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docs: improve README with usage instructions

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  1. README.md +10 -7
  2. requirements.txt +1 -1
README.md CHANGED
@@ -13,16 +13,19 @@ short_description: Negative feedback loop homeostasis simulation
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  # ⚖️ Feedback Loop Homeostasis
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- Simulate a **NegativeFeedbackLoop** controlling a value toward a setpoint. Configure gain, damping, and disturbances to watch convergence, oscillation, or overdamping in real time.
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- ## Features
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- - **6 presets**: Temperature control, oscillating convergence, overdamped, underdamped, disturbance rejection
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- - **Tunable parameters**: Setpoint, gain, damping, iterations, disturbance injection
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- - **Convergence analysis**: Steps to within 1% of setpoint, loop statistics
 
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  ## How It Works
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- The `NegativeFeedbackLoop` computes a correction at each step based on the error (distance from setpoint), scaled by gain and damped to prevent oscillation. This mirrors biological homeostasis thermostats, blood sugar regulation, and neural feedback.
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- [GitHub](https://github.com/coredipper/operon) | [PyPI](https://pypi.org/project/operon-ai/)
 
 
 
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  # ⚖️ Feedback Loop Homeostasis
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+ Simulate a negative feedback loop driving a value toward a setpoint -- like a thermostat, blood sugar regulation, or any biological homeostasis mechanism.
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+ ## What to Try
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+ 1. Select a preset from the **Preset** dropdown (e.g. "Temperature control" or "Underdamped oscillation") and click **Run Simulation** to see the value converge toward the setpoint over time.
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+ 2. Increase the **Gain** slider to see faster convergence, or push it too high to trigger oscillation. Raise **Damping** to suppress overshoot.
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+ 3. Set a **Disturbance step** and **Disturbance magnitude** to inject a sudden perturbation mid-simulation and watch the loop reject it.
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+ 4. Compare "Overdamped" vs. "Underdamped" presets to see the tradeoff between speed and stability.
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  ## How It Works
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+ The NegativeFeedbackLoop computes a correction at each step based on the error (distance from setpoint), scaled by gain and damped to prevent oscillation. This mirrors how biological systems maintain homeostasis -- applying proportional corrections that self-regulate toward equilibrium.
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+ ## Learn More
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+
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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)
requirements.txt CHANGED
@@ -1,2 +1,2 @@
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  gradio>=4.0
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- operon-ai>=0.14.0
 
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  gradio>=4.0
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+ operon-ai>=0.15.0