Update app.py

app.py

@@ -1,22 +1,22 @@
+# app.py
 # ============================================
-# CICE 2.0 Healthcare Team Assessment Tool - HF Gradio Version
-# app.py for deployment on Hugging Face Spaces
+# CICE 2.0 Healthcare Team Assessment Tool
+# Hugging Face Spaces - Single File Deployment
 # ============================================
 
 import os
 import time
-from datetime import datetime
 import re
-import numpy as np
-from PIL import Image
-import cv2
 import tempfile
 import mimetypes
-import shutil
+from datetime import datetime
+from getpass import getpass
+
 import gradio as gr
 from google import genai
 from google.genai import types
 from gtts import gTTS
+import cv2
 from reportlab.lib.pagesizes import letter
 from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
 from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
@@ -24,206 +24,276 @@ from reportlab.lib.units import inch
 from reportlab.lib.enums import TA_JUSTIFY, TA_CENTER
 from reportlab.lib.colors import HexColor
 
-# Set up the API key — Replace with a hardcoded key for demo or read from env on HF
-GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY") or "YOUR_GOOGLE_API_KEY"
+# Initialize Google Generative AI
+def init_genai_client():
+    api_key = os.environ.get("GOOGLE_API_KEY") or os.environ.get("GOOGLE_API_KEY_HIDDEN")
+    if not api_key:
+        raise ValueError("GOOGLE_API_KEY environment variable not set. Please add your API key in Secrets.")
+    return genai.Client(api_key=api_key)
 
-client = genai.Client(api_key=GOOGLE_API_KEY)
-model_name = "gemini-2.0-flash-exp"
+# CICE Assessment Class
+class CICE_Assessment:
+    def __init__(self, client):
+        self.client = client
+        self.model_name = "gemini-2.0-flash-exp"
 
+    def analyze_video(self, video_path):
+        """Analyze video using the 18-point CICE 2.0 assessment"""
+        try:
+            mime_type, _ = mimetypes.guess_type(video_path)
+            if mime_type is None:
+                mime_type = 'video/mp4'
 
-def analyze_video(video_path):
-    """Analyze video using the 18-point CICE 2.0 assessment with specific behavioral cues"""
-    try:
-        mime_type, _ = mimetypes.guess_type(video_path)
-        if mime_type is None:
-            mime_type = 'video/mp4'
+            print(f"📤 Uploading video (type: {mime_type})...")
+            with open(video_path, 'rb') as f:
+                video_file = self.client.files.upload(file=f, config={'mime_type': mime_type})
 
-        print(f"📤 Uploading video to Gemini AI (type: {mime_type})...")
-        with open(video_path, 'rb') as f:
-            video_file = client.files.upload(file=f, config={'mime_type': mime_type})
+            print("⏳ Processing video...")
+            max_wait = 300
+            wait_time = 0
+            while video_file.state == "PROCESSING" and wait_time < max_wait:
+                time.sleep(3)
+                wait_time += 3
+                video_file = self.client.files.get(name=video_file.name)
 
-        print("⏳ Processing video...")
-        max_wait = 300
-        wait_time = 0
-        while video_file.state == "PROCESSING" and wait_time < max_wait:
-            time.sleep(3)
-            wait_time += 3
-            video_file = client.files.get(name=video_file.name)
+            if video_file.state == "FAILED":
+                raise Exception("Video processing failed")
 
-        if video_file.state == "FAILED":
-            raise Exception("Video processing failed")
+            print("🔍 Analyzing team interactions...")
+            prompt = """Analyze this healthcare team interaction video and provide a comprehensive assessment based on the CICE 2.0 instrument's 18 interprofessional competencies, looking for these SPECIFIC BEHAVIORAL CUES:
 
-        print("🔍 Analyzing team interactions...")
+For EACH competency, clearly state whether it was "OBSERVED" or "NOT OBSERVED" based on these specific behaviors:
 
-        prompt = """Analyze this healthcare team interaction video and provide a comprehensive...
+1. IDENTIFIES FACTORS INFLUENCING HEALTH STATUS
+   LOOK FOR: Team mentions allergy bracelet, fall-related trauma, multiple injuries, or states airway/breathing/circulation concerns out loud
 
-[Same prompt as before — trimmed for brevity here but paste in full from original]
-        
-STRUCTURE YOUR RESPONSE AS FOLLOWS:
+2. IDENTIFIES TEAM GOALS FOR THE PATIENT
+   LOOK FOR: Team verbalizes goals like: stabilize airway, CPR/AED, give epinephrine, control bleeding, preserve tooth, prepare EMS handoff
 
-## OVERALL ASSESSMENT
-...
+3. PRIORITIZES GOALS FOCUSED ON IMPROVING HEALTH OUTCOMES
+   LOOK FOR: CPR/AED prioritized before bleeding/dental injury, EpiPen administered before addressing secondary injuries
 
-## DETAILED COMPETENCY EVALUATION
-...
+4. VERBALIZES DISCIPLINE-SPECIFIC ROLE (PRE-BRIEF)
+   LOOK FOR: Students acknowledge interprofessional communication expectations and scene safety review before scenario begins
 
-## STRENGTHS
-...
+5. OFFERS TO SEEK GUIDANCE FROM COLLEAGUES
+   LOOK FOR: Peer-to-peer checks (e.g., dental to dental: confirm tooth storage; nursing to nursing: confirm CPR quality)
 
-## AREAS FOR IMPROVEMENT
-...
+6. COMMUNICATES ABOUT COST-EFFECTIVE AND TIMELY CARE
+   LOOK FOR: Team chooses readily available supplies (AED, saline, tourniquet) without delay, states need for rapid EMS transfer
 
-## AUDIO SUMMARY
-...
+7. DIRECTS QUESTIONS TO OTHER HEALTH PROFESSIONALS BASED ON EXPERTISE
+   LOOK FOR: Asks discipline-specific expertise (e.g., "Dental—what do we do with the tooth?"), invites pharmacy/medical input on epinephrine use
 
-## FINAL SCORE
-..."""
-
-        response = client.models.generate_content(
-            model=model_name,
-            contents=[
-                types.Part.from_uri(file_uri=video_file.uri, mime_type=video_file.mime_type),
-                prompt
-            ]
-        )
-        print("✅ Analysis complete!")
-        return response.text
+8. AVOIDS DISCIPLINE-SPECIFIC TERMINOLOGY
+   LOOK FOR: Uses plain language like "no pulse" instead of "asystole"
 
-    except Exception as e:
-        return f"Error during analysis: {str(e)}"
+9. EXPLAINS DISCIPLINE-SPECIFIC TERMINOLOGY WHEN NECESSARY
+   LOOK FOR: Clarifies medical/dental terms for others when necessary
 
+10. COMMUNICATES ROLES AND RESPONSIBILITIES CLEARLY
+    LOOK FOR: Announces assignments out loud: "I'll do compressions," "I'll call 911," "I'll document"
 
-def generate_audio_feedback(text):
-    """Generate audio summary from text"""
-    audio_summary_match = re.search(r'## AUDIO SUMMARY\s*(.*?)(?=##|\Z)', text, re.DOTALL)
-    if audio_summary_match:
-        summary_text = audio_summary_match.group(1).strip()
-    else:
-        summary_text = create_brief_summary(text)
+11. ENGAGES IN ACTIVE LISTENING
+    LOOK FOR: Repeats back instructions ("Everyone clear for shock"), pauses to hear teammates' updates
 
-    clean_text = re.sub(r'[#*_\[\]()]', ' ', summary_text)
-    clean_text = re.sub(r'\s+', ' ', clean_text).strip()
+12. SOLICITS AND ACKNOWLEDGES PERSPECTIVES
+    LOOK FOR: Leader asks "Anything else we need to address?", responds to peer input respectfully
 
-    audio_script = f"""CICE Healthcare Team Assessment Summary.\n\n{clean_text}\n\nPlease refer to the detailed report for full insights.\nEnd of summary."""
+13. RECOGNIZES APPROPRIATE CONTRIBUTIONS
+    LOOK FOR: Affirms correct actions verbally ("Good catch on allergy bracelet"), non-verbal acknowledgment (nodding, thumbs up)
 
-    try:
-        tts = gTTS(text=audio_script, lang='en', slow=False, tld='com')
-        temp_audio_path = "/tmp/feedback.mp3"
-        tts.save(temp_audio_path)
-        return temp_audio_path
-    except Exception as e:
-        print(f"⚠️ Audio generation failed: {str(e)}")
-        return None
+14. RESPECTFUL OF OTHER TEAM MEMBERS
+    LOOK FOR: Listens without interrupting, values input across professions
 
+15. COLLABORATIVELY WORKS THROUGH INTERPROFESSIONAL CONFLICTS
+    LOOK FOR: Negotiates intervention priorities (airway vs. bleeding) respectfully
 
-def create_brief_summary(text):
-    observed_count = text.lower().count("observed") - text.lower().count("not observed")
-    total = 18
-    percentage = (observed_count / total) * 100
-
-    if percentage >= 85:
-        level = "Exemplary"
-    elif percentage >= 70:
-        level = "Proficient"
-    elif percentage >= 50:
-        level = "Developing"
-    else:
-        level = "Needs Improvement"
-
-    return f"""The team demonstrated {level} performance with {observed_count} out of {total} competencies observed,
-    achieving {percentage:.0f} percent overall.
-    Key strengths included strong team communication and role clarity.
-    Areas for improvement include enhancing active listening and conflict resolution skills.
-    The team should focus on pre-briefing protocols and post-scenario debriefing.
-    Emphasis should be placed on clear role assignment and closed-loop communication."""
-
-
-def parse_assessment_scores(assessment_text):
-    observed_count = assessment_text.lower().count("observed") - assessment_text.lower().count("not observed")
-    total_competencies = 18
-    percentage = (observed_count / total_competencies) * 100
-
-    if percentage >= 85:
-        level = "Exemplary"
-        color = "#0F766E"
-    elif percentage >= 70:
-        level = "Proficient"
-        color = "#1E40AF"
-    elif percentage >= 50:
-        level = "Developing"
-        color = "#EA580C"
-    else:
-        level = "Needs Improvement"
-        color = "#B91C1C"
-
-    return observed_count, total_competencies, percentage, level, color
-
-
-def generate_pdf_report(assessment_text):
-    temp_pdf_path = "/tmp/report.pdf"
-    try:
-        doc = SimpleDocTemplate(temp_pdf_path, pagesize=letter)
-        styles = getSampleStyleSheet()
-        title_style = ParagraphStyle('CustomTitle', parent=styles['Heading1'], fontSize=20, textColor=HexColor('#111827'), spaceAfter=30, alignment=TA_CENTER)
-        heading_style = ParagraphStyle('CustomHeading', parent=styles['Heading2'], fontSize=14, textColor=HexColor('#1E40AF'), spaceAfter=12, bold=True)
-        body_style = ParagraphStyle('CustomBody', parent=styles['BodyText'], fontSize=11, alignment=TA_JUSTIFY, spaceAfter=6)
-
-        elements = [Paragraph("CICE 2.0 Healthcare Team Assessment Report", title_style)]
-
-        timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-        elements.append(Paragraph(f"<b>Assessment Date:</b> {timestamp}", body_style))
-        elements.append(Spacer(1, 12))
-
-        lines = assessment_text.split('\n')
-        for line in lines:
-            line = line.strip()
-            if not line:
-                elements.append(Spacer(1, 6))
-            elif line.startswith('##'):
-                heading = line.replace('##', '').strip()
-                elements.append(Paragraph(heading, heading_style))
-            elif line.startswith('Competency'):
-                elements.append(Paragraph(f"<b>{line}</b>", body_style))
-            elif line.startswith('Status:') or line.startswith('Evidence:'):
-                elements.append(Paragraph(line, body_style))
-            else:
-                escaped_line = line.replace('&', '&amp;').replace('<', '&lt;').replace('>', '&gt;')
-                elements.append(Paragraph(escaped_line, body_style))
+16. REFLECTS ON STRENGTHS OF TEAM INTERACTIONS (POST-BRIEF)
+    LOOK FOR: Notes strong teamwork, communication, or role clarity after the scenario
 
-        doc.build(elements)
-        return temp_pdf_path
-    except Exception as e:
-        print(f"⚠️ PDF generation failed: {str(e)}")
-        temp_txt_path = "/tmp/report.txt"
-        with open(temp_txt_path, 'w') as f:
-            f.write("CICE 2.0 Healthcare Team Assessment\n")
-            f.write("="*60 + "\n")
-            f.write(f"Date: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n")
-            f.write("="*60 + "\n\n")
-            f.write(assessment_text)
-        return temp_txt_path
-
-
-def get_video_info(video_path):
+17. REFLECTS ON CHALLENGES OF TEAM INTERACTIONS (POST-BRIEF)
+    LOOK FOR: Identifies confusion, delays, or role overlap in debriefing
+
+18. IDENTIFIES HOW TO IMPROVE TEAM EFFECTIVENESS (POST-BRIEF)
+    LOOK FOR: Suggests faster role assignment, consistent closed-loop communication, earlier epi use
+
+STRUCTURE YOUR RESPONSE AS FOLLOWS:
+
+## OVERALL ASSESSMENT
+Brief overview of the team interaction quality.
+
+## DETAILED COMPETENCY EVALUATION
+For each of the 18 competencies, format as:
+Competency [number]: [name]
+Status: [OBSERVED/NOT OBSERVED]
+Evidence: [Specific behavioral cue observed or explanation of absence]
+
+## STRENGTHS
+Top 3-5 key strengths with specific examples
+
+## AREAS FOR IMPROVEMENT
+Top 3-5 areas needing work with specific suggestions
+
+## AUDIO SUMMARY
+[Create a concise 60-second spoken summary focusing on: overall performance level, top 3 strengths, top 3 areas for improvement, and 2 key actionable recommendations. Write this in a natural, conversational tone suitable for text-to-speech narration.]
+
+## FINAL SCORE
+Competencies Observed: X/18
+Overall Performance Level: [Exemplary (85-100%)/Proficient (70-84%)/Developing (50-69%)/Needs Improvement (0-49%)]"""
+
+            response = self.client.models.generate_content(
+                model=self.model_name,
+                contents=[
+                    types.Part.from_uri(file_uri=video_file.uri, mime_type=video_file.mime_type),
+                    prompt
+                ]
+            )
+            print("✅ Analysis complete!")
+            return response.text
+
+        except Exception as e:
+            return f"Error during analysis: {str(e)}"
+
+    def generate_audio_feedback(self, text):
+        """Generate audio summary"""
+        audio_summary_match = re.search(r'## AUDIO SUMMARY\s*(.*?)(?=##|\Z)', text, re.DOTALL)
+        if audio_summary_match:
+            summary_text = audio_summary_match.group(1).strip()
+        else:
+            summary_text = self.create_brief_summary(text)
+
+        clean_text = re.sub(r'[#*_\[\]()]', ' ', summary_text)
+        clean_text = re.sub(r'\s+', ' ', clean_text)
+        clean_text = re.sub(r'[-•·]\s+', '', clean_text)
+
+        audio_script = f"""CICE Healthcare Team Assessment Summary.
+        {clean_text}
+        Please refer to the detailed written report for complete competency evaluation and specific recommendations.
+        End of audio summary."""
+
+        try:
+            tts = gTTS(text=audio_script, lang='en', slow=False, tld='com')
+            temp_audio = tempfile.NamedTemporaryFile(delete=False, suffix='.mp3')
+            tts.save(temp_audio.name)
+            temp_audio.close()
+            return temp_audio.name
+        except Exception as e:
+            print(f"⚠️ Audio generation failed: {str(e)}")
+            return None
+
+    def create_brief_summary(self, text):
+        """Create fallback summary"""
+        observed_count = text.lower().count("observed") - text.lower().count("not observed")
+        total = 18
+        percentage = (observed_count / total) * 100
+
+        if percentage >= 85:
+            level = "Exemplary"
+        elif percentage >= 70:
+            level = "Proficient"
+        elif percentage >= 50:
+            level = "Developing"
+        else:
+            level = "Needs Improvement"
+
+        return f"""The team demonstrated {level} performance with {observed_count} out of {total} competencies observed,
+        achieving {percentage:.0f} percent overall.
+        Key strengths included strong team communication and role clarity.
+        Areas for improvement include enhancing active listening and conflict resolution skills.
+        The team should focus on pre-briefing protocols and post-scenario debriefing to enhance future performance.
+        Emphasis should be placed on clear role assignment and closed-loop communication during critical interventions."""
+
+    def parse_assessment_scores(self, assessment_text):
+        """Parse scores for visualization"""
+        observed_count = assessment_text.lower().count("observed") - assessment_text.lower().count("not observed")
+        total_competencies = 18
+        percentage = (observed_count / total_competencies) * 100
+
+        if percentage >= 85:
+            level = "Exemplary"
+            color = "#0F766E"
+        elif percentage >= 70:
+            level = "Proficient"
+            color = "#1E40AF"
+        elif percentage >= 50:
+            level = "Developing"
+            color = "#EA580C"
+        else:
+            level = "Needs Improvement"
+            color = "#B91C1C"
+
+        return observed_count, total_competencies, percentage, level, color
+
+    def generate_pdf_report(self, assessment_text):
+        """Generate PDF report"""
+        try:
+            temp_pdf = tempfile.NamedTemporaryFile(delete=False, suffix='.pdf')
+            doc = SimpleDocTemplate(temp_pdf.name, pagesize=letter)
+            elements = []
+            styles = getSampleStyleSheet()
+            
+            title_style = ParagraphStyle('CustomTitle', parent=styles['Heading1'], fontSize=20, textColor=HexColor('#111827'), spaceAfter=30, alignment=TA_CENTER)
+            heading_style = ParagraphStyle('CustomHeading', parent=styles['Heading2'], fontSize=14, textColor=HexColor('#1E40AF'), spaceAfter=12, spaceBefore=12, bold=True)
+            body_style = ParagraphStyle('CustomBody', parent=styles['BodyText'], fontSize=11, alignment=TA_JUSTIFY, spaceAfter=12)
+
+            elements.append(Paragraph("CICE 2.0 Healthcare Team Assessment Report", title_style))
+            elements.append(Spacer(1, 12))
+            timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+            elements.append(Paragraph(f"<b>Assessment Date:</b> {timestamp}", body_style))
+            elements.append(Spacer(1, 20))
+
+            lines = assessment_text.split('\n')
+            for line in lines:
+                line = line.strip()
+                if not line:
+                    elements.append(Spacer(1, 6))
+                elif line.startswith('##'):
+                    heading_text = line.replace('##', '').strip()
+                    elements.append(Paragraph(heading_text, heading_style))
+                elif line.startswith('Competency'):
+                    elements.append(Paragraph(f"<b>{line}</b>", body_style))
+                elif line.startswith('Status:') or line.startswith('Evidence:'):
+                    elements.append(Paragraph(line, body_style))
+                else:
+                    line = line.replace('&', '&amp;').replace('<', '&lt;').replace('>', '&gt;')
+                    elements.append(Paragraph(line, body_style))
+
+            doc.build(elements)
+            temp_pdf.close()
+            return temp_pdf.name
+        except Exception as e:
+            print(f"⚠️ PDF generation failed: {str(e)}")
+            temp_txt = tempfile.NamedTemporaryFile(delete=False, suffix='.txt', mode='w')
+            temp_txt.write("CICE 2.0 Healthcare Team Interaction Assessment\n")
+            temp_txt.write("="*60 + "\n")
+            temp_txt.write(f"Date: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n")
+            temp_txt.write("="*60 + "\n\n")
+            temp_txt.write(assessment_text)
+            temp_txt.close()
+            return temp_txt.name
+
+# Initialize assessment tool
+def initialize_assessor():
     try:
-        cap = cv2.VideoCapture(video_path)
-        width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
-        height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
-        fps = int(cap.get(cv2.CAP_PROP_FPS))
-        frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
-        cap.release()
-        return width, height, fps, frame_count
-    except:
-        return None, None, None, None
+        client = init_genai_client()
+        return CICE_Assessment(client)
+    except Exception as e:
+        print(f"Initialization error: {e}")
+        return None
 
+assessor = initialize_assessor()
 
+# Video processing functions
 def resize_video(input_path, target_width, target_height):
+    """Resize video for faster processing"""
     try:
         cap = cv2.VideoCapture(input_path)
         fps = int(cap.get(cv2.CAP_PROP_FPS))
         fourcc = cv2.VideoWriter_fourcc(*'mp4v')
-        temp_output_path = "/tmp/resized_video.mp4"
-        out = cv2.VideoWriter(temp_output_path, fourcc, fps, (target_width, target_height))
+        temp_output = tempfile.NamedTemporaryFile(delete=False, suffix='.mp4')
+        temp_output.close()
+        out = cv2.VideoWriter(temp_output.name, fourcc, fps, (target_width, target_height))
 
         print(f"📐 Resizing video to {target_width}x{target_height}...")
         while True:
@@ -235,22 +305,27 @@ def resize_video(input_path, target_width, target_height):
 
         cap.release()
         out.release()
-        return temp_output_path
+        print("✅ Video resized successfully")
+        return temp_output.name
     except Exception as e:
-        print(f"⚠️ Video resizing failed: {str(e)}")
+        print(f"⚠️ Video resize failed: {str(e)}")
         return input_path
 
-
+# Main processing function
 def process_video(video, resize_option):
+    """Process uploaded video"""
     if video is None:
-        return "Please upload or record a video.", None, None, None
+        return "Please upload a video first.", None, None, None
+
+    if assessor is None:
+        return "Error: API key not configured. Please check your secrets.", None, None, None
 
     try:
-        orig_width, orig_height, fps, frame_count = get_video_info(video)
-        if orig_width and orig_height:
-            print(f"📹 Original video: {orig_width}x{orig_height} @ {fps}fps ({frame_count} frames)")
+        print(f"📹 Processing video ({os.path.getsize(video)/(1024*1024):.1f}MB)...")
 
+        # Handle resizing
         video_to_process = video
+        temp_resized_file = None
         if resize_option != "Original (No Resize)":
             if "640x480" in resize_option:
                 target_width, target_height = 640, 480
@@ -259,69 +334,106 @@ def process_video(video, resize_option):
             elif "1280x720" in resize_option:
                 target_width, target_height = 1280, 720
             else:
-                target_width, target_height = orig_width, orig_height
+                target_width, target_height = 800, 600
+
+            temp_resized_file = resize_video(video, target_width, target_height)
+            video_to_process = temp_resized_file
 
-            if orig_width != target_width or orig_height != target_height:
-                video_to_process = resize_video(video, target_width, target_height)
+        # Analyze video
+        print("🏥 Starting CICE 2.0 Assessment...")
+        assessment_result = assessor.analyze_video(video_to_process)
+
+        # Cleanup
+        if temp_resized_file and temp_resized_file != video:
+            try:
+                os.unlink(temp_resized_file)
+            except:
+                pass
 
-        assessment_result = analyze_video(video_to_process)
         if "Error" in assessment_result:
             return assessment_result, None, None, None
 
-        audio_path = generate_audio_feedback(assessment_result)
-        pdf_path = generate_pdf_report(assessment_result)
-        observed, total, percentage, level, color = parse_assessment_scores(assessment_result)
+        # Generate outputs
+        print("🔊 Generating audio summary...")
+        audio_path = assessor.generate_audio_feedback(assessment_result)
+        
+        print("📄 Generating PDF report...")
+        pdf_path = assessor.generate_pdf_report(assessment_result)
+        
+        observed, total, percentage, level, color = assessor.parse_assessment_scores(assessment_result)
 
+        # Create HTML summary
         summary_html = f"""
-        <div style="padding:20px; border-radius:10px; background:white; box-shadow:0 2px 10px rgba(0,0,0,0.08);">
-            <h2>CICE 2.0 Assessment Summary</h2>
-            <div style="display:flex; justify-content:space-around;">
-                <div>
-                    <div style="font-size:36px; font-weight:bold; color:{color};">{observed}/{total}</div>
-                    <div>Competencies Observed</div>
+        <div style="max-width:800px; margin:20px auto; padding:30px; border-radius:15px; box-shadow:0 2px 10px rgba(0,0,0,0.08); background:white;">
+            <h2 style="text-align:center; color:#111827; margin-bottom:30px; font-weight:600;">CICE 2.0 Assessment Summary</h2>
+            <div style="display:flex; justify-content:space-around; margin:30px 0;">
+                <div style="text-align:center;">
+                    <div style="font-size:48px; font-weight:bold; color:{color};">{observed}/{total}</div>
+                    <div style="color:#4B5563; margin-top:10px; font-weight:500;">Competencies Observed</div>
                 </div>
-                <div>
-                    <div style="font-size:36px; font-weight:bold; color:{color};">{percentage:.0f}%</div>
-                    <div>Overall Score</div>
+                <div style="text-align:center;">
+                    <div style="font-size:48px; font-weight:bold; color:{color};">{percentage:.0f}%</div>
+                    <div style="color:#4B5563; margin-top:10px; font-weight:500;">Overall Score</div>
                 </div>
             </div>
-            <div style="text-align:center; margin-top:15px;">
-                <div style="padding:15px; background:#F8FAFC; border-radius:8px;">
-                    <div style="font-size:18px; font-weight:bold; color:{color};">Performance Level: {level}</div>
-                </div>
+            <div style="text-align:center; padding:20px; background:#F8FAFC; border-radius:10px; margin:20px 0; border:1px solid #E2E8F0;">
+                <div style="font-size:24px; font-weight:bold; color:{color};">Performance Level: {level}</div>
+            </div>
+            <div style="margin-top:30px; padding:20px; background:#FFF7ED; border-radius:10px; border-left:4px solid #EA580C;">
+                <p style="text-align:center; color:#431407; margin:0; font-weight:600;">
+                    🔊 Listen to the 1-minute audio summary<br>
+                    📄 Download the PDF report for complete documentation
+                </p>
             </div>
         </div>
         """
 
         return assessment_result, summary_html, audio_path, pdf_path
-    except Exception as e:
-        return f"Processing error: {str(e)}", None, None, None
 
+    except Exception as e:
+        error_msg = f"❌ Error during processing: {str(e)}"
+        print(error_msg)
+        return error_msg, None, None, None
 
-with gr.Blocks(title="CICE 2.0 Healthcare Team Assessment", theme=gr.themes.Soft()) as demo:
+# Gradio Interface
+with gr.Blocks(title="CICE 2.0 Healthcare Assessment", theme=gr.themes.Soft()) as demo:
     gr.Markdown("""
     # 🏥 CICE 2.0 Healthcare Team Assessment Tool
-    Analyze team interactions using AI-driven behavioral cues.
+
+    **Analyze healthcare team interactions using the 18-point CICE 2.0 framework**
+
+    ---
     """)
+
     with gr.Row():
         with gr.Column(scale=1):
+            gr.Markdown("### 📹 Video Input")
             resize_dropdown = gr.Dropdown(
                 choices=[
                     "Original (No Resize)",
-                    "640x480 (Fastest - Recommended)",
+                    "640x480 (Fastest - Recommended for quick tests)",
                     "800x600 (Fast - Good balance)",
-                    "1280x720 (HD - Best quality)"
+                    "1280x720 (HD - Best quality, slower)"
                 ],
                 value="800x600 (Fast - Good balance)",
-                label="🎬 Video Resolution"
+                label="Video Resolution"
+            )
+            
+            video_input = gr.Video(
+                label="Upload Video",
+                sources=["upload"],
+                format="mp4",
+                include_audio=True
             )
-            video_input = gr.Video(sources=["upload", "webcam"], format="mp4", include_audio=True)
-            analyze_btn = gr.Button("🔍 Analyze Video", variant="primary")
+            
+            analyze_btn = gr.Button("🔍 Analyze Video", variant="primary", size="lg")
+
         with gr.Column(scale=2):
-            summary_output = gr.HTML()
-            audio_output = gr.Audio(type="filepath")
-            pdf_output = gr.File(file_types=[".pdf", ".txt"])
-            assessment_output = gr.Textbox(label="Detailed Assessment", lines=15, interactive=False)
+            gr.Markdown("### 📊 Assessment Results")
+            summary_output = gr.HTML(value="<p style='text-align:center; color:#6b7280; padding:40px;'>Results will appear here after analysis...</p>")
+            audio_output = gr.Audio(label="🔊 1-Minute Audio Summary", type="filepath")
+            pdf_output = gr.File(label="📄 Download Full PDF Report")
+            assessment_output = gr.Textbox(label="Detailed Assessment", lines=20, max_lines=30, interactive=False)
 
     analyze_btn.click(
         fn=process_video,
@@ -329,5 +441,6 @@ with gr.Blocks(title="CICE 2.0 Healthcare Team Assessment", theme=gr.themes.Soft
         outputs=[assessment_output, summary_output, audio_output, pdf_output]
     )
 
+# Launch configuration for Hugging Face
 if __name__ == "__main__":
     demo.launch()