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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

License

MIT License

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