Hardware/Software Codesign Space Exploration and Optimization Environment for Embodied AI systems
Project description
Embodied AI Architect
A design environment for creating and evaluating autonomous agents, with hardware/software codesign space exploration and optimization.
Features
- Model Analysis: Analyze PyTorch model structure and compute requirements
- Hardware Profiling: Recommendations for edge/cloud deployment
- Multi-Hardware Benchmarking: Local CPU, remote SSH, Kubernetes backends
- Interactive Chat: Claude-powered architect for design decisions
- Codebase Analysis: Scan and assess application codebases for hardware deployment
- SoC Optimization: LangGraph-based RTL optimization loop (experimental)
Installation
pip install embodied-ai-architect
With optional dependencies:
# Remote SSH benchmarking
pip install embodied-ai-architect[remote]
# Kubernetes benchmarking
pip install embodied-ai-architect[kubernetes]
# Interactive chat (requires ANTHROPIC_API_KEY)
pip install embodied-ai-architect[chat]
# All optional dependencies
pip install embodied-ai-architect[all]
Usage
# Show available commands
branes --help
# Analyze a PyTorch model
branes analyze model.pt
# Run full workflow
branes workflow run model.pt
# Benchmark on local CPU
branes benchmark model.pt --backend local
# Scan and assess a codebase for hardware deployment
branes codebase scan /path/to/project
branes codebase assess /path/to/project --hardware jetson_orin
# Interactive chat session
export ANTHROPIC_API_KEY=your-key-here
branes chat
Environment Variables
| Variable | Description |
|---|---|
ANTHROPIC_API_KEY |
Required for Claude-powered features (chat, codebase analysis) |
Documentation
For full documentation, development setup, and contributing guidelines, visit the GitHub repository.
Related Projects
- embodied-schemas: Shared Pydantic schemas and hardware catalog
- graphs: Analysis tools and roofline models
License
MIT License
Project details
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