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by matiasmolinas
172 days ago
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Built a browser-based AI OS where a master agent creates/evolves specialized sub-agents defined in markdown, executes Python via WebAssembly, and learns from past executions via persistent memory. Key features:
- Agent reuse & evolution (80% match rule)
- Python runtime in browser (Pyodide: numpy, scipy, matplotlib)
- Memory system that improves over time
- Virtual file system (localStorage)
- Completely client-side Example: Ask for "FFT signal analysis" → system checks memory → finds/evolves SignalProcessorAgent → generates Python → executes in browser → saves results → records experience → next time runs in seconds. Try it:
https://github.com/EvolvingAgentsLabs/llmos Started as a weekend project exploring self-improving AI systems. Core features working, some rough edges. Feedback welcome, especially on the agent evolution approach and memory structure. |
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