Project Overview: Seeking a developer to implement DeepSeek's open-source LLM (67B parameters) with browser-use automation capabilities. The system will enable AI-controlled browser interactions using the DeepSeek model as the reasoning engine.
Key Technical Components:
- DeepSeek LLM 67B implementation for text generation/comprehension
- browser-use framework for browser automation and control
- Integration layer between DeepSeek LLM and browser-use
- Cloud infrastructure deployment
Primary Responsibilities:
- Set up DeepSeek LLM 67B model on cloud infrastructure
- Implement browser-use integration with proper async handling
- Develop custom prompts and pipelines for browser control
- Create system architecture for efficient model-browser communication
- Optimize model response time and browser interaction latency
Required Technical Skills:
- Python development with async/await patterns
- Experience with LLM deployment and optimization
- Familiar with Hugging Face Transformers library
- Playwright/browser automation expertise
- Docker and containerization
- Cloud platform deployment (AWS/GCP/Azure)
Required Knowledge:
- DeepSeek LLM architecture and capabilities
- browser-use framework and its API
- WebSocket and async programming
- LLM prompt engineering
- Browser automation patterns
Project Deliverables:
- Functional DeepSeek LLM deployment
- Working browser-use integration
- Documentation including:
- Setup/deployment guide
- API documentation
- Example use cases
- Maintenance procedures
- Performance optimization suggestions
Technical Implementation Details:
- Use DeepSeek's official HuggingFace implementation
- Implement browser-use Agent class integration
- Set up proper async handlers for browser control
- Create custom prompting system for browser tasks
- Implement error handling and recovery