app.py

# app.py — Affection 👁️ (Hugging Face Space)

import os
import gradio as gr
import matplotlib.pyplot as plt

os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
os.environ["HF_HUB_DISABLE_TELEMETRY"] = "1"
os.environ["SPACES_DISABLE_RELOAD"] = "1"

from utils.presets import EMOTION_PRESETS
from utils.drama import apply_drama
from utils.color_model import infer_color, render_color


# ------------------------------------------------------------
# Passion (Radial Amplification)
# ------------------------------------------------------------
def apply_passion(raw: dict, passion: float) -> dict:
    passion = max(0.0, min(3.5, float(passion)))
    out = {}

    for k, v in raw.items():
        v = float(v)
        if k in ("V", "A", "D"):
            delta = v - 0.5
            magnitude = abs(delta)
            gain = 1.0 + passion * magnitude
            out[k] = max(0.0, min(1.0, 0.5 + delta * gain))
        else:
            out[k] = max(0.0, min(1.0, v))

    return out


# ------------------------------------------------------------
# Valence–Arousal Visualization (2D Projection)
# ------------------------------------------------------------
def generate_scatter(raw, amplified, cinematic, target, target_name, passion, drama):

    fig, ax = plt.subplots(figsize=(6, 7))  # slightly taller
    plt.subplots_adjust(right=0.75)  # leave room for legend

    # ----------------------------------
    # Background Anchors
    # ----------------------------------
    for name, preset in EMOTION_PRESETS.items():
        t = preset["target"]
        ax.scatter(t["V"], t["A"], alpha=0.06, s=90, color="#DDDDDD")

    # ----------------------------------
    # Trajectory Points (Styled)
    # ----------------------------------

    # 1️⃣ Natural — light grey thin border
    ax.scatter(
        raw["V"], raw["A"],
        s=180,
        facecolor="#F0F0F0",
        edgecolor="#CCCCCC",
        linewidth=1,
        label="Natural"
    )

    # 2️⃣ After Passion — medium grey
    ax.scatter(
        amplified["V"], amplified["A"],
        s=180,
        facecolor="#9E9E9E",
        edgecolor="#666666",
        linewidth=1.5,
        label="After Passion"
    )

    # 3️⃣ After Drama — dark grey thin border
    ax.scatter(
        cinematic["V"], cinematic["A"],
        s=220,
        facecolor="#2F2F2F",
        edgecolor="black",
        linewidth=1,
        label="After Drama"
    )

    # Cinematic Anchor
    ax.scatter(
        target["V"],
        target["A"],
        s=180,
        marker="X",
        color="#E74C3C",
        edgecolor="black",
        linewidth=1.2,
        label=f"Anchor ({target_name})"
    )

    # ----------------------------------
    # Dynamic Zoom (20% padded)
    # ----------------------------------
    xs = [raw["V"], amplified["V"], cinematic["V"], target["V"]]
    ys = [raw["A"], amplified["A"], cinematic["A"], target["A"]]

    min_x, max_x = min(xs), max(xs)
    min_y, max_y = min(ys), max(ys)

    span_x = max_x - min_x
    span_y = max_y - min_y
    span = max(span_x, span_y)
    span = max(span, 0.05)

    padding = span * 0.20
    center_x = (min_x + max_x) / 2
    center_y = (min_y + max_y) / 2

    # shift center slightly upward
    center_y += span * 0.10

    half_range = (span / 2) + padding

    ax.set_xlim(center_x - half_range, center_x + half_range)
    ax.set_ylim(center_y - half_range, center_y + half_range)

    ax.set_aspect('equal', adjustable='box')

    # ----------------------------------
    # Proportional Arrows
    # ----------------------------------
    arrow_head = span * 0.035

    ax.arrow(
        raw["V"], raw["A"],
        amplified["V"] - raw["V"],
        amplified["A"] - raw["A"],
        head_width=arrow_head,
        length_includes_head=True,
        color="#888888",
        linestyle="--",
        linewidth=1.8,
        alpha=0.7
    )

    ax.arrow(
        amplified["V"], amplified["A"],
        cinematic["V"] - amplified["V"],
        cinematic["A"] - amplified["A"],
        head_width=arrow_head,
        length_includes_head=True,
        color="#444444",
        linestyle="-",
        linewidth=2,
        alpha=0.9
    )

    # ----------------------------------
    # Labels & Legend
    # ----------------------------------
    ax.set_xlabel("Valence")
    ax.set_ylabel("Arousal")
    ax.set_title(f"{target_name}\nPassion={round(passion,2)} | Drama={round(drama,2)}")

    ax.grid(alpha=0.12)

    # Move legend outside plot
    ax.legend(loc="center left", bbox_to_anchor=(1.02, 0.5), frameon=False)

    plt.tight_layout()
    return fig


# ------------------------------------------------------------
# Fast-Loop Simulation
# ------------------------------------------------------------
def run_pipeline(preset_name, passion, drama):

    preset = EMOTION_PRESETS[preset_name]

    text = preset["text"]
    natural = preset["raw"]
    target = preset["target"]

    amplified = apply_passion(natural, passion)
    cinematic = apply_drama(amplified, target, drama)

    color_params = infer_color(cinematic)
    color_block = render_color(color_params)

    fig = generate_scatter(
        natural,
        amplified,
        cinematic,
        target,
        preset_name,
        passion,
        drama
    )

    return (
        text,
        natural,
        amplified,
        cinematic,
        color_params,
        color_block,
        fig
    )


# ------------------------------------------------------------
# UI
# ------------------------------------------------------------
with gr.Blocks(title="Affection 👁️ — Edge Emotional Intelligence") as demo:

    gr.Markdown("# Affection 👁️")
    gr.Markdown("## Simulation Layer for an Edge AI Emotional Robotics System")

    gr.Markdown("### 🗣 Robot Speech")

    preset_selector = gr.Radio(
        choices=list(EMOTION_PRESETS.keys()),
        label="Select Transcript Sample",
        value=list(EMOTION_PRESETS.keys())[0],
    )

    transcript_output = gr.Textbox(label="Input Transcript", interactive=False)

    gr.Markdown("---")

    gr.Markdown("### ⚡ Edge Affect Processing")

    with gr.Row():
        passion = gr.Slider(0.0, 3.0, value=2.25, step=0.1, label="Passion")
        drama = gr.Slider(0.0, 1.5, value=0.65, step=0.05, label="Drama")

    with gr.Row():
        natural_output = gr.JSON(label="Natural")
        amplified_output = gr.JSON(label="After Passion")
        cinematic_output = gr.JSON(label="After Drama")

    scatter_output = gr.Plot(label="Valence–Arousal Projection")

    gr.Markdown("---")

    gr.Markdown("### 💡 Emotional Expression")

    rgb_output = gr.JSON(label="Model Output")
    color_display = gr.HTML(label="Rendered Expression")

    outputs = [
        transcript_output,
        natural_output,
        amplified_output,
        cinematic_output,
        rgb_output,
        color_display,
        scatter_output
    ]

    preset_selector.change(fn=run_pipeline, inputs=[preset_selector, passion, drama], outputs=outputs)
    passion.change(fn=run_pipeline, inputs=[preset_selector, passion, drama], outputs=outputs)
    drama.change(fn=run_pipeline, inputs=[preset_selector, passion, drama], outputs=outputs)

    demo.load(fn=run_pipeline, inputs=[preset_selector, passion, drama], outputs=outputs)

demo.launch(server_name="0.0.0.0", server_port=7860)