Update app.py

app.py

@@ -224,6 +224,8 @@ class ContentAnalyzer:
         self.client = OpenAI(api_key=api_key)
         self.retry_count = 3
         self.retry_delay = 1
+        self.GPT4_INPUT_COST = 0.15 / 1_000_000  # $0.15 per 1M tokens input
+        self.GPT4_OUTPUT_COST = 0.60 / 1_000_000  # $0.60 per 1M tokens output
         
     def analyze_content(self, transcript: str, progress_callback=None) -> Dict[str, Any]:
         """Analyze teaching content with retry logic and robust JSON handling"""
@@ -233,8 +235,6 @@ class ContentAnalyzer:
                     progress_callback(0.2, "Preparing content analysis...")
                 
                 prompt = self._create_analysis_prompt(transcript)
-                logger.info(f"Attempt {attempt + 1}: Sending analysis request")
-                logger.info(f"Transcript length: {len(transcript)} characters")
                 
                 if progress_callback:
                     progress_callback(0.5, "Processing with AI model...")
@@ -651,6 +651,9 @@ class MentorEvaluator:
         self._feature_extractor = None
         self._content_analyzer = None
         self._recommendation_generator = None
+        
+        # Cost per minute for Whisper transcription
+        self.WHISPER_COST_PER_MINUTE = 0.006  # $0.006 per minute of audio
 
     @property
     def whisper_model(self):
@@ -660,8 +663,8 @@ class MentorEvaluator:
                 logger.info("Attempting to initialize Whisper model...")
                 # First try to initialize model with downloading allowed
                 self._whisper_model = WhisperModel(
-                    "small",
-                    device="small",
+                    "medium",
+                    device="cpu",
                     compute_type="int8",
                     download_root=self.model_cache_dir,
                     local_files_only=False  # Allow downloading if needed
@@ -1186,68 +1189,12 @@ def display_evaluation(evaluation: Dict[str, Any]):
             
             recommendations = evaluation.get("recommendations", {})
             
-            # Calculate Overall Score
-            communication_metrics = evaluation.get("communication", {})
-            teaching_data = evaluation.get("teaching", {})
-            
-            # Calculate Communication Score
-            comm_scores = []
-            for category in ["speed", "fluency", "flow", "intonation", "energy"]:
-                if category in communication_metrics:
-                    if "score" in communication_metrics[category]:
-                        comm_scores.append(communication_metrics[category]["score"])
-            
-            communication_score = (sum(comm_scores) / len(comm_scores) * 100) if comm_scores else 0
-            
-            # Calculate Teaching Score (combining concept and code assessment)
-            concept_assessment = teaching_data.get("Concept Assessment", {})
-            code_assessment = teaching_data.get("Code Assessment", {})
-            
-            teaching_scores = []
-            # Add concept scores
-            for category in concept_assessment.values():
-                if isinstance(category, dict) and "Score" in category:
-                    teaching_scores.append(category["Score"])
-            
-            # Add code scores
-            for category in code_assessment.values():
-                if isinstance(category, dict) and "Score" in category:
-                    teaching_scores.append(category["Score"])
+            # Geography Fit with improved formatting
+            # with st.expander("🌍 Geography Fit", expanded=True):
+            #     geography_fit = recommendations.get("geographyFit", "Not specified")
+            #     st.info(geography_fit)
             
-            teaching_score = (sum(teaching_scores) / len(teaching_scores) * 100) if teaching_scores else 0
-            
-            # Calculate Overall Score (50-50 weight between communication and teaching)
-            overall_score = (communication_score + teaching_score) / 2
-            
-            # Display Overall Scores at the top of recommendations
-            st.markdown("### 📊 Overall Performance")
-            col1, col2, col3 = st.columns(3)
-            
-            with col1:
-                st.metric(
-                    "Communication Score",
-                    f"{communication_score:.1f}%",
-                    delta="Pass" if communication_score >= 70 else "Needs Improvement",
-                    delta_color="normal" if communication_score >= 70 else "inverse"
-                )
-            
-            with col2:
-                st.metric(
-                    "Teaching Score",
-                    f"{teaching_score:.1f}%",
-                    delta="Pass" if teaching_score >= 70 else "Needs Improvement",
-                    delta_color="normal" if teaching_score >= 70 else "inverse"
-                )
-            
-            with col3:
-                st.metric(
-                    "Overall Score",
-                    f"{overall_score:.1f}%",
-                    delta="Pass" if overall_score >= 70 else "Needs Improvement",
-                    delta_color="normal" if overall_score >= 70 else "inverse"
-                )
-            
-            # Continue with existing recommendations display
+            # Improvements Needed with better formatting
             with st.expander("💡 Areas for Improvement", expanded=True):
                 improvements = recommendations.get("improvements", [])
                 if isinstance(improvements, list):
@@ -1528,108 +1475,6 @@ def check_dependencies() -> List[str]:
     
     return missing
 
-def generate_pdf_report(evaluation_data: Dict[str, Any]) -> bytes:
-    """Generate a formatted PDF report from evaluation data"""
-    try:
-        from reportlab.lib import colors
-        from reportlab.lib.pagesizes import letter
-        from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
-        from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle
-        from io import BytesIO
-        
-        # Create PDF buffer
-        buffer = BytesIO()
-        doc = SimpleDocTemplate(buffer, pagesize=letter)
-        styles = getSampleStyleSheet()
-        story = []
-        
-        # Title
-        title_style = ParagraphStyle(
-            'CustomTitle',
-            parent=styles['Heading1'],
-            fontSize=24,
-            spaceAfter=30
-        )
-        story.append(Paragraph("Mentor Demo Evaluation Report", title_style))
-        story.append(Spacer(1, 20))
-        
-        # Communication Metrics Section
-        story.append(Paragraph("Communication Metrics", styles['Heading2']))
-        comm_metrics = evaluation_data.get("communication", {})
-        
-        # Create tables for each metric category
-        for category in ["speed", "fluency", "flow", "intonation", "energy"]:
-            if category in comm_metrics:
-                metrics = comm_metrics[category]
-                story.append(Paragraph(category.title(), styles['Heading3']))
-                
-                data = [[k.replace('_', ' ').title(), str(v)] for k, v in metrics.items()]
-                t = Table(data, colWidths=[200, 200])
-                t.setStyle(TableStyle([
-                    ('BACKGROUND', (0, 0), (-1, 0), colors.grey),
-                    ('TEXTCOLOR', (0, 0), (-1, 0), colors.whitesmoke),
-                    ('ALIGN', (0, 0), (-1, -1), 'CENTER'),
-                    ('FONTNAME', (0, 0), (-1, 0), 'Helvetica-Bold'),
-                    ('FONTSIZE', (0, 0), (-1, 0), 14),
-                    ('BOTTOMPADDING', (0, 0), (-1, 0), 12),
-                    ('BACKGROUND', (0, 1), (-1, -1), colors.beige),
-                    ('TEXTCOLOR', (0, 1), (-1, -1), colors.black),
-                    ('FONTNAME', (0, 1), (-1, -1), 'Helvetica'),
-                    ('FONTSIZE', (0, 1), (-1, -1), 12),
-                    ('GRID', (0, 0), (-1, -1), 1, colors.black)
-                ]))
-                story.append(t)
-                story.append(Spacer(1, 20))
-        
-        # Teaching Analysis Section
-        story.append(Paragraph("Teaching Analysis", styles['Heading2']))
-        teaching_data = evaluation_data.get("teaching", {})
-        
-        for assessment_type in ["Concept Assessment", "Code Assessment"]:
-            if assessment_type in teaching_data:
-                story.append(Paragraph(assessment_type, styles['Heading3']))
-                categories = teaching_data[assessment_type]
-                
-                for category, details in categories.items():
-                    score = details.get("Score", 0)
-                    citations = details.get("Citations", [])
-                    
-                    data = [
-                        [category, "Score: " + ("Pass" if score == 1 else "Needs Improvement")],
-                        ["Citations:", ""]
-                    ] + [["-", citation] for citation in citations]
-                    
-                    t = Table(data, colWidths=[200, 300])
-                    t.setStyle(TableStyle([
-                        ('BACKGROUND', (0, 0), (-1, 0), colors.grey),
-                        ('TEXTCOLOR', (0, 0), (-1, 0), colors.whitesmoke),
-                        ('ALIGN', (0, 0), (-1, -1), 'LEFT'),
-                        ('FONTNAME', (0, 0), (-1, 0), 'Helvetica-Bold'),
-                        ('GRID', (0, 0), (-1, -1), 1, colors.black)
-                    ]))
-                    story.append(t)
-                    story.append(Spacer(1, 20))
-        
-        # Recommendations Section
-        story.append(Paragraph("Recommendations", styles['Heading2']))
-        recommendations = evaluation_data.get("recommendations", {})
-        
-        if "improvements" in recommendations:
-            story.append(Paragraph("Areas for Improvement:", styles['Heading3']))
-            for improvement in recommendations["improvements"]:
-                story.append(Paragraph("• " + improvement, styles['Normal']))
-        
-        # Build PDF
-        doc.build(story)
-        pdf_data = buffer.getvalue()
-        buffer.close()
-        
-        return pdf_data
-        
-    except Exception as e:
-        logger.error(f"Error generating PDF report: {e}")
-        raise RuntimeError(f"Failed to generate PDF report: {str(e)}")
-
 def main():
     try:
         # Set page config must be the first Streamlit command
@@ -1870,28 +1715,21 @@ def main():
                 st.success("Analysis complete!")
                 display_evaluation(st.session_state.evaluation_results)
                 
-                # Add download options
-                col1, col2 = st.columns(2)
+                # Add download button using stored results
+                if st.download_button(
+                    "📥 Download Full Report",
+                    json.dumps(st.session_state.evaluation_results, indent=2),
+                    "evaluation_report.json",
+                    "application/json",
+                    help="Download the complete evaluation report in JSON format"
+                ):
+                    st.success("Report downloaded successfully!")
                 
-                with col1:
-                    if st.download_button(
-                        "📥 Download JSON Report",
-                        json.dumps(st.session_state.evaluation_results, indent=2),
-                        "evaluation_report.json",
-                        "application/json",
-                        help="Download the raw evaluation data in JSON format"
-                    ):
-                        st.success("JSON report downloaded successfully!")
-                
-                with col2:
-                    if st.download_button(
-                        "📄 Download Full Report (PDF)",
-                        generate_pdf_report(st.session_state.evaluation_results),
-                        "evaluation_report.pdf",
-                        "application/pdf",
-                        help="Download a formatted PDF report with detailed analysis"
-                    ):
-                        st.success("PDF report downloaded successfully!")
+                # Debugging code
+                # if st.session_state.evaluation_results:
+                #     st.write("Debug: Teaching Analysis Structure")
+                #     teaching_data = st.session_state.evaluation_results.get("teaching", {})
+                #     st.json(teaching_data)
                 
             except Exception as e:
                 st.error(f"Error during evaluation: {str(e)}")