Add Gradio-based Control Panel with Secure Learning and SDR Memory System#19
Add Gradio-based Control Panel with Secure Learning and SDR Memory System#19MASSIVEMAGNETICS wants to merge 1 commit into
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…ycles - Added Gradio-based web GUI to `Victor_GUI/app.py`. - Designed `VictorEngine` to encapsulate logic and provide simple API access for the interface. - Created `ModelAdapter` to intercept calls from the UI, providing dummy intent/emotion fallback for demo purposes while retaining architecture for real models. - Set up SDR memory in `memory/sdr_memory.py` using `.jsonl` appends to store interactions continuously. - Implemented REM Dream Cycle in `memory/dream_cycle.py` to compress interactions and reinforce core agent directives. - Implemented secure queue-based training logic inside `training/learning_queue.py` and `training/auto_train.py` which proposes modifications for human approval instead of immediate core rewrites. - Wrote easy-to-use launch scripts (`launch_windows.bat`, `launch_linux_mac.sh`), added dependencies to a dedicated `requirements.txt`, and documented usage cleanly in a `README.md`. Co-authored-by: MASSIVEMAGNETICS <209589629+MASSIVEMAGNETICS@users.noreply.github.com>
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| test_btn.click(fn=run_self_test, inputs=None, outputs=test_output) | ||
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| if __name__ == "__main__": | ||
| demo.launch(server_name="0.0.0.0", server_port=7860) |
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Launching with server_name="0.0.0.0" exposes the control panel on every network interface, so anyone on the same network/host namespace can access chat, memory, and training controls without additional protection. In environments where this app runs on a shared machine or VM, this is a security regression compared to a localhost-only default and should be restricted (or explicitly gated behind auth/config).
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| @@ -0,0 +1,67 @@ | |||
| import os | |||
| import sys | |||
| import torch | |||
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Importing torch at module import time crashes startup with ModuleNotFoundError before the existing HAS_MODEL fallback can run, so the GUI cannot boot in mock mode on systems without torch. This defeats the adapter’s graceful-degradation path and blocks the app for users who should still be able to run the non-model features.
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| "compressed": True, | ||
| "pattern_found": dominant_intent | ||
| } | ||
| compressed_records.append(reinforcement) |
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Each dream cycle unconditionally appends a fresh identity_reinforcement record, even when all existing memories are already compressed, so repeated REM runs grow the store instead of compressing it. This can steadily bloat memory_store.jsonl and make the "compressed X down to Y" result misleading when users trigger maintenance cycles multiple times.
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Built the initial GUI for Victor out using Gradio, ensuring a strong modular design where the frontend interacts strictly through an adapter
VictorEngine. The backend now actively logs interactions to a simulated "SDR Memory" system (memory_store.jsonl), captures potential learning scenarios using aLearningQueue, and offers a safe way to review system behavior through an approval ledger before making alterations. The system also supports "Dream Cycles" designed to compress data periodically and reinforce agent behavior goals. All instructions and launch scripts are geared toward absolute beginners, ensuring automated setups across Win/Mac/Linux setups.PR created automatically by Jules for task 14127787931182039170 started by @MASSIVEMAGNETICS