- Updated framing component (components.toml) with comprehensive analysis:
- Body visibility tracking (head to feet, top to bottom)
- Frame cutoff detection (where body is cropped)
- Subject distance/scale (fills frame / medium / far)
- Rule of thirds positioning (horizontal + vertical)
- Enhanced JSON output schema for agentic mode
- Updated single-shot prompts (prompts.toml) for all tiers:
- Advanced tier: detailed/extreme with FRAMING & VISIBILITY section
- Standard tier: framing info in detailed/extreme modes
- Basic tier: updated detailed/extreme with body visibility and positioning
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Updated Detailed and Extreme mode prompts (all tiers) to include:
Body Positioning (each limb independently):
- Left/right shoulder position and angle
- Left/right arm position, bend, hand placement
- Left/right leg position if visible
- Weight distribution
Light & Shadow Analysis:
- Face: highlight areas (forehead, cheekbones), shadow areas (under eyes, jawline)
- Chest/torso: where light and shadow fall
- Arms: light and shadow placement
- Overall direction, key/fill ratio, rim lighting, shadow color temp
This ensures single-shot mode captures the same detail as agentic mode
with the new body_positioning and light_shadow_body components.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
New components for detailed prompt detection:
1. body_positioning - Detailed limb analysis:
- Left/right shoulder position, angle, visibility
- Left/right arm position, bend angle, hand placement
- Left/right leg position, bend, weight distribution
- All limbs analyzed independently
2. light_shadow_body - Light and shadow on body parts:
- Face: highlights (forehead, cheekbones), shadows (under eyes, jawline)
- Chest/torso: highlight and shadow areas
- Arms/hands: light and shadow placement
- Overall: main direction, key/fill ratio, rim lighting, shadow color temp
Added to "detailed" and "extreme" analysis modes.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add prompt_length dropdown (Short/Medium/Long/Free) to control output length
- Default to "Free" (no constraint) for maximum flexibility
- Updated prompts.toml with Z-Image best practices:
- Structured format: composition → subject → clothing → lighting
- Geometric face angles (front view, 45°, profile)
- Specific lighting keywords (soft diffused daylight, rim lighting)
- Cleanup constraints at end (no text, no watermark)
- Added get_length_constraint() to config_loader.py
- Length constraints applied to both single-shot and agentic pipelines
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add sample workflows for Ollama, Groq, OpenRouter, and local QwenVL
- Add vision model warning for Ollama/LM Studio non-vision models (warn but allow)
- Improve basic tier prompts with examples for local models
- Remove numbered lists in favor of flowing instructions
- Add more cleanup patterns for local model output prefixes
- Fix issues #4 (sample workflows) and #5 (local model prompts)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add attention_mode selection (auto/flash_attention_2/sdpa/eager)
- Add torch.compile support for CUDA acceleration (~20-30% speedup)
- Add repetition_penalty and top_p parameters for better output control
- Implement response validation with retry logic for short responses
- Add adaptive resolution based on Qwen model version (Qwen3 vs Qwen2.5)
- Add quality metrics tracking (word count, tokens/sec)
- Add provider-specific cleanup patterns (Groq, Together, Fireworks, etc.)
- Update providers.toml with local model configurations and VRAM guidelines
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Implements externalized configuration using TOML files for:
- Provider tiers (advanced/standard/basic) and stop strings
- Tier-specific system/user prompts for local vs cloud models
- Component prompts for agentic analysis by tier
- Output filter patterns for example text removal
Local models (Ollama, LM Studio) now get simplified prompts
without JSON output or complex numbered instructions.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
