model you have loaded) Temperature: 0.7 (recommended for balanced creativity) ``` ## Ollama Configuration ``` Backend: ollama Endpoint: http://localhost:11434/api Model: llama3 (or llama3.1, mistral, etc.) Temperature: 0.7 ``` ## Remote LLM (if running on another machine) ``` Backend: lm_studio or ollama Endpoint: http://192.168.1.100:1234/v1 (replace with your IP) Model: [your model name] Temperature: 0.7 ``` ## Local Qwen3-VL Vision Backend ``` Backend: qwen3_vl Model: Qwen/Qwen3-VL-4B-Instruct@4bit (or local path) Endpoint Overrides: quant=4bit;attn=sdpa;device=cuda:0 Temperature: 0.6 (captioning focused) ``` Set this backend inside the image-to-video or image-to-image nodes when you want to caption reference images without calling an HTTP server. Install `transformers`, `accelerate`, `huggingface_hub`, and (optionally) `bitsandbytes` beforehand. ## Preset Recommendations ### For Realistic Scenes - Preset: **cinematic** - Tier: **advanced** or **cinematic** - Temperature: 0.5-0.7 ### For Creative/Artistic Content - Preset: **stylized** or **surreal** - Tier: **enhanced** or **advanced** - Temperature: 0.8-1.0 ### For High-Energy Sequences - Preset: **action** - Tier: **advanced** - Temperature: 0.6-0.8 ### For Moody/Atmospheric - Preset: **noir** - Tier: **advanced** or **cinematic** - Temperature: 0.5-0.7 ### For Experimentation - Preset: **random** - Tier: **auto** - Temperature: 1.0-1.5 ## Temperature Guidelines - **0.1-0.3**: Very focused, consistent, less creative - **0.4-0.6**: Balanced, reliable, some creativity - **0.7-0.9**: Creative, varied, good for exploration - **1.0-1.5**: Highly creative, experimental, more random - **1.5-2.0**: Very experimental, unpredictable ## Keyword Examples ### LoRA Triggers ``` Positive Keywords: myLoRA_style, detailed_face, high_quality ``` ### Style Enforcement ``` Positive Keywords: cinematic, professional, 4k, high-end ``` ### Character/Object Specific ``` Positive Keywords: red_hair, blue_eyes, leather_jacket ``` ### Negative Keywords (Custom) ``` Negative Keywords: cartoonish, anime, illustration, painting ``` ## Example Workflows ### Workflow 1: Quick Cinematic ```yaml Basic Prompt: "woman walking in rain" Preset: cinematic Tier: auto (will detect "enhanced") Variations: 1 Save: true ``` ### Workflow 2: Multiple Style Variations ```yaml Basic Prompt: "robot in futuristic city" Preset: custom Tier: advanced Variations: 3 Save: true ``` Then manually try with different presets to compare. ### Workflow 3: Image-to-Video ```yaml Basic Prompt: "slowly turns head and smiles" Mode: image-to-video Preset: cinematic Tier: enhanced Positive Keywords: [your lora trigger] ``` ### Workflow 4: Action Sequence ```yaml Basic Prompt: "superhero lands from sky" Preset: action Tier: cinematic Temperature: 0.8 Variations: 2 ``` ## File Naming Strategies ### By Project ``` filename_base: project_alpha_scene01 filename_base: project_alpha_scene02 ``` ### By Style ``` filename_base: cinematic_city_night filename_base: noir_detective_walk ``` ### By Character ``` filename_base: character_hero_intro filename_base: character_villain_reveal ``` ## Tips for Best Results 1. **Let Auto-Detect Work**: The auto tier detection is quite good 2. **Start Small**: Begin with basic prompts and increase complexity as needed 3. **Use Presets**: They dramatically influence the output style 4. **Iterate**: Generate variations and pick the best 5. **Save Everything**: Build a library of good prompts for reference 6. **Keywords First**: Always include LoRA triggers in positive_keywords 7. **Temperature Matters**: Lower for consistency, higher for creativity 8. **Mode Matters**: image-to-video mode focuses on motion, not scene setup ## Troubleshooting Common Issues ### Prompts Too Long - Lower the tier (cinematic → advanced → enhanced) - Use more concise basic_prompt - Some video models have token limits ### Not Enough Detail - Increase tier (basic → enhanced → advanced) - Use more descriptive basic_prompt - Try higher temperature for more elaboration ### Keywords Not Included - The node auto-appends missing keywords - Check spelling and comma separation - Verify in the output prompt ### Style Not Matching - Try different presets - Adjust temperature - Add style terms to positive_keywords ### LLM Too Slow - Use a smaller/faster model - Reduce max_tokens (edit node if needed) - Lower temperature slightly ## Model Recommendations ### Fast & Good Quality - Llama 3 8B - Mistral 7B ### Best Quality (Slower) - Llama 3 70B - Mixtral 8x7B ### Experimental - Llama 3.1 variants - Qwen models - Custom fine-tuned models ## Integration with Video Nodes The output connects directly to most video generation nodes: ``` [AI Video Prompt Expander] ↓ positive_prompt_1 [CogVideoX] [Runway Gen-3] [Pika Labs] [Stable Video Diffusion] etc. ``` Remember to also connect the **negative_prompt** output!