Update src/app.py

src/app.py

@@ -2,7 +2,7 @@ import streamlit as st
 import cv2
 import numpy as np
 import os
-import tempfile                   # <-- 1. IMPORT TEMPFILE
+import tempfile
 from dotenv import load_dotenv
 from st_audiorec import st_audiorec
 from analysis import (
@@ -42,6 +42,16 @@ with col1:
     st.subheader("📸 1. Capture Your Expression")
     camera_image = st.camera_input("Take a snapshot")
     
+    # --- START: ADDED DEBUG BLOCK ---
+    # This block will re-run every time the app updates
+    if camera_image is None:
+        st.warning("DEBUG: 'camera_image' is currently None. Waiting for user to take photo...")
+    else:
+        st.success("DEBUG: Image captured!")
+        st.write(f"DEBUG: 'camera_image' has data. Type: {type(camera_image)}")
+        st.write(f"DEBUG: Image size: {camera_image.size} bytes")
+    # --- END: ADDED DEBUG BLOCK ---
+    
 with col2:
     st.subheader("💭 2. Your Query")
     user_query = st.text_area(
@@ -75,12 +85,9 @@ if st.button("🧠 Analyze My Emotion & Answer", type="primary", use_container_w
                 file_bytes = np.asarray(bytearray(camera_image.read()), dtype=np.uint8)
                 image = cv2.imdecode(file_bytes, cv2.IMREAD_COLOR)
                 
-                # --- 2. USE A NAMED TEMPORARY FILE FOR THE IMAGE ---
                 with tempfile.NamedTemporaryFile(delete=True, suffix=".jpg") as temp_img:
                     cv2.imwrite(temp_img.name, image)
-                    # Pass the unique temp file's name for analysis
                     facial_emotion = get_facial_emotion(temp_img.name)
-                # The temp_img file is now automatically deleted
                 
             except Exception as e:
                 st.error(f"Error processing image: {e}")
@@ -89,14 +96,11 @@ if st.button("🧠 Analyze My Emotion & Answer", type="primary", use_container_w
         # Step 2: Process recorded audio
         with st.spinner("🎵 Saving and analyzing audio..."):
             try:
-                # --- 3. USE A NAMED TEMPORARY FILE FOR THE AUDIO ---
                 with tempfile.NamedTemporaryFile(delete=True, suffix=".wav") as temp_aud:
                     temp_aud.write(audio_bytes)
                     
-                    # Pass the unique temp file's name for analysis
                     voice_emotion = get_voice_emotion(temp_aud.name)
                     transcript = get_transcript(temp_aud.name)
-                # The temp_aud file is now automatically deleted
 
             except Exception as e:
                 st.error(f"Error processing audio: {e}")