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license: apache-2.0
base_model:
- openai/gpt-oss-120b
- deepseek-ai/DeepSeek-V3.1
tags:
- chat-interface
- gpt-oss-120b-chat-interface
---
# Model Card: GPT-OSS-120B Chat Interface
```markdown
---
license: apache-2.0
tags:
- mlx
- chat-ui
- local-ai
- gpt
- python
- pyqt5
---
# GPT-OSS-120B Chat Interface
## Model Description
This is a modern, feature-rich chat interface for the GPT-OSS-120B model running on Apple MLX framework. The interface provides a user-friendly way to interact with the 120-billion parameter open-source language model locally on Apple Silicon hardware.
## Model Overview
- **Model Name:** GPT-OSS-120B (4-bit quantized)
- **Framework:** Apple MLX
- **Interface:** PyQt5-based desktop application
- **Hardware Requirements:** Apple Silicon with sufficient RAM (recommended: M3 Ultra with 512GB RAM)
## Features
- 🎨 Modern, responsive UI with PyQt5
- 💬 Real-time chat interface with message history
- ⚡ Local inference on Apple Silicon
- 📝 Markdown support with syntax highlighting
- 💾 Conversation export functionality
- ⚙️ Adjustable generation parameters
- 🎯 Code block detection and formatting
- 📊 Performance monitoring
## UI Architecture Diagram
```
┌─────────────────────────────────────────────────────────────────────────┐
│ MAIN WINDOW │
├───────────────────────────────┬─────────────────────────────────────────┤
│ LEFT PANEL │ CHAT AREA │
│ │ │
│ ┌─────────────────────────┐ │ ┌───────────────────────────────────┐ │
│ │ MODEL INFO │ │ │ │ │
│ │ - Model details │ │ │ ┌─────────────────────────────┐ │ │
│ │ - Hardware specs │ │ │ │ CHAT MESSAGE (User) │ │ │
│ │ - Performance metrics │ │ │ │ - Avatar + timestamp │ │ │
│ │ │ │ │ │ - Formatted content │ │ │
│ └─────────────────────────┘ │ │ └─────────────────────────────┘ │ │
│ │ │ │ │
│ ┌─────────────────────────┐ │ │ ┌─────────────────────────────┐ │ │
│ │ GENERATION SETTINGS │ │ │ │ CHAT MESSAGE (Assistant) │ │ │
│ │ - Max tokens control │ │ │ │ - Avatar + timestamp │ │ │
│ │ │ │ │ │ - Formatted content │ │ │
│ └─────────────────────────┘ │ │ │ - Generation time │ │ │
│ │ │ └─────────────────────────────┘ │ │
│ │ │ ... │ │
│ ┌─────────────────────────┐ │ │ │ │
│ │ CONVERSATION TOOLS │ │ │ ┌─────────────────────────────┐ │ │
│ │ - Clear conversation │ │ │ │ INPUT AREA │ │ │
│ │ - Export chat │ │ │ │ - Multi-line text input │ │ │
│ │ │ │ │ │ - Character counter │ │ │
│ └─────────────────────────┘ │ │ │ - Send button │ │ │
│ │ │ └─────────────────────────────┘ │ │
│ ┌─────────────────────────┐ │ │ │ │
│ │ STATUS INDICATOR │ │ │ │ │
│ │ - Loading/ready state │ │ │ │ │
│ │ │ │ │ │ │
│ └─────────────────────────┘ │ │ │ │
│ │ │ │ │
└───────────────────────────────┴───────────────────────────────────────┘
```
## Development
This interface was developed using PyQt5 and integrates with the MLX-LM library for efficient inference on Apple Silicon. The UI features a responsive design with:
1. **Threaded Operations:** Model loading and text generation run in background threads
2. **Custom Widgets:** Specialized chat message widgets with formatting
3. **Syntax Highlighting:** Code detection and highlighting in responses
4. **Modern Styling:** Clean, professional interface with appropriate spacing and colors
## DeepSeek Involvement
The `gpt_oss_ui.py` Python script was created with assistance from DeepSeek's AI models, which helped design the architecture, implement the PyQt5 interface components, and ensure proper integration with the MLX inference backend.
## Usage
1. Install requirements: `pip install PyQt5 markdown mlx-lm`
2. Run the application: `python gpt_oss_ui.py`
3. Wait for model to load (first time will download the model)
4. Start chatting with the GPT-OSS-120B model
## Performance
On an M3 Ultra with 512GB RAM:
- Model load time: ~2-3 minutes (first time)
- Inference speed: ~95 tokens/second
- Memory usage: Optimized with 4-bit quantization
## Limitations
- Requires significant RAM for the 120B parameter model
- Currently only supports Apple Silicon hardware
- Model loading can be time-consuming on first run
## Ethical Considerations
This interface is designed for local use, ensuring privacy as all processing happens on-device. Users should still follow responsible AI practices when using the model.
``` |