Update session_analysis.py

session_analysis.py

@@ -1,5 +1,6 @@
 import streamlit as st
 import io
+from io import BytesIO
 import pandas as pd
 import plotly.express as px
 import plotly.graph_objects as go
@@ -57,6 +58,47 @@ def show_upload_section():
     else:  # Previous Session Data
         show_previous_sessions_selector()
 
+def process_video_file(video_file):
+    """Process uploaded video file"""
+    try:
+        # Save video temporarily
+        temp_path = f"temp_video_{datetime.now().strftime('%Y%m%d_%H%M%S')}.mp4"
+        with open(temp_path, "wb") as f:
+            f.write(video_file.getbuffer())
+        
+        st.video(temp_path)
+        st.info("Video uploaded successfully. Please note: automatic transcription is not yet implemented. Please provide transcript manually.")
+        
+        # Add manual transcript input
+        transcript = st.text_area("Please enter the session transcript:", height=300)
+        if transcript:
+            st.session_state.current_transcript = transcript
+            analyze_session_content(transcript)
+            
+    except Exception as e:
+        st.error(f"Error processing video: {str(e)}")
+
+def process_audio_file(audio_file):
+    """Process uploaded audio file"""
+    try:
+        # Save audio temporarily
+        temp_path = f"temp_audio_{datetime.now().strftime('%Y%m%d_%H%M%S')}.mp3"
+        with open(temp_path, "wb") as f:
+            f.write(audio_file.getbuffer())
+        
+        st.audio(temp_path)
+        st.info("Audio uploaded successfully. Please note: automatic transcription is not yet implemented. Please provide transcript manually.")
+        
+        # Add manual transcript input
+        transcript = st.text_area("Please enter the session transcript:", height=300)
+        if transcript:
+            st.session_state.current_transcript = transcript
+            analyze_session_content(transcript)
+            
+    except Exception as e:
+        st.error(f"Error processing audio: {str(e)}")
+
+
 def process_media_file(file, type):
     st.write(f"Processing {type}...")
     
@@ -313,38 +355,54 @@ def process_analysis_results(raw_analysis):
     }
 
 def show_analysis_results():
-    """Display comprehensive analysis results"""
+    """Display the analysis results in the dashboard"""
     if not st.session_state.analysis_results:
         return
-
-    results = st.session_state.analysis_results
-    
-    # Top-level metrics
-    show_mi_metrics_dashboard(results['metrics'])
-    
-    # Detailed analysis sections
-    tabs = st.tabs([
-        "MI Adherence", 
-        "Technical Skills", 
-        "Client Language", 
-        "Session Flow", 
-        "Recommendations"
-    ])
     
-    with tabs[0]:
-        show_mi_adherence_analysis(results)
-    
-    with tabs[1]:
-        show_technical_skills_analysis(results)
+    # Use the analysis results directly (they're already parsed)
+    analysis = st.session_state.analysis_results
+    
+    # Display MI Adherence Score
+    st.subheader("MI Adherence Score")
+    score = analysis.get('mi_adherence_score', 0)
+    create_gauge_chart(score)
+    
+    # Display Key Themes
+    st.subheader("Key Themes")
+    themes = analysis.get('key_themes', [])
+    if themes:
+        for theme in themes:
+            st.markdown(f"• {theme}")
+    
+    # Display Technique Usage
+    st.subheader("MI Technique Usage")
+    technique_usage = analysis.get('technique_usage', {})
+    if technique_usage:
+        fig = go.Figure(data=[
+            go.Bar(x=list(technique_usage.keys()), y=list(technique_usage.values()))
+        ])
+        fig.update_layout(title="Technique Usage Frequency")
+        st.plotly_chart(fig)
+    
+    # Display Strengths and Areas for Improvement
+    col1, col2 = st.columns(2)
     
-    with tabs[2]:
-        show_client_language_analysis(results)
+    with col1:
+        st.subheader("Strengths")
+        strengths = analysis.get('strengths', [])
+        for strength in strengths:
+            st.markdown(f"✓ {strength}")
     
-    with tabs[3]:
-        show_session_flow_analysis(results)
+    with col2:
+        st.subheader("Areas for Improvement")
+        improvements = analysis.get('areas_for_improvement', [])
+        for improvement in improvements:
+            st.markdown(f"△ {improvement}")
     
-    with tabs[4]:
-        show_recommendations(results)
+    # Display Session Summary
+    st.subheader("Session Summary")
+    st.write(analysis.get('session_summary', ''))
+
 
 def show_mi_metrics_dashboard(metrics):
     st.subheader("MI Performance Dashboard")
@@ -513,24 +571,36 @@ def save_analysis_results():
             st.error(f"Error saving analysis results: {str(e)}")
 
 def show_upload_section():
-    st.header("Session Data Upload")
+    """Display the upload section of the dashboard"""
+    st.subheader("Upload Session")
     
     upload_type = st.radio(
-        "Select Input Method:",
-        ["Text Transcript", "Session Notes", "Previous Session Data"]  # Removed Audio/Video options
+        "Choose input method:",
+        ["Text Transcript", "Video Recording", "Audio Recording", "Session Notes", "Previous Sessions"]
     )
     
     if upload_type == "Text Transcript":
-        file = st.file_uploader("Upload Transcript", type=["txt", "doc", "docx", "json"])
+        file = st.file_uploader("Upload transcript file", type=['txt', 'doc', 'docx'])
         if file:
             process_text_file(file)
             
+    elif upload_type == "Video Recording":
+        video_file = st.file_uploader("Upload video file", type=['mp4', 'mov', 'avi'])
+        if video_file:
+            process_video_file(video_file)
+            
+    elif upload_type == "Audio Recording":
+        audio_file = st.file_uploader("Upload audio file", type=['mp3', 'wav', 'm4a'])
+        if audio_file:
+            process_audio_file(audio_file)
+            
     elif upload_type == "Session Notes":
         show_manual_input_form()
         
-    else:  # Previous Session Data
+    else:
         show_previous_sessions_selector()
 
+
 def process_text_file(file):
     try:
         if file.name.endswith('.json'):