Update app.py

app.py

@@ -44,7 +44,6 @@ LANGUAGES = {
 
 last_result = {}
 chat_context = {}
-# Store last AI reply text for replay button
 last_ai_reply = {"text": "", "lang": "en"}
 
 try:
@@ -156,9 +155,7 @@ def generate_pdf(original_image, annotated_image, seen, alert, explanation):
     story += [model_table, Spacer(1,0.4*cm),
               HRFlowable(width="100%", thickness=1, color=colors.HexColor('#1a3a5c')),
               Spacer(1,0.2*cm),
-              Paragraph("DISCLAIMER: This report is generated by an AI research prototype for educational purposes only. "
-                "It is NOT a medical device and must not be used for clinical decision-making. "
-                "All demo footage is from the publicly available CholecSeg8k research dataset — no real patient data involved.", footer_style),
+              Paragraph("DISCLAIMER: Research prototype only. Not a medical device. No real patient data.", footer_style),
               Paragraph("Built for Build Small Hackathon 2026", footer_style)]
     doc.build(story)
     return pdf_path
@@ -195,7 +192,7 @@ def segment_image(input_image, conf_threshold=0.25):
         try:
             prompt = (f"You are a surgical anatomy teacher for a junior resident. "
                 f"Detected in a laparoscopic cholecystectomy frame: {', '.join(tissue_list)}. "
-                f"In 3 sentences, explain what the resident should know — what they are, why they matter, what to watch out for.")
+                f"In 3 sentences, explain what the resident should know.")
             response = client.chat_completion([{"role":"user","content":prompt}], max_tokens=180, temperature=0.4)
             explanation = response.choices[0].message.content.strip()
         except Exception as e:
@@ -220,7 +217,8 @@ def segment_image(input_image, conf_threshold=0.25):
 
 def chat_response(message, history, language):
     global chat_context, last_ai_reply
-    if not message.strip(): return history, "", gr.update(visible=False), gr.update(visible=False)
+    if not message.strip():
+        return history, "", gr.update(visible=False), gr.update(visible=False)
     tissue_list = chat_context.get("tissue_list", [])
     alert       = chat_context.get("alert", "")
     lang_cfg    = LANGUAGES.get(language, LANGUAGES["English"])
@@ -230,23 +228,25 @@ def chat_response(message, history, language):
         + "Answer concisely in 2-4 sentences. "
         + lang_cfg["prompt"])
     messages = [{"role": "system", "content": system_prompt}]
-    for msg in history: messages.append({"role": msg["role"], "content": msg["content"]})
+    for msg in history:
+        messages.append({"role": msg["role"], "content": msg["content"]})
     messages.append({"role": "user", "content": message})
     try:
         response = client.chat_completion(messages, max_tokens=200, temperature=0.5)
         reply = response.choices[0].message.content.strip()
     except Exception as e:
         reply = f"Error: {str(e)}"
-    new_history = history + [{"role": "user", "content": message}, {"role": "assistant", "content": reply}]
+    new_history = history + [
+        {"role": "user", "content": message},
+        {"role": "assistant", "content": reply}
+    ]
     last_ai_reply = {"text": reply, "lang": lang_cfg["code"]}
-    # Auto-generate TTS and show audio player
     audio_path = text_to_speech(reply, lang_cfg["code"])
     audio_update = gr.update(value=audio_path, visible=True) if audio_path else gr.update(visible=False)
     return new_history, "", audio_update, gr.update(visible=True)
 
 
 def replay_last(language):
-    """Replay button — re-generates TTS for last AI reply."""
     global last_ai_reply
     lang_cfg = LANGUAGES.get(language, LANGUAGES["English"])
     text = last_ai_reply.get("text", "")
@@ -254,14 +254,13 @@ def replay_last(language):
     return gr.update(value=audio_path, visible=True) if audio_path else gr.update(visible=False)
 
 
-def use_suggested(q, h, lang): return chat_response(q, h, lang)
-
 def export_pdf():
     if not last_result: return None
     return generate_pdf(last_result["original"], last_result["annotated"],
                         last_result["seen"], last_result["alert"], last_result["explanation"])
 
 
+# CSS passed to launch() in Gradio 6
 css = """
 .gradio-container { max-width: 1120px !important; margin: 0 auto !important; }
 .generating, .progress-text, .progress-bar-wrap, .eta-bar, .eta-text { display: none !important; }
@@ -271,47 +270,57 @@ css = """
   flex-direction:column; align-items:center; justify-content:center;
 }
 #surgi-overlay.active { display:flex !important; }
-.or-spinner { width:48px;height:48px;border:4px solid rgba(255,255,255,0.2);border-top-color:#fff;border-radius:50%;animation:spin 0.8s linear infinite;margin-bottom:16px; }
-@keyframes spin{to{transform:rotate(360deg)}}
-.or-text { color:#fff;font-size:1rem;font-weight:600;text-align:center; }
-.or-sub  { color:rgba(255,255,255,0.6);font-size:0.82rem;margin-top:6px; }
+.or-spinner {
+  width:48px; height:48px;
+  border:4px solid rgba(255,255,255,0.2);
+  border-top-color:#fff; border-radius:50%;
+  animation:spin 0.8s linear infinite; margin-bottom:16px;
+}
+@keyframes spin { to { transform:rotate(360deg) } }
+.or-text { color:#fff; font-size:1rem; font-weight:600; text-align:center; }
+.or-sub  { color:rgba(255,255,255,0.6); font-size:0.82rem; margin-top:6px; }
 """
 
-overlay_html = """
-<div id="surgi-overlay">
-  <div class="or-spinner"></div>
-  <div class="or-text">Analysing Surgical Frame…</div>
-  <div class="or-sub">YOLOv26n-seg · Modal GPU · Llama 3.1</div>
-</div>
-<script>
-(function(){
-  var attached=false;
-  function attachBtn(){
-    var btn=document.querySelector('#run-btn button');
-    if(btn&&!attached){
-      btn.addEventListener('click',function(){ document.getElementById('surgi-overlay').classList.add('active'); });
-      attached=true;
-    } else if(!btn){ setTimeout(attachBtn,500); }
+# JS runs once on page load — safe place for scripts in Gradio 6
+overlay_js = """
+() => {
+  // Inject overlay HTML
+  const div = document.createElement('div');
+  div.id = 'surgi-overlay';
+  div.innerHTML = `
+    <div class="or-spinner"></div>
+    <div class="or-text">Analysing Surgical Frame…</div>
+    <div class="or-sub">YOLOv8 · Modal GPU · Llama 3.1</div>
+  `;
+  document.body.appendChild(div);
+
+  // Attach click listener to run button
+  function attachBtn() {
+    const btn = document.querySelector('#run-btn button');
+    if (btn) {
+      btn.addEventListener('click', () => div.classList.add('active'));
+    } else {
+      setTimeout(attachBtn, 500);
+    }
   }
-  var obs=new MutationObserver(function(){
-    var img=document.querySelector('#output-frame img');
-    if(img&&img.src&&img.src.length>80){ document.getElementById('surgi-overlay').classList.remove('active'); }
-  });
-  obs.observe(document.body,{childList:true,subtree:true,attributes:true,attributeFilter:['src']});
-  setTimeout(function(){ document.getElementById('surgi-overlay').classList.remove('active'); },90000);
-  if(document.readyState==='loading'){ document.addEventListener('DOMContentLoaded',function(){setTimeout(attachBtn,900);}); }
-  else { setTimeout(attachBtn,900); }
-})();
-</script>
-"""
+  attachBtn();
 
-with gr.Blocks(title="SurgiSight — Surgical AI", css=css) as demo:
+  // Hide overlay when output image appears
+  new MutationObserver(() => {
+    const img = document.querySelector('#output-frame img');
+    if (img && img.src && img.src.length > 80) div.classList.remove('active');
+  }).observe(document.body, {childList:true, subtree:true, attributes:true, attributeFilter:['src']});
+
+  // Safety timeout
+  setTimeout(() => div.classList.remove('active'), 90000);
+}
+"""
 
-    gr.HTML(overlay_html)
+with gr.Blocks(title="SurgiSight — Surgical AI", js=overlay_js) as demo:
 
     gr.Markdown("""
 # SurgiSight — Surgical Tissue Segmentation
-**AI-powered anatomy detection for laparoscopic training** · YOLOv8n-seg · Llama 3.1 8B · Modal GPU · CholecSeg8k (MICCAI 2020) · mAP50: 0.581
+**AI-powered anatomy detection for laparoscopic training** · YOLOv26n-seg · Llama 3.1 8B · Modal GPU · CholecSeg8k (MICCAI 2020) · mAP50: 0.581
 
 > Research prototype — No real patient data.
 """)
@@ -337,7 +346,6 @@ with gr.Blocks(title="SurgiSight — Surgical AI", css=css) as demo:
         pdf_btn = gr.Button("⬇  Export Full Report (PDF)", visible=False)
     pdf_output = gr.File(label="Download Report", visible=False)
 
-    # ── Chat section ──────────────────────────────────────────────────────────
     with gr.Column(visible=False) as chat_section:
         gr.Markdown("---\n### 💬 AI Anatomy Consult")
 
@@ -354,14 +362,12 @@ with gr.Blocks(title="SurgiSight — Surgical AI", css=css) as demo:
 
         chatbot = gr.Chatbot(height=340, show_label=False)
 
-        # Audio player — appears after each AI reply, autoplay on
+        # Audio player — autoplay, appears after each reply
         audio_out = gr.Audio(
             label="🔊 AI Voice Reply",
             visible=False,
             autoplay=True,
-            format="mp3",
-            show_download_button=False,
-            waveform_options={"show_controls": True}
+            format="mp3"
         )
 
         with gr.Row():
@@ -376,7 +382,7 @@ with gr.Blocks(title="SurgiSight — Surgical AI", css=css) as demo:
 
     gr.Markdown("---\n*CholecSeg8k · MICCAI 2020 · No patient data · Built for Build Small Hackathon 2026*")
 
-    # ── Wiring ────────────────────────────────────────────────────────────────
+    # Wiring
     run_btn.click(fn=segment_image, inputs=[input_img, conf_slider],
         outputs=[output_img, output_text, danger_box, explain_box,
                  pdf_btn, chat_section, sq1, sq2, sq3, chatbot])
@@ -393,9 +399,9 @@ with gr.Blocks(title="SurgiSight — Surgical AI", css=css) as demo:
 
     replay_btn.click(fn=replay_last, inputs=[lang_select], outputs=[audio_out])
 
-    sq1.click(fn=use_suggested, inputs=[sq1, chatbot, lang_select], outputs=[chatbot, chat_input, audio_out, replay_btn])
-    sq2.click(fn=use_suggested, inputs=[sq2, chatbot, lang_select], outputs=[chatbot, chat_input, audio_out, replay_btn])
-    sq3.click(fn=use_suggested, inputs=[sq3, chatbot, lang_select], outputs=[chatbot, chat_input, audio_out, replay_btn])
+    sq1.click(fn=chat_response, inputs=[sq1, chatbot, lang_select], outputs=[chatbot, chat_input, audio_out, replay_btn])
+    sq2.click(fn=chat_response, inputs=[sq2, chatbot, lang_select], outputs=[chatbot, chat_input, audio_out, replay_btn])
+    sq3.click(fn=chat_response, inputs=[sq3, chatbot, lang_select], outputs=[chatbot, chat_input, audio_out, replay_btn])
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(css=css)