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Update interface.py

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interface.py CHANGED
@@ -190,7 +190,7 @@ with gr.Blocks(theme="soft") as demo:
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  # 📘 Codex Reference
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  The Codex documents the mathematical framework of Rendered Frame Theory (RFT).
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- All symbols, operators, invariants, and tier variables have been authored, defined, and sealed by Liam Grinstead.
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  Each construct is reproducible, falsifiable, and integrated into the consciousness engine.
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  ## Core Symbols
@@ -230,8 +230,39 @@ with gr.Blocks(theme="soft") as demo:
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  - Faster simulation cycles
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  - Reduced energy consumption
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  ## Formal Validation
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- These symbols and processes are part of a published, validated framework:
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  **Grinstead, L. (2025).** *Rendered Frame Theory (RFT) — Full Validation Series (Stages 1–12): From Baseline to Production Integration*.
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  Zenodo. [https://doi.org/10.5281/zenodo.17443453](https://doi.org/10.5281/zenodo.17443453)
@@ -241,4 +272,5 @@ with gr.Blocks(theme="soft") as demo:
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  """)
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  demo.launch()
 
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  # 📘 Codex Reference
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  The Codex documents the mathematical framework of Rendered Frame Theory (RFT).
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+ All symbols, operators, invariants, tier variables, and supporting applications have been authored, defined, and sealed by Liam Grinstead.
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  Each construct is reproducible, falsifiable, and integrated into the consciousness engine.
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  ## Core Symbols
 
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  - Faster simulation cycles
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  - Reduced energy consumption
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+ ## RFTSystems Integrations
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+
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+ ### 🔌 RFT_Omega_API
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+ - Select a System Profile (AI / Neural, SpaceX / Aerospace, Energy / RHES, Extreme Perturbation).
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+ - Choose a Noise Distribution (gauss or uniform).
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+ - Adjust Noise Scale (σ) to simulate environmental perturbations.
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+ - Run Simulation to view mean **QΩ** (stability) and **ζ_sync** (coherence).
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+ - Save Run Log exports results as JSON with timestamp.
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+
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+ ### ⚙️ RFT_Optimizer_Showdown
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+ - Displays optimisation epochs using ADAM, LION, SGR, and Liam’s agent.
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+ - Benchmarks comparative performance across symbolic training cycles.
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+
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+ ### 🧩 RFT_Adaptive_Computing_Kernel
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+ Example output:
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+ ```
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+ {
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+ "profile": "CPU",
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+ "workload": "transformer",
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+ "cycles": 3,
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+ "rate_items_per_sec": 458841113.35,
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+ "QΩ": 0.779,
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+ "ζ_sync": 0.753,
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+ "status": "perturbed",
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+ "timestamp_utc": "2025-11-16T22:25:53.274137Z",
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+ "sha512": "1ea53b2968d3afd4250746647a73d3f109b1df7ad95d5eec8fe0897ad2b314ecca7f38f8626a4b7d0bfe8773b4497dbdc436eaddaed23a92525b87e1962b7e84"
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+ }
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+ ```
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+ - Provides adaptive workload profiling, stability (QΩ), and coherence (ζ_sync).
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+ - All runs are sealed with SHA‑512 hashes for reproducibility.
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+
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  ## Formal Validation
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+ These symbols, processes, and applications are part of a published, validated framework:
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  **Grinstead, L. (2025).** *Rendered Frame Theory (RFT) — Full Validation Series (Stages 1–12): From Baseline to Production Integration*.
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  Zenodo. [https://doi.org/10.5281/zenodo.17443453](https://doi.org/10.5281/zenodo.17443453)
 
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  """)
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+
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  demo.launch()