Update app.py

app.py

@@ -33,10 +33,9 @@ emotion_tokenizer = AutoTokenizer.from_pretrained(emotion_model_name)
 emotion_model = AutoModelForSequenceClassification.from_pretrained(emotion_model_name)
 
 # ---------- constants ----------
-CSV_PATH_PLUS  = "la matrice plus.csv"   # pathways + colors + narrative pieces
+CSV_PATH_PLUS  = "la matrice plus.csv"   # pathways + colors + phrase parts
 CSV_PATH_COLOR = "la matrice.csv"        # color lexicon
 
-# only explicit pathways (no Auto here)
 SEQUENCE_ALIASES = {
     "Direct": "direct",
     "Fem": "feminine",
@@ -99,7 +98,7 @@ GNH_COLORS: Dict[str, str] = {
     "Cultural Diversity": "#9370db",
 }
 
-# ---------- load pathway → colors & phrase (plus) ----------
+# ---------- load pathway → colors & phrase ----------
 def load_pathway_info(csv_path_plus: str):
     df = pd.read_csv(csv_path_plus)
     keys = set(SEQUENCE_ALIASES.values())
@@ -111,10 +110,10 @@ def load_pathway_info(csv_path_plus: str):
     cols_for_phrase = [c for c in df.columns if c not in ("color", "r", "g", "b")]
     for _, row in rows.iterrows():
         key = str(row["color"]).strip().lower()
-        # colors list is in column 'r' (comma/space separated), supports 2–8
+        # colors in 'r' as comma/space separated list (supports 2–8)
         colors_field = str(row.get("r", "") or "")
         colors = [c.strip().lower() for c in re.split(r"[,\s]+", colors_field) if c.strip()]
-        seq_to_colors[key] = list(dict.fromkeys(colors))  # dedupe, keep order
+        seq_to_colors[key] = list(dict.fromkeys(colors))  # dedupe
 
         vals = []
         for c in cols_for_phrase:
@@ -130,7 +129,7 @@ def load_pathway_info(csv_path_plus: str):
 
 SEQ_TO_COLORS, SEQ_PHRASE = load_pathway_info(CSV_PATH_PLUS)
 
-# ---------- load color lexicon (color CSV) ----------
+# ---------- load color lexicon ----------
 def _find_col(df: pd.DataFrame, candidates: List[str]) -> str | None:
     names = {c.lower(): c for c in df.columns}
     for c in candidates:
@@ -247,7 +246,7 @@ def chip_html_for(color: str, mode: str, max_words: int = 4) -> str:
         dot = f"<span style='display:inline-block;width:12px;height:12px;border-radius:50%;background:{hex_color};margin-right:6px;border:1px solid #999;vertical-align:middle'></span>"
         pill = f"<span style='display:inline-block;margin:2px 6px;padding:2px 8px;border-radius:12px;background:#eee;font-size:12px'>{domain} · {sim:.2f}</span>"
         return f"<div style='margin-bottom:6px'>{dot}<b>{color.capitalize()}</b>{pill}</div>"
-    # word modes
+    # lexicon modes
     key = "english" if mode.lower() == "english" else ("matrice1" if mode.lower()=="matrice1" else "matrice")
     words = COLOR_LEX.get(color.lower(), {}).get(key, [])[:max_words]
     pills = "".join(
@@ -270,23 +269,22 @@ def labels_for_mode(colors: List[str], mode: str) -> List[str]:
     return [c.capitalize() for c in colors]
 
 # ---------- dynamic prompt UI (2–8 inputs) ----------
-MAX_COLORS = 8  # upper bound for inputs we render
+MAX_COLORS = 8  # upper bound; raise if some pathways exceed this
 
 def update_prompt_ui(seq_choice: str, word_mode: str):
     key = SEQUENCE_ALIASES.get(seq_choice)
     colors = colors_for_sequence(key)
     labels = labels_for_mode(colors, word_mode)
 
-    # chips HTML for all colors
     chips = "".join(chip_html_for(c, word_mode) for c in colors) or "No prompts available for this pathway."
 
-    # build visibility/labels/placeholders for up to MAX_COLORS textboxes
+    # Return updates for chips + each color input (visibility, label, placeholder)
     inputs_updates = []
     for i in range(MAX_COLORS):
         if i < len(colors):
-            lab = f"{labels[i]} meaning" if labels[i] else f"Input {i+1} meaning"
-            ph  = f"Describe {labels[i]} meaning..." if labels[i] else "—"
-            inputs_updates.append(gr.update(visible=True, label=lab, placeholder=ph, value=""))
+            lab = labels[i] if i < len(labels) else f"Input {i+1}"
+            ph  = f"Describe {lab} meaning..." if lab else "—"
+            inputs_updates.append(gr.update(visible=True, label=f"{lab} meaning", placeholder=ph, value=""))
         else:
             inputs_updates.append(gr.update(visible=False, value="", label=f"Input {i+1}", placeholder="—"))
     return (chips, *inputs_updates)
@@ -295,14 +293,14 @@ def update_prompt_ui(seq_choice: str, word_mode: str):
 def analyze(text: str, seq_choice: str, word_mode: str, *color_inputs):
     """
     - user chooses pathway
-    - we show N color prompts (2–8)
-    - compose updated pathway phrase that embeds all non-empty inputs
+    - show N color prompts (2–8)
+    - compose updated pathway phrase embedding all inputs
     - analyze sentiment/emotion + GNH on (text + updated phrase)
     """
     key = SEQUENCE_ALIASES.get(seq_choice)
     if key not in SEQ_PHRASE:
         return (5.0, "neutral (0.0)", 5.0, "Please choose a valid pathway.", "{}", None, None,
-                f"{seq_choice} (unavailable)")
+                f"{seq_choice} (unavailable)", *update_prompt_ui(seq_choice, word_mode))
 
     sentiment = score_sentiment(text or "")
     emotion, emo_conf = classify_emotion(text or "")
@@ -311,7 +309,7 @@ def analyze(text: str, seq_choice: str, word_mode: str, *color_inputs):
     colors = colors_for_sequence(key)
     labels = labels_for_mode(colors, word_mode)
 
-    # updated phrase = base phrase + each "{Label}: {input}"
+    # Updated phrase = base phrase + each "{Label}: {input}"
     base_phrase = SEQ_PHRASE.get(key, "")
     pieces = [base_phrase]
     for lab, user_text in zip(labels, list(color_inputs)[:len(colors)]):
@@ -330,7 +328,7 @@ def analyze(text: str, seq_choice: str, word_mode: str, *color_inputs):
     meta = f"{key} | colors: {', '.join(cols) if cols else '—'}"
     img_path = sequence_to_image_path(key)
 
-    # refresh prompt area to keep labels/visibility consistent after run
+    # keep UI prompts in sync after run
     chips_and_inputs = update_prompt_ui(seq_choice, word_mode)
 
     return (
@@ -353,7 +351,7 @@ with gr.Blocks(title="RGB Root Matriz Color Plotter") as demo:
 
     with gr.Row():
         seq = gr.Dropdown(choices=SEQ_CHOICES, value=DEFAULT_SEQ, label="Pathway")
-        word_mode = gr.Radio(choices=["Matrice1", "Matrice", "English", "GNH Indicators"], value="Matrice1", label="Word Mode")
+        word_mode = gr.Radio(choices=WORD_MODES, value="Matrice1", label="Word Mode")
 
     chips_block = gr.HTML()  # chips for all colors
 
@@ -379,13 +377,7 @@ with gr.Blocks(title="RGB Root Matriz Color Plotter") as demo:
     img_out  = gr.Image(label="Pathway image", type="filepath")
     meta_out = gr.Text(label="Chosen pathway / colors")
 
-    # initialize prompt area for default selection
-    init_updates = update_prompt_ui(DEFAULT_SEQ, "Matrice1")
-    chips_block.value = init_updates[0]
-    for tb, up in zip(color_inputs, init_updates[1:1+MAX_COLORS]):
-        tb.update(**up)
-
-    # re-render prompts on changes
+    # events
     def _update_ui(seq_choice, mode):
         return update_prompt_ui(seq_choice, mode)
 
@@ -398,7 +390,12 @@ with gr.Blocks(title="RGB Root Matriz Color Plotter") as demo:
         outputs=[sent, emo, acc, phrase_out, gnh_top, gnh_plot, img_out, meta_out, chips_block, *color_inputs],
     )
 
+    # ✅ initialize prompts on load (instead of tb.update(...))
+    demo.load(
+        fn=_update_ui,
+        inputs=[seq, word_mode],
+        outputs=[chips_block, *color_inputs]
+    )
+
 if __name__ == "__main__":
     demo.launch()
-
-