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README.md
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sdk: gradio
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license: apache-2.0
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tags:
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- flux
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- computer-vision
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---
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## Technical Details
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- Optimized FLUX prompt ready for image generation
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- Detailed analysis report with technical specifications
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- Quality score with breakdown across different dimensions
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## License
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Apache 2.0 - See LICENSE file for details
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---
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---
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title: Phramer AI
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emoji: π¬
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colorFrom: blue
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colorTo: purple
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sdk: gradio
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pinned: false
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license: apache-2.0
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tags:
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- multimodal
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- image-to-prompt
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- flux
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- midjourney
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- generative-ai
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- computer-vision
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- cinematic
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- photography
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- bagel
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- pariente-ai
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---
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# Phramer AI
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*By Pariente AI, for MIA TV Series*
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**Logline:** Phramer AI is a multimodal tool that reads an image and turns it into a refined, photo-realistic prompt. Ready for Midjourney, Flux or any generative engine.
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## Overview
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**Phramer AI** is an advanced multimodal system developed by **Pariente AI** for the **MIA TV Series** creative pipeline.
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Upload any image, and Phramer AI will:
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- **Analyze it deeply** using a custom Bagel architecture
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- **Generate a detailed semantic-visual description**
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- **Enhance it** using a curated photographic knowledge base
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- **Output a structured prompt** with camera settings, composition hints, mood, and style β ready for **Flux** or other diffusion-based platforms
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Whether you're creating cinematic storyboards, photorealistic scenes, or exploring visual concepts, Phramer AI bridges the gap between image understanding and generative prompting.
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## Key Features
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### π **Deep Multimodal Analysis**
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- Custom Bagel-7B architecture for advanced image understanding
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- Semantic-visual analysis with professional photography insights
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- Context-aware scene detection and composition analysis
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### π― **Multi-Engine Optimization**
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- **Flux-ready prompts** with technical specifications
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- **Midjourney compatibility** with style and mood descriptors
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- **Universal format** compatible with major generative engines
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### πΈ **Professional Photography Knowledge**
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- Curated database of camera settings and equipment
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- Lighting techniques and composition principles
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- Technical parameters optimized for photorealistic output
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### π¬ **Cinematic Focus**
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- Designed for TV series and film production workflows
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- Storyboard and concept art optimization
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- Dramatic lighting and mood analysis
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## How It Works
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1. **Image Upload** - Support for JPG, PNG, WebP formats up to 1024px
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2. **Bagel Analysis** - Custom architecture analyzes visual content and composition
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3. **Knowledge Enhancement** - Professional photography database enriches the analysis
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4. **Prompt Generation** - Structured output with technical details and artistic direction
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5. **Multi-Engine Ready** - Copy and use in Flux, Midjourney, or any diffusion platform
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## Technical Specifications
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### Architecture
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- **Base Model**: Custom Bagel-7B multimodal architecture
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- **Vision Processing**: Advanced semantic-visual understanding
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- **Knowledge Integration**: Professional photography database with 30+ years expertise
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- **Output Optimization**: Multi-engine compatibility layer
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### Processing Pipeline
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- **Image Preprocessing**: Automatic optimization and format conversion
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- **Multimodal Analysis**: Deep scene understanding with technical assessment
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- **Professional Enhancement**: Camera, lighting, and composition recommendations
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- **Prompt Structuring**: Organized output with technical and artistic elements
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### Supported Platforms
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- **Flux** - Primary optimization target with technical specifications
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- **Midjourney** - Style and mood descriptors
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- **Stable Diffusion** - Technical parameter integration
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- **Other Engines** - Universal prompt format compatibility
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## Use Cases
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### π¬ **Film & TV Production**
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- Storyboard creation and visualization
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- Concept art development
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- Scene planning and mood reference
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- Visual consistency across episodes
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### πΈ **Photography Reference**
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- Lighting setup recreation
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- Camera configuration guidance
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- Composition analysis and improvement
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- Technical parameter optimization
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### π¨ **Creative Development**
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- Visual concept exploration
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- Style reference generation
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- Mood and atmosphere studies
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- Character and environment design
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### πΌ **Commercial Applications**
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- Product visualization
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- Marketing material creation
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- Brand consistency maintenance
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- Commercial photography planning
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## Example Workflow
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```
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Input: Portrait photograph of a person in dramatic lighting
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Phramer AI Analysis:
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βββ Scene Detection: Studio portrait with dramatic side lighting
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βββ Technical Analysis: Professional setup with controlled lighting
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βββ Camera Recommendation: Canon EOS R5 with 85mm f/1.4 lens
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βββ Enhancement: Cinematic mood with film-quality specifications
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Output Prompt:
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"A cinematic portrait of [subject description], shot on Canon EOS R5
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with 85mm f/1.4 lens at f/2.8, dramatic side lighting with subtle rim
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light, professional studio setup, film grain, photorealistic,
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ultra-detailed, commercial photography style"
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```
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## Quality Scoring
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Phramer AI evaluates generated prompts across multiple dimensions:
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- **Prompt Quality** (25%) - Content detail and description accuracy
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- **Technical Details** (25%) - Camera settings and equipment specifications
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- **Professional Photography** (25%) - Lighting, composition, and technical expertise
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- **Multi-Engine Optimization** (25%) - Compatibility and enhancement features
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Scores range from 0-100 with grades from POOR to LEGENDARY.
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## Installation & Usage
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### Requirements
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- Python 3.8+
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- CUDA-compatible GPU (recommended)
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- 8GB+ RAM
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- Internet connection for model access
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### Local Setup
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```bash
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git clone [repository-url]
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cd phramer-ai
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pip install -r requirements.txt
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python app.py
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```
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### Cloud Usage
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Available on Hugging Face Spaces with instant access - no installation required.
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## API Integration
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Phramer AI provides a simple API for integration into existing workflows:
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```python
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from phramer import PhramerlAI
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phramer = PhramerAI()
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prompt, metadata = phramer.analyze_image("path/to/image.jpg")
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print(f"Generated prompt: {prompt}")
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```
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## Performance
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- **Average Processing Time**: 2-4 seconds per image
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- **Supported Image Size**: Up to 1024x1024 pixels
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- **Batch Processing**: Multiple images with queue management
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- **Memory Optimization**: Automatic cleanup and resource management
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## Roadmap
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### Version 2.1 (Coming Soon)
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- Video frame analysis
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- Batch processing improvements
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- Additional engine-specific optimizations
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- Enhanced cinematic analysis
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### Version 2.2 (Planned)
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- Style transfer integration
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- Custom knowledge base training
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- API rate limiting and authentication
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- Advanced composition analysis
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## Technical Details
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### Model Architecture
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- **Bagel-7B Base**: Advanced vision-language model
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- **Custom Training**: Optimized for prompt generation
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- **Knowledge Integration**: Professional photography database
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- **Multi-Modal Processing**: Image + text understanding
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### Optimization Features
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- **Memory Efficient**: Automatic resource management
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- **GPU Acceleration**: CUDA optimization when available
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- **Batch Processing**: Multiple image support
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- **Error Handling**: Robust fallback systems
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## Contributing
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We welcome contributions to improve Phramer AI:
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1. Fork the repository
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2. Create a feature branch
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3. Submit a pull request with detailed description
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4. Follow coding standards and include tests
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## License
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Apache 2.0 - See LICENSE file for details.
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## Support
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For technical support, feature requests, or collaboration inquiries:
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- **Technical Issues**: Create an issue in the repository
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- **Feature Requests**: Submit detailed proposals
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- **Commercial Licensing**: Contact Pariente AI
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- **MIA TV Series Integration**: Production team coordination
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## Credits
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**Phramer AI** is developed by **Pariente AI** specifically for the **MIA TV Series** production pipeline.
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### Core Technologies
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- Bagel-7B multimodal architecture
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- Professional photography knowledge base
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- Advanced prompt optimization algorithms
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- Multi-engine compatibility layer
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### Research & Development
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- **Pariente AI** - Advanced multimodal AI research
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- **MIA TV Series** - Creative pipeline integration
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- **Professional Photography Consultants** - 30+ years expertise database
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- **Community Contributors** - Feature improvements and testing
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**Pariente AI** β’ Advanced Multimodal AI Research & Development β’ **MIA TV Series**
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*Bridging the gap between image understanding and generative prompting*
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