Update app.py

app.py

@@ -1,87 +1,158 @@
 import gradio as gr
 import os
+
 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.passion import apply_passion
 from utils.drama import apply_drama
-from utils.color_model import infer_color, apply_cinematic_blend, render_color
+from utils.color_model import infer_color, render_color
 from utils.visualization import generate_scatter
 
 
-def process_emotion(emotion, drama):
-    preset = EMOTION_PRESETS[emotion]
+# ------------------------------------------------------------
+# Fast Loop Processing (Edge Simulation)
+# ------------------------------------------------------------
+
+def run_pipeline(preset_name, passion, drama):
 
-    raw = preset["raw"]
+    preset = EMOTION_PRESETS[preset_name]
+
+    text = preset["text"]
+    natural = preset["raw"]
     target = preset["target"]
 
-    cinematic = apply_drama(raw, target, drama)
+    # Edge Phase 1 — Natural Extraction
+    extracted = natural
 
-    # 1️⃣ Get cinematic parameters from model
-    model_output = infer_color(cinematic)
+    # Edge Phase 2 — Passion Amplification
+    amplified = apply_passion(extracted, passion)
 
-    # 2️⃣ Apply drama-aware blend toward white
-    blended = apply_cinematic_blend(model_output, drama)
+    # Edge Phase 3 — Cinematic Alignment
+    cinematic = apply_drama(amplified, target, drama)
 
-    # 3️⃣ Render HTML
-    color_block = render_color(blended)
+    # Embedded Phase — Color Model
+    color_params = infer_color(cinematic)
+    color_block = render_color(color_params)
 
-    scatter_fig = generate_scatter(raw, cinematic, emotion, drama)
+    scatter_fig = generate_scatter(extracted, cinematic, preset_name, drama)
 
     return (
-        preset["text"],
-        raw,
+        text,
+        extracted,
+        amplified,
         cinematic,
-        blended,
+        color_params,
         color_block,
         scatter_fig
     )
 
 
-with gr.Blocks(title="VIBE-Eyes 👁️") as demo:
+# ------------------------------------------------------------
+# UI
+# ------------------------------------------------------------
+
+with gr.Blocks(title="VIBE-Eyes — Edge Emotional Intelligence") as demo:
 
     gr.Markdown("# VIBE-Eyes 👁️")
-    gr.Markdown("**Emotion becomes cinema.**")
+    gr.Markdown("## Edge Emotional Intelligence for Robotics")
 
-    with gr.Row():
+    # --------------------------------------------------------
+    # SECTION 1 — Robot Speech
+    # --------------------------------------------------------
+
+    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="Transcript",
+        interactive=False
+    )
+
+    gr.Markdown("---")
+
+    # --------------------------------------------------------
+    # SECTION 2 — Edge Processing
+    # --------------------------------------------------------
+
+    gr.Markdown("### ⚡ Edge Processing — NVIDIA Jetson Orin Nano")
 
-        with gr.Column(scale=1):
+    passion = gr.Slider(
+        minimum=0.0,
+        maximum=3.0,
+        value=2.25,
+        step=0.1,
+        label="Passion (Radial Emotional Amplification)"
+    )
 
-            emotion = gr.Radio(
-                choices=list(EMOTION_PRESETS.keys()),
-                label="Select Emotion",
-                value="Anger (Red)"
-            )
+    drama = gr.Slider(
+        minimum=0.0,
+        maximum=1.5,
+        value=0.65,
+        step=0.05,
+        label="Drama (Cinematic Alignment)"
+    )
 
-            drama = gr.Slider(
-                minimum=0,
-                maximum=1.5,
-                value=0,
-                step=0.05,
-                label="Drama (Cinematic Amplification)"
-            )
+    with gr.Row():
+        natural_output = gr.JSON(label="Natural VAD+CC (Extraction)")
+        amplified_output = gr.JSON(label="After Passion (Radial Gain)")
+        cinematic_output = gr.JSON(label="After Drama (Cinematic Alignment)")
+
+    scatter_output = gr.Plot(label="Valence–Arousal Projection")
+
+    gr.Markdown(
+        """
+        *Note:*  
+        In the full hardware system, a slow baseline loop (Nemotron via Ollama)
+        continuously recalibrates the emotional baseline in parallel.
+        This demo focuses on the real-time fast loop for clarity.
+        """
+    )
 
-        with gr.Column(scale=2):
+    gr.Markdown("---")
 
-            text_output = gr.Textbox(label="Preset Text")
+    # --------------------------------------------------------
+    # SECTION 3 — Embedded Display Module
+    # --------------------------------------------------------
 
-            with gr.Row():
-                raw_output = gr.JSON(label="Raw VAD+CC")
-                cine_output = gr.JSON(label="Cinematic VAD+CC")
+    gr.Markdown("### 💡 Embedded Display Module")
 
-            rgb_output = gr.JSON(label="RGB + E + I")
-            color_display = gr.HTML(label="Rendered Color")
+    rgb_output = gr.JSON(label="Color Model Output (RGB + Expressive Parameters)")
+    color_display = gr.HTML(label="Rendered Expression")
 
-            scatter_output = gr.Plot(label="Valence–Arousal Space")
+    # --------------------------------------------------------
+    # Bind
+    # --------------------------------------------------------
 
-    emotion.change(
-        fn=process_emotion,
-        inputs=[emotion, drama],
+    preset_selector.change(
+        fn=run_pipeline,
+        inputs=[preset_selector, passion, drama],
         outputs=[
-            text_output,
-            raw_output,
-            cine_output,
+            transcript_output,
+            natural_output,
+            amplified_output,
+            cinematic_output,
+            rgb_output,
+            color_display,
+            scatter_output
+        ]
+    )
+
+    passion.change(
+        fn=run_pipeline,
+        inputs=[preset_selector, passion, drama],
+        outputs=[
+            transcript_output,
+            natural_output,
+            amplified_output,
+            cinematic_output,
             rgb_output,
             color_display,
             scatter_output
@@ -89,23 +160,23 @@ with gr.Blocks(title="VIBE-Eyes 👁️") as demo:
     )
 
     drama.change(
-        fn=process_emotion,
-        inputs=[emotion, drama],
+        fn=run_pipeline,
+        inputs=[preset_selector, passion, drama],
         outputs=[
-            text_output,
-            raw_output,
-            cine_output,
+            transcript_output,
+            natural_output,
+            amplified_output,
+            cinematic_output,
             rgb_output,
             color_display,
             scatter_output
         ]
     )
 
+
 demo.launch(
     server_name="0.0.0.0",
     server_port=7860,
-    ssr_mode=False,
     show_error=True,
     debug=False
 )
-