Update app.py

app.py

@@ -15,6 +15,11 @@ from reportlab.lib.units import cm
 from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Image as RLImage, Table, TableStyle, HRFlowable
 from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
 from reportlab.lib.enums import TA_CENTER
+from docx import Document
+from docx.shared import Inches, Pt, RGBColor
+from docx.enum.text import WD_ALIGN_PARAGRAPH
+from docx.oxml.ns import qn
+from docx.oxml import OxmlElement
 
 print("All imports OK")
 
@@ -33,7 +38,6 @@ CLASS_NAMES = [
 ]
 DANGER_CLASSES = ["Hepatic Vein","Cystic Duct","Blood"]
 
-# Only languages with reliable gTTS support
 LANGUAGES = {
     "English": {"code": "en", "prompt": "Respond in English."},
     "French":  {"code": "fr", "prompt": "Réponds en français."},
@@ -41,8 +45,6 @@ LANGUAGES = {
 
 last_result = {}
 chat_context = {}
-
-# Each entry: {"role": "user"/"assistant", "en": "original english text", "display": "current display text"}
 _chat_history = []
 
 try:
@@ -71,12 +73,10 @@ def tts_to_b64(text, lang_code):
         print(f"TTS error: {e}"); return ""
 
 def translate_to(text, lang_cfg):
-    """Translate text to target language via Llama. Returns translated string."""
-    if lang_cfg["code"] == "en" or not client:
-        return text
+    if lang_cfg["code"] == "en" or not client: return text
     try:
-        prompt = (f"Translate the following medical text to {list(LANGUAGES.keys())[[v['code'] for v in LANGUAGES.values()].index(lang_cfg['code'])]}. "
-                  f"Output ONLY the translation, nothing else.\n\n{text}")
+        lang_name = [k for k,v in LANGUAGES.items() if v["code"]==lang_cfg["code"]][0]
+        prompt = f"Translate the following medical text to {lang_name}. Output ONLY the translation, nothing else.\n\n{text}"
         resp = client.chat_completion([{"role":"user","content":prompt}], max_tokens=300, temperature=0.1)
         return resp.choices[0].message.content.strip()
     except:
@@ -96,19 +96,15 @@ def generate_suggested_questions(tissue_list):
     return questions[:3]
 
 def render_chat_html(history, lang_code):
-    """Render Perplexity-style chat with 🔊 per AI message. Audio embedded as base64."""
     if not history:
         return '<p style="color:#888;text-align:center;padding:32px 0;font-size:0.9rem;">Run analysis first, then ask questions here.</p>'
-
     items = []
     for i, msg in enumerate(history):
         role = msg["role"]
         text = msg["display"]
-        # Markdown bold
         text_html = re.sub(r'\*\*(.+?)\*\*', r'<strong>\1</strong>', text)
         text_html = text_html.replace("\n\n", "</p><p style='margin:6px 0;'>").replace("\n", "<br>")
         text_html = f"<p style='margin:0;'>{text_html}</p>"
-
         if role == "user":
             items.append(f"""
             <div style="display:flex;justify-content:flex-end;margin:14px 0 2px;">
@@ -136,7 +132,6 @@ def render_chat_html(history, lang_code):
                     f'border-radius:6px;color:#6b7280;flex-shrink:0;margin-top:1px;transition:color 0.15s;" '
                     f'onmouseover="this.style.color=\'#2563eb\'" onmouseout="this.style.color=\'#6b7280\'">🔊</button>'
                 )
-
             items.append(f"""
             <div style="display:flex;justify-content:flex-start;margin:14px 0 2px;">
               <div style="max-width:82%;">
@@ -144,74 +139,66 @@ def render_chat_html(history, lang_code):
                   SurgiSight AI
                 </div>
                 <div style="display:flex;align-items:flex-start;gap:10px;">
-                  <div style="font-size:0.9rem;line-height:1.7;flex:1;">
-                    {text_html}
-                  </div>
+                  <div style="font-size:0.9rem;line-height:1.7;flex:1;">{text_html}</div>
                   {spk_btn}
                 </div>
                 {audio_html}
               </div>
             </div>""")
-
     scroll_js = "<script>setTimeout(function(){var e=document.getElementById('ce');if(e)e.scrollIntoView({behavior:'smooth'});},80);</script>"
     return f"""
     <div id="chat-scroll" style="height:440px;overflow-y:auto;padding:8px 12px;border-radius:8px;border:1px solid var(--border-color-primary,#333);">
       {''.join(items)}
       <div id="ce"></div>
     </div>
-    {scroll_js}
-    """
+    {scroll_js}"""
 
 def retranslate_history(language):
-    """Retranslate all assistant messages to new language, rebuild display."""
     global _chat_history
     if not _chat_history:
-        return render_chat_html([], LANGUAGES.get(language,LANGUAGES["English"])["code"])
+        return render_chat_html([], LANGUAGES.get(language, LANGUAGES["English"])["code"])
     lang_cfg = LANGUAGES.get(language, LANGUAGES["English"])
     for msg in _chat_history:
         if msg["role"] == "assistant":
-            if lang_cfg["code"] == "en":
-                msg["display"] = msg["en"]   # restore original
-            else:
-                msg["display"] = translate_to(msg["en"], lang_cfg)
+            msg["display"] = msg["en"] if lang_cfg["code"] == "en" else translate_to(msg["en"], lang_cfg)
     return render_chat_html(_chat_history, lang_cfg["code"])
 
 
+# ── PDF ───────────────────────────────────────────────────────────────────────
 def generate_pdf(original_image, annotated_image, seen, alert, explanation):
     pdf_path = "/tmp/surgisight_report.pdf"
     doc = SimpleDocTemplate(pdf_path, pagesize=A4,
         rightMargin=2*cm, leftMargin=2*cm, topMargin=2*cm, bottomMargin=2*cm)
     styles = getSampleStyleSheet()
-    title_style   = ParagraphStyle('Title2',   parent=styles['Title'],  fontSize=22, textColor=colors.HexColor('#1a3a5c'), spaceAfter=4, fontName='Helvetica-Bold', alignment=TA_CENTER)
-    subtitle_style= ParagraphStyle('Sub2',     parent=styles['Normal'], fontSize=10, textColor=colors.HexColor('#888888'), spaceAfter=2, alignment=TA_CENTER)
-    section_style = ParagraphStyle('Sec2',     parent=styles['Normal'], fontSize=13, textColor=colors.HexColor('#1a3a5c'), spaceAfter=6, spaceBefore=12, fontName='Helvetica-Bold')
-    body_style    = ParagraphStyle('Body2',    parent=styles['Normal'], fontSize=10, textColor=colors.HexColor('#1a1a1a'), spaceAfter=4, leading=16)
-    danger_style  = ParagraphStyle('Danger2',  parent=styles['Normal'], fontSize=10, textColor=colors.HexColor('#cc0000'), spaceAfter=4, leading=16, fontName='Helvetica-Bold', backColor=colors.HexColor('#fff0f0'), borderPadding=(6,8,6,8))
-    safe_style    = ParagraphStyle('Safe2',    parent=styles['Normal'], fontSize=10, textColor=colors.HexColor('#1a7a40'), spaceAfter=4, leading=16, fontName='Helvetica-Bold', backColor=colors.HexColor('#f0fff4'), borderPadding=(6,8,6,8))
-    caption_style = ParagraphStyle('Cap2',     parent=styles['Normal'], fontSize=8,  textColor=colors.HexColor('#888888'), alignment=TA_CENTER, spaceAfter=4)
-    footer_style  = ParagraphStyle('Foot2',    parent=styles['Normal'], fontSize=8,  textColor=colors.HexColor('#aaaaaa'), alignment=TA_CENTER)
+    title_s  = ParagraphStyle('T2', parent=styles['Title'],  fontSize=22, textColor=colors.HexColor('#1a3a5c'), spaceAfter=4, fontName='Helvetica-Bold', alignment=TA_CENTER)
+    sub_s    = ParagraphStyle('S2', parent=styles['Normal'], fontSize=10, textColor=colors.HexColor('#888'), spaceAfter=2, alignment=TA_CENTER)
+    sec_s    = ParagraphStyle('Se2',parent=styles['Normal'], fontSize=13, textColor=colors.HexColor('#1a3a5c'), spaceAfter=6, spaceBefore=12, fontName='Helvetica-Bold')
+    body_s   = ParagraphStyle('B2', parent=styles['Normal'], fontSize=10, textColor=colors.HexColor('#1a1a1a'), spaceAfter=4, leading=16)
+    danger_s = ParagraphStyle('D2', parent=styles['Normal'], fontSize=10, textColor=colors.HexColor('#cc0000'), spaceAfter=4, leading=16, fontName='Helvetica-Bold', backColor=colors.HexColor('#fff0f0'), borderPadding=(6,8,6,8))
+    safe_s   = ParagraphStyle('Sa2',parent=styles['Normal'], fontSize=10, textColor=colors.HexColor('#1a7a40'), spaceAfter=4, leading=16, fontName='Helvetica-Bold', backColor=colors.HexColor('#f0fff4'), borderPadding=(6,8,6,8))
+    cap_s    = ParagraphStyle('C2', parent=styles['Normal'], fontSize=8,  textColor=colors.HexColor('#888'), alignment=TA_CENTER, spaceAfter=4)
+    foot_s   = ParagraphStyle('F2', parent=styles['Normal'], fontSize=8,  textColor=colors.HexColor('#aaa'), alignment=TA_CENTER)
     story = []
-    timestamp = datetime.datetime.now().strftime("%B %d, %Y at %H:%M")
-    story += [Spacer(1,.3*cm), Paragraph("SurgiSight",title_style),
-              Paragraph("Surgical Anatomy Analysis Report",subtitle_style),
-              Paragraph(f"Generated on {timestamp}",subtitle_style),
+    ts = datetime.datetime.now().strftime("%B %d, %Y at %H:%M")
+    story += [Spacer(1,.3*cm), Paragraph("SurgiSight",title_s),
+              Paragraph("Surgical Anatomy Analysis Report",sub_s),
+              Paragraph(f"Generated on {ts}",sub_s),
               Spacer(1,.2*cm), HRFlowable(width="100%",thickness=2,color=colors.HexColor('#1a3a5c')),
-              Spacer(1,.4*cm), Paragraph("Segmentation Output",section_style)]
-    iw,ih = 8.5*cm, 6.5*cm
+              Spacer(1,.4*cm), Paragraph("Segmentation Output",sec_s)]
+    iw,ih = 8.5*cm,6.5*cm
     ob=io.BytesIO(); original_image.save(ob,format="PNG"); ob.seek(0)
     ab=io.BytesIO(); annotated_image.save(ab,format="PNG"); ab.seek(0)
     it=Table([[RLImage(ob,width=iw,height=ih),RLImage(ab,width=iw,height=ih)],
-              [Paragraph("Original Frame",caption_style),Paragraph("AI Segmented Output",caption_style)]],
+              [Paragraph("Original Frame",cap_s),Paragraph("AI Segmented Output",cap_s)]],
              colWidths=[iw+.5*cm,iw+.5*cm])
     it.setStyle(TableStyle([('ALIGN',(0,0),(-1,-1),'CENTER'),('VALIGN',(0,0),(-1,-1),'MIDDLE'),
         ('BACKGROUND',(0,0),(-1,0),colors.HexColor('#f5f5f5')),
         ('BOX',(0,0),(0,0),.5,colors.HexColor('#ddd')),('BOX',(1,0),(1,0),.5,colors.HexColor('#ddd'))]))
-    story+=[it,Spacer(1,.5*cm),Paragraph("Safety Assessment",section_style)]
-    if any(d in alert for d in DANGER_CLASSES): story.append(Paragraph(f"WARNING: {alert}",danger_style))
-    else: story.append(Paragraph(f"SAFE: {alert}",safe_style))
-    story+=[Spacer(1,.4*cm),Paragraph("Detected Tissues & Instruments",section_style)]
-    td=[["Structure","Confidence","Risk Level"]]
-    rd=[]
+    story+=[it,Spacer(1,.5*cm),Paragraph("Safety Assessment",sec_s)]
+    if any(d in alert for d in DANGER_CLASSES): story.append(Paragraph(f"WARNING: {alert}",danger_s))
+    else: story.append(Paragraph(f"SAFE: {alert}",safe_s))
+    story+=[Spacer(1,.4*cm),Paragraph("Detected Tissues & Instruments",sec_s)]
+    td=[["Structure","Confidence","Risk Level"]]; rd=[]
     for name,conf in sorted(seen.items(),key=lambda x:-x[1]):
         if name=="Black Background": continue
         bar="\u2588"*int(conf*10)+"\u2591"*(10-int(conf*10))
@@ -230,8 +217,8 @@ def generate_pdf(original_image, annotated_image, seen, alert, explanation):
         if isd: ds.append(('FONTNAME',(2,r),(2,r),'Helvetica-Bold'))
     dt.setStyle(TableStyle(ds))
     story+=[dt,Spacer(1,.5*cm),HRFlowable(width="100%",thickness=.5,color=colors.HexColor('#ccc')),
-            Spacer(1,.3*cm),Paragraph("Anatomy Teaching Note",section_style),
-            Paragraph(explanation,body_style),Spacer(1,.5*cm),
+            Spacer(1,.3*cm),Paragraph("Anatomy Teaching Note",sec_s),
+            Paragraph(explanation,body_s),Spacer(1,.5*cm),
             HRFlowable(width="100%",thickness=.5,color=colors.HexColor('#ccc')),Spacer(1,.3*cm)]
     md=[["Detection Model","YOLOv8-seg fine-tuned on CholecSeg8k (MICCAI 2020)"],
         ["LLM","Meta Llama 3.1 8B Instruct"],["Inference","Modal GPU (T4)"],
@@ -243,18 +230,115 @@ def generate_pdf(original_image, annotated_image, seen, alert, explanation):
         ('ROWBACKGROUNDS',(0,0),(-1,-1),[colors.HexColor('#f5f5f5'),colors.white])]))
     story+=[mt,Spacer(1,.4*cm),HRFlowable(width="100%",thickness=1,color=colors.HexColor('#1a3a5c')),
             Spacer(1,.2*cm),
-            Paragraph("DISCLAIMER: Research prototype only. Not a medical device. No real patient data.",footer_style),
-            Paragraph("Built for Build Small Hackathon 2026",footer_style)]
+            Paragraph("DISCLAIMER: Research prototype only. Not a medical device. No real patient data.",foot_s),
+            Paragraph("Built for Build Small Hackathon 2026",foot_s)]
     doc.build(story)
     return pdf_path
 
 
+# ── Word ──────────────────────────────────────────────────────────────────────
+def generate_word(original_image, annotated_image, seen, alert, explanation):
+    docx_path = "/tmp/surgisight_report.docx"
+    doc = Document()
+    for section in doc.sections:
+        section.top_margin = Inches(1); section.bottom_margin = Inches(1)
+        section.left_margin = Inches(1.1); section.right_margin = Inches(1.1)
+
+    t = doc.add_heading("SurgiSight", 0)
+    t.alignment = WD_ALIGN_PARAGRAPH.CENTER
+    for run in t.runs:
+        run.font.color.rgb = RGBColor(0x1a,0x3a,0x5c)
+
+    sub = doc.add_paragraph("Surgical Anatomy Analysis Report")
+    sub.alignment = WD_ALIGN_PARAGRAPH.CENTER
+    sub.runs[0].font.size = Pt(11)
+    sub.runs[0].font.color.rgb = RGBColor(0x88,0x88,0x88)
+
+    ts = doc.add_paragraph(datetime.datetime.now().strftime("Generated on %B %d, %Y at %H:%M"))
+    ts.alignment = WD_ALIGN_PARAGRAPH.CENTER
+    ts.runs[0].font.size = Pt(9)
+    ts.runs[0].font.color.rgb = RGBColor(0x88,0x88,0x88)
+    doc.add_paragraph()
+
+    doc.add_heading("Segmentation Output", 2)
+    img_tbl = doc.add_table(rows=2, cols=2)
+    img_tbl.style = "Table Grid"
+    for col_idx, (pil_img, caption) in enumerate([(original_image,"Original Frame"),(annotated_image,"AI Segmented Output")]):
+        buf = io.BytesIO(); pil_img.save(buf,format="PNG"); buf.seek(0)
+        cell = img_tbl.cell(0,col_idx)
+        cell.paragraphs[0].alignment = WD_ALIGN_PARAGRAPH.CENTER
+        cell.paragraphs[0].add_run().add_picture(buf, width=Inches(2.9))
+        cap_cell = img_tbl.cell(1,col_idx)
+        cap_cell.paragraphs[0].alignment = WD_ALIGN_PARAGRAPH.CENTER
+        cr = cap_cell.paragraphs[0].add_run(caption)
+        cr.font.size = Pt(9); cr.font.color.rgb = RGBColor(0x88,0x88,0x88)
+    doc.add_paragraph()
+
+    doc.add_heading("Safety Assessment", 2)
+    is_danger = any(d in alert for d in DANGER_CLASSES)
+    p = doc.add_paragraph()
+    run = p.add_run(("⚠ WARNING: " if is_danger else "✓ SAFE: ") + alert)
+    run.bold = True
+    run.font.size = Pt(11)
+    run.font.color.rgb = RGBColor(0xcc,0,0) if is_danger else RGBColor(0x1a,0x7a,0x40)
+    doc.add_paragraph()
+
+    doc.add_heading("Detected Tissues & Instruments", 2)
+    rows = [(n,c) for n,c in sorted(seen.items(),key=lambda x:-x[1]) if n!="Black Background"]
+    if rows:
+        tbl = doc.add_table(rows=1+len(rows), cols=3)
+        tbl.style = "Table Grid"
+        hdr = tbl.rows[0].cells
+        for i,h in enumerate(["Structure","Confidence","Risk Level"]):
+            hdr[i].text = h
+            hdr[i].paragraphs[0].runs[0].bold = True
+            hdr[i].paragraphs[0].runs[0].font.size = Pt(10)
+            hdr[i].paragraphs[0].runs[0].font.color.rgb = RGBColor(0xff,0xff,0xff)
+            tc = hdr[i]._tc; tcPr = tc.get_or_add_tcPr()
+            shd = OxmlElement('w:shd')
+            shd.set(qn('w:val'),'clear'); shd.set(qn('w:color'),'auto'); shd.set(qn('w:fill'),'1a3a5c')
+            tcPr.append(shd)
+        for r_idx,(name,conf) in enumerate(rows):
+            row = tbl.rows[r_idx+1].cells
+            row[0].text = name
+            row[1].text = f"{conf:.1%}"
+            is_d = name in DANGER_CLASSES
+            rr = row[2].paragraphs[0].add_run("DANGER" if is_d else "Safe")
+            rr.bold = is_d
+            rr.font.size = Pt(9)
+            rr.font.color.rgb = RGBColor(0xcc,0,0) if is_d else RGBColor(0x1a,0x7a,0x40)
+            for c in [row[0],row[1]]:
+                if c.paragraphs[0].runs:
+                    c.paragraphs[0].runs[0].font.size = Pt(9)
+    doc.add_paragraph()
+
+    doc.add_heading("Anatomy Teaching Note", 2)
+    doc.add_paragraph(explanation)
+    doc.add_paragraph()
+
+    doc.add_heading("Model Information", 2)
+    for label,value in [("Detection Model","YOLOv8-seg fine-tuned on CholecSeg8k (MICCAI 2020)"),
+                        ("LLM","Meta Llama 3.1 8B Instruct"),("Inference","Modal GPU (T4)"),
+                        ("Dataset","CholecSeg8k — 8,080 frames, 13 classes"),("mAP50","0.581")]:
+        p = doc.add_paragraph()
+        rl = p.add_run(f"{label}: "); rl.bold=True; rl.font.size=Pt(9); rl.font.color.rgb=RGBColor(0x1a,0x3a,0x5c)
+        rv = p.add_run(value); rv.font.size=Pt(9)
+    doc.add_paragraph()
+
+    disc = doc.add_paragraph("DISCLAIMER: Research prototype only. Not a medical device. No real patient data. Built for Build Small Hackathon 2026.")
+    disc.runs[0].font.size = Pt(8)
+    disc.runs[0].font.color.rgb = RGBColor(0xaa,0xaa,0xaa)
+    doc.save(docx_path)
+    return docx_path
+
+
+# ── Segment ───────────────────────────────────────────────────────────────────
 def segment_image(input_image, conf_threshold=0.25):
     global last_result, chat_context, _chat_history
     _chat_history = []
     if input_image is None:
         return (None,"Upload a frame to begin analysis.","——","——",
-                gr.update(visible=False),gr.update(visible=False),
+                gr.update(visible=False),gr.update(visible=False),gr.update(visible=False),
                 gr.update(visible=False),gr.update(visible=False),gr.update(visible=False),
                 render_chat_html([],"en"))
     detector = get_detector()
@@ -298,8 +382,11 @@ def segment_image(input_image, conf_threshold=0.25):
     q2=suggested[1] if len(suggested)>1 else ""
     q3=suggested[2] if len(suggested)>2 else ""
     return (annotated_image, summary, alert, explanation,
-        gr.update(visible=True), gr.update(visible=True), gr.update(visible=True),
-        gr.update(value=q1, visible=bool(q1)),
+            gr.update(visible=True), gr.update(visible=True), gr.update(visible=True),
+            gr.update(value=q1,visible=bool(q1)),
+            gr.update(value=q2,visible=bool(q2)),
+            gr.update(value=q3,visible=bool(q3)),
+            render_chat_html(_chat_history,"en"))
 
 
 def send_message(message, language):
@@ -312,12 +399,9 @@ def send_message(message, language):
     system_prompt=(
         "You are SurgiSight, an expert surgical anatomy assistant for medical trainees. "
         +(f"Current frame detected: {', '.join(tissue_list)}. Safety status: {alert}. " if tissue_list else "")
-        +"Answer concisely in 2-4 sentences. "
-        +lang_cfg["prompt"])
-    # Build context from english originals for coherent conversation
+        +"Answer concisely in 2-4 sentences. "+lang_cfg["prompt"])
     msgs=[{"role":"system","content":system_prompt}]
-    for m in _chat_history:
-        msgs.append({"role":m["role"],"content":m["en"]})
+    for m in _chat_history: msgs.append({"role":m["role"],"content":m["en"]})
     msgs.append({"role":"user","content":message})
     try:
         resp=client.chat_completion(msgs,max_tokens=200,temperature=0.5)
@@ -334,6 +418,11 @@ def export_pdf():
     return generate_pdf(last_result["original"],last_result["annotated"],
                         last_result["seen"],last_result["alert"],last_result["explanation"])
 
+def export_word():
+    if not last_result: return None
+    return generate_word(last_result["original"],last_result["annotated"],
+                         last_result["seen"],last_result["alert"],last_result["explanation"])
+
 
 css = """
 .gradio-container { max-width:1120px !important; margin:0 auto !important; }
@@ -365,10 +454,10 @@ overlay_js = """
 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 · mAP50: 0.581
+# SurgiSight — Surgical Tissue Segmentation
+**AI-powered anatomy detection for laparoscopic training** · YOLOv26n-seg · Llama 3.1 8B · Modal GPU · CholecSeg8k · mAP50: 0.581
 
-> ⚠️ Research prototype — not a medical device. No real patient data.
+> Research prototype — No real patient data.
 """)
 
     with gr.Row(equal_height=True):
@@ -385,26 +474,26 @@ with gr.Blocks(title="SurgiSight — Surgical AI", js=overlay_js) as demo:
 
     explain_box = gr.Textbox(label="📖 Anatomy Brief", lines=4, placeholder="AI explanation will appear after analysis…")
 
+    # ── Export buttons ────────────────────────────────────────────────────────
+    with gr.Row():
+        pdf_btn  = gr.Button("⬇  Export PDF Report",   visible=False, variant="secondary")
+        word_btn = gr.Button("⬇  Export Word (.docx)", visible=False, variant="secondary")
     with gr.Row():
-        pdf_btn = gr.Button("⬇  Export Full Report (PDF)", visible=False)
-    pdf_output = gr.File(label="Download Report", visible=False)
+        pdf_output  = gr.File(label="📄 PDF Download",  visible=False)
+        word_output = gr.File(label="📝 Word Download", visible=False)
 
     with gr.Column(visible=False) as chat_section:
         gr.Markdown("---\n### 💬 AI Anatomy Consult")
-
         with gr.Row():
             lang_select = gr.Dropdown(
                 choices=list(LANGUAGES.keys()), value="English",
                 label="🌍 Language — switching retranslates all messages",
-                scale=0, min_width=260)
-
+                scale=0, min_width=280)
         with gr.Row():
             sq1 = gr.Button("", visible=False, size="sm")
             sq2 = gr.Button("", visible=False, size="sm")
             sq3 = gr.Button("", visible=False, size="sm")
-
         chat_display = gr.HTML(value="", label="")
-
         with gr.Row():
             chat_input = gr.Textbox(
                 placeholder="Ask about anatomy, safety, or technique…",
@@ -418,22 +507,19 @@ with gr.Blocks(title="SurgiSight — Surgical AI", js=overlay_js) 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, chat_display])
+                 pdf_btn, word_btn, chat_section, sq1, sq2, sq3, chat_display])
 
     pdf_btn.click(fn=export_pdf, outputs=[pdf_output]).then(
         fn=lambda: gr.update(visible=True), outputs=[pdf_output])
+    word_btn.click(fn=export_word, outputs=[word_output]).then(
+        fn=lambda: gr.update(visible=True), outputs=[word_output])
 
-    send_btn.click(fn=send_message, inputs=[chat_input, lang_select],
-        outputs=[chat_display, chat_input])
-    chat_input.submit(fn=send_message, inputs=[chat_input, lang_select],
-        outputs=[chat_display, chat_input])
-
-    # Language change → retranslate entire chat
+    send_btn.click(fn=send_message, inputs=[chat_input, lang_select], outputs=[chat_display, chat_input])
+    chat_input.submit(fn=send_message, inputs=[chat_input, lang_select], outputs=[chat_display, chat_input])
     lang_select.change(fn=retranslate_history, inputs=[lang_select], outputs=[chat_display])
-
     sq1.click(fn=send_message, inputs=[sq1, lang_select], outputs=[chat_display, chat_input])
     sq2.click(fn=send_message, inputs=[sq2, lang_select], outputs=[chat_display, chat_input])
     sq3.click(fn=send_message, inputs=[sq3, lang_select], outputs=[chat_display, chat_input])