docs: improve README with usage instructions
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README.md
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short_description: Escalating healing when stagnation is detected
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# Operon Epiplexity Healing Cascade
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Detect epistemic stagnation
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##
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- **Presets**: Healthy agent, stagnant agent, critical with regeneration
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##
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EpiplexityMonitor
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short_description: Escalating healing when stagnation is detected
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---
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# 💡 Operon Epiplexity Healing Cascade
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Detect epistemic stagnation and escalate through increasingly aggressive healing -- autophagy, regeneration, and abort -- like an immune system ramping up its response when initial measures fail.
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## What to Try
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1. Select a preset from the **Preset** dropdown (e.g. "Stagnant agent" or "Critical with regeneration") and click **Run Cascade** to see how stagnation triggers escalating healing interventions.
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2. Adjust the **Stagnation threshold** and **Autophagy threshold** sliders to change when each healing level kicks in, then re-run to compare outcomes.
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3. Try the "Healthy agent" preset to confirm that a well-performing agent passes through without triggering any healing.
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## How It Works
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The EpiplexityMonitor watches for declining novelty in agent output. When stagnation is detected, the cascade escalates: first autophagy prunes noisy context, then regeneration respawns the worker with clean state, and finally abort halts the pipeline if nothing else works.
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## Learn More
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[GitHub](https://github.com/coredipper/operon) | [PyPI](https://pypi.org/project/operon-ai/) | [Paper](https://github.com/coredipper/operon/tree/main/article)
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requirements.txt
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gradio>=4.0
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operon-ai>=0.
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gradio>=4.0
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operon-ai>=0.15.0
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