"""
Extropy Engine, XP formula demo.

This Space runs the canonical Extropy XP formula faithfully ported from the
TypeScript source of record at:
  github.com/00ranman/extropy-engine -> packages/xp-formula/src/index.ts

    XP = R * F * dS * (w . E) * log(1 / Ts)

where
    R   Rarity multiplier (action-class scarcity, NOT actor reputation)
    F   Frequency-of-decay penalty (1.0 = first occurrence of this action class)
    dS  Verified entropy reduction, must be > 0 to mint
    w   Weight vector over effort dimensions
    E   Energy/effort vector (same length as w)
    Ts  Timestamp decay factor in (0, 1], computed as exp(-lambda * dt)

Reputation never enters XP minting. That is the whole point.
"""

import math
import gradio as gr

# Eight canonical entropy domains and their causal-closure speeds c_L,
# from packages/contracts/src/types.ts. The irreducible value form is
# XP = dS / c_L^2: slower closure (smaller c_L) means higher value per unit dS.
CAUSAL_CLOSURE_SPEEDS = {
    "cognitive": 1e-6,
    "code": 1e-4,
    "social": 1e-3,
    "economic": 1e-2,
    "thermodynamic": 1e-4,
    "informational": 1e-5,
    "governance": 1e-3,
    "temporal": 1e-6,
}
DOMAINS = list(CAUSAL_CLOSURE_SPEEDS.keys())


def compute_xp(R, F, dS, w, E, Ts):
    """Faithful port of computeXP. Returns (xp, breakdown, valid, reason)."""
    if dS <= 0:
        return 0.0, {"R": R, "F": F, "deltaS": dS, "wDotE": 0.0, "logDecay": 0.0}, False, "deltaS must be > 0"
    if Ts <= 0 or Ts > 1:
        return 0.0, {"R": R, "F": F, "deltaS": dS, "wDotE": 0.0, "logDecay": 0.0}, False, "Ts must be in (0, 1]"
    if len(w) != len(E):
        return 0.0, {"R": R, "F": F, "deltaS": dS, "wDotE": 0.0, "logDecay": 0.0}, False, "w and E must have equal length"

    w_dot_e = sum(wi * ei for wi, ei in zip(w, E))
    log_decay = math.log(1.0 / Ts)
    xp = R * F * dS * w_dot_e * log_decay
    return max(0.0, xp), {
        "R": R, "F": F, "deltaS": dS, "wDotE": w_dot_e, "logDecay": log_decay,
    }, True, None


def timestamp_decay(dt_seconds, lam=0.001):
    return math.exp(-lam * dt_seconds)


def run(R, F, dS, w_cog, w_phys, w_temp, e_cog, e_phys, e_temp, dt_hours, lam, domain):
    w = [w_cog, w_phys, w_temp]
    E = [e_cog, e_phys, e_temp]
    Ts = timestamp_decay(dt_hours * 3600.0, lam)
    xp, bd, valid, reason = compute_xp(R, F, dS, w, E, Ts)

    c_l = CAUSAL_CLOSURE_SPEEDS[domain]
    irreducible = dS / (c_l ** 2)

    if not valid:
        verdict = f"NO MINT. Precondition failed: {reason}"
    else:
        verdict = f"MINT: {xp:,.4f} XP"

    lines = [
        f"### {verdict}",
        "",
        f"Ts (timestamp decay) = exp(-{lam} x {dt_hours*3600:.0f}s) = **{Ts:.6f}**",
        "",
        "_Note: production xp-mint caps the log(1/Ts) recency term to prevent runaway values on long-settled loops. This demo shows the raw formula._",
        "",
        "| Term | Value |",
        "| --- | --- |",
        f"| R (rarity) | {bd['R']:.4f} |",
        f"| F (frequency-of-decay) | {bd['F']:.4f} |",
        f"| dS (entropy reduction) | {bd['deltaS']:.4f} |",
        f"| w . E (effort) | {bd['wDotE']:.4f} |",
        f"| log(1/Ts) (recency) | {bd['logDecay']:.4f} |",
        f"| **XP** | **{xp:,.4f}** |",
        "",
        f"Domain **{domain}** has causal-closure speed c_L = {c_l:g}. "
        f"Irreducible value form XP = dS / c_L^2 = **{irreducible:,.3g}**. "
        "Slower-closing domains (cognitive, temporal) reward the same dS far more "
        "than fast-closing ones (economic), because the loop is harder to close.",
    ]
    return "\n".join(lines)


INTRO = """
# Extropy Engine, XP formula demo

The unit of value is entropy reduction. This is not a metaphor.

This demo runs the **canonical XP formula** straight from the source of record,
[`packages/xp-formula`](https://github.com/00ranman/extropy-engine/blob/main/packages/xp-formula/src/index.ts).
Move the sliders and watch a contribution get scored. Set dS to 0 or push Ts out
of range to see the mint preconditions fail closed.

XP = R x F x dS x (w . E) x log(1 / Ts). Reputation never enters this formula.

Paper: [An Emergence-First Grand Unified Theory](https://www.academia.edu/167360291).
Discussion: [open thread](https://www.academia.edu/s/b1ff6dbe50).
"""

with gr.Blocks(title="Extropy Engine, XP formula demo") as demo:
    gr.Markdown(INTRO)
    with gr.Row():
        with gr.Column():
            R = gr.Slider(0.0, 10.0, value=2.0, step=0.1, label="R, rarity (action-class scarcity)")
            F = gr.Slider(0.0, 1.0, value=1.0, step=0.01, label="F, frequency-of-decay (1.0 = first time)")
            dS = gr.Slider(-1.0, 50.0, value=12.0, step=0.5, label="dS, verified entropy reduction (must be > 0)")
            gr.Markdown("**Effort: weights w and energy E over (cognitive, physical, temporal)**")
            with gr.Row():
                w_cog = gr.Slider(0.0, 1.0, value=0.5, step=0.05, label="w cognitive")
                w_phys = gr.Slider(0.0, 1.0, value=0.3, step=0.05, label="w physical")
                w_temp = gr.Slider(0.0, 1.0, value=0.2, step=0.05, label="w temporal")
            with gr.Row():
                e_cog = gr.Slider(0.0, 10.0, value=6.0, step=0.5, label="E cognitive")
                e_phys = gr.Slider(0.0, 10.0, value=2.0, step=0.5, label="E physical")
                e_temp = gr.Slider(0.0, 10.0, value=4.0, step=0.5, label="E temporal")
            dt_hours = gr.Slider(0.0, 48.0, value=2.0, step=0.5, label="Elapsed time since trigger (hours)")
            lam = gr.Slider(0.0001, 0.01, value=0.001, step=0.0001, label="lambda, decay constant")
            domain = gr.Dropdown(DOMAINS, value="cognitive", label="Entropy domain")
            btn = gr.Button("Score contribution", variant="primary")
        with gr.Column():
            out = gr.Markdown()

    inputs = [R, F, dS, w_cog, w_phys, w_temp, e_cog, e_phys, e_temp, dt_hours, lam, domain]
    btn.click(run, inputs=inputs, outputs=out)
    demo.load(run, inputs=inputs, outputs=out)

if __name__ == "__main__":
    demo.launch()