Update app.py

app.py

@@ -1,5 +1,5 @@
 """
-app.py — Video Verifier & Sentiment Analyzer  (Gradio 6.x)
+app.py — Misinformation Detection & Public Engagement   (Gradio 6.x)
 
 """
 
@@ -341,17 +341,17 @@ def run_pipeline(
 
     #  Guards
     if not (url_or_id or "").strip():
-        yield _blank_outputs("⚠️ Please enter a YouTube URL or video ID.")
+        yield _blank_outputs(" Please enter a YouTube URL or video ID.")
         return
 
     video_id = extract_video_id(url_or_id.strip())
     if not video_id:
-        yield _blank_outputs("❌ Could not parse a valid YouTube video ID.")
+        yield _blank_outputs(" Could not parse a valid YouTube video ID.")
         return
 
     if not api_key:
         yield _blank_outputs(
-            "⚠️ YouTube API key not found. "
+            " YouTube API key not found. "
             "Set the <code>YT_API_KEY</code> environment variable / Space secret."
         )
         return
@@ -360,7 +360,7 @@ def run_pipeline(
     progress(0.05, desc="Fetching video metadata…")
     meta, err = fetch_video_metadata(video_id, api_key)
     if err:
-        yield _blank_outputs(f"❌ {err}")
+        yield _blank_outputs(f" {err}")
         return
 
     # 2 — Transcript
@@ -372,16 +372,7 @@ def run_pipeline(
     comments_df, c_status = fetch_comments(video_id, api_key, max_comments=int(max_comments))
 
     # 4 — Misinformation
-    # BUG FIX: previously both audio_transcript and video_transcript were set
-    # to the same `transcript` variable.  When the transcript was empty (no
-    # captions), ALL three modalities hit the empty-string fallback inside
-    # _compute_modality_analysis and returned a fixed 50/50 split with
-    # logit_m = logit_c = 0, trust = 0 %, uncertainty = 100 % — values that
-    # never changed across videos.
-    # The fix keeps audio_transcript = spoken transcript (speech stream) and
-    # video_transcript = spoken transcript too, but detect_misinformation()
-    # now internally builds the video segment as transcript + title + tags,
-    # giving all three modalities distinct content and therefore distinct scores.
+
     progress(0.50, desc="Running misinformation detection…")
     misinfo = detect_misinformation(
         text=f"{meta['title']} {meta['description']}",
@@ -419,7 +410,7 @@ def run_pipeline(
         sentiments=sentiments, sent_sum=sent_sum,
         pos_kw=pos_kw, neg_kw=neg_kw,
         status_log=[
-            f"✅ Metadata: {meta['title'][:55]}",
+            f" Metadata: {meta['title'][:55]}",
             t_status,
             c_status,
             f"🔬 Misinfo score: {misinfo['confidence_pct']}%",
@@ -442,7 +433,7 @@ def _build_outputs(
     #  Status
     status_html = (
         '<p style="color:#00e5a0;font-family:DM Mono,monospace;font-size:0.82rem;padding:6px 0">'
-        "✅ Analysis complete</p>"
+        " Analysis complete</p>"
     )
 
     #  Log
@@ -498,9 +489,9 @@ def _build_outputs(
     #  Misinfo badge
     score = misinfo["score"]
     if score < 0.35:
-        badge_html = '<span class="vv-badge-green">✅ Appears Credible</span>'
+        badge_html = '<span class="vv-badge-green"> Appears Credible</span>'
     elif score < 0.65:
-        badge_html = '<span class="vv-badge-amber">⚠️ Uncertain / Mixed Signals</span>'
+        badge_html = '<span class="vv-badge-amber"> Uncertain / Mixed Signals</span>'
     else:
         badge_html = '<span class="vv-badge-red">🚨 Likely Misinformation</span>'
 
@@ -560,12 +551,12 @@ def _build_outputs(
         stat_pos = (
             f'<div class="vv-card" style="text-align:center">'
             f'<p class="vv-stat-big-green">{sent_sum["pos_pct"]}%</p>'
-            f'<p style="color:#5a6070;font-size:0.75rem;margin:4px 0 0">Positive</p></div>'
+            f'<p style="color:#5a6070;font-size:0.75rem;margin:4px 0 0">Positively Engagement</p></div>'
         )
         stat_neg = (
             f'<div class="vv-card" style="text-align:center">'
             f'<p class="vv-stat-big-red">{sent_sum["neg_pct"]}%</p>'
-            f'<p style="color:#5a6070;font-size:0.75rem;margin:4px 0 0">Negative</p></div>'
+            f'<p style="color:#5a6070;font-size:0.75rem;margin:4px 0 0">Negatively Engagement</p></div>'
         )
         stat_neu = (
             f'<div class="vv-card" style="text-align:center">'
@@ -599,8 +590,8 @@ def _build_outputs(
             .reset_index(drop=True)
         )
         if "sentiment" in display_df.columns:
-            df_pos = display_df[display_df["sentiment"] == "POSITIVE"][cols].head(50).reset_index(drop=True)
-            df_neg = display_df[display_df["sentiment"] == "NEGATIVE"][cols].head(50).reset_index(drop=True)
+            df_pos = display_df[display_df["sentiment"] == "Positively Engagement"][cols].head(50).reset_index(drop=True)
+            df_neg = display_df[display_df["sentiment"] == "Negatively Engagement"][cols].head(50).reset_index(drop=True)
 
     return (
         status_html,    # 0   status_box
@@ -632,7 +623,7 @@ def do_search(keyword: str):
     api_key = os.environ.get("YT_API_KEY", "").strip()
     if not api_key:
         return (
-            "<p style='color:#ff4757;font-family:DM Mono,monospace'>⚠️ YT_API_KEY secret not set.</p>",
+            "<p style='color:#ff4757;font-family:DM Mono,monospace'> YT_API_KEY secret not set.</p>",
             gr.update(choices=[], value=None, visible=False),
         )
     if not (keyword or "").strip():
@@ -678,14 +669,14 @@ def pick_and_analyze(selected_url, sentiment_method, max_comments):
 #  GRADIO BLOCKS UI
 
 
-with gr.Blocks(title="VideoVerifier — MHMisinfo") as demo:
+with gr.Blocks(title="Misinformation Detection & Public Engagement ") as demo:
 
     #  Header
     gr.HTML("""
     <div style="padding:1.5rem 0 0.8rem;border-bottom:1px solid #1e2330;margin-bottom:1.2rem">
-      <h1 class="vv-hero">🔬 Video Verifier & Sentiment Analyzer</h1>
+      <h1 class="vv-hero">🔬 Misinformation Detection & Public Engagement </h1>
       <p style="color:#5a6070;font-size:0.85rem;margin-top:4px;font-family:'DM Mono',monospace">
-        mental health misinformation detection
+        Misinformation detection
       </p>
     </div>
     """)
@@ -809,9 +800,9 @@ with gr.Blocks(title="VideoVerifier — MHMisinfo") as demo:
                         wrap=True,
                         max_height=320,
                     )
-                with gr.TabItem("Positive"):
+                with gr.TabItem("Positively Engagement"):
                     df_pos_out = gr.Dataframe(wrap=True, max_height=320)
-                with gr.TabItem("Negative"):
+                with gr.TabItem("Negatively Engagement"):
                     df_neg_out = gr.Dataframe(wrap=True, max_height=320)
                 with gr.TabItem("Most Liked"):
                     df_top_out = gr.Dataframe(wrap=True, max_height=320)