Update app.py

app.py

@@ -1,9 +1,9 @@
 #############################################################################################################################
 # Filename   : app.py
 # Description: A Streamlit application to detect facial expressions from images and provide responses.
-# Author     : Lucas Yao
+# Author     : [Your Name]
 #
-# Copyright © 2024 by Lucas Yao
+# Copyright © 2024 by [Your Name]
 #############################################################################################################################
 
 # Import libraries.
@@ -50,15 +50,17 @@ def query_emotion(image):
     return predicted_label
 
 #############################################################################################################################
-# Function to generate a response using OpenAI based on detected emotion.
-def generate_text_based_on_mood(emotion):
+# Function to generate a response using OpenAI based on detected emotion and user preference.
+def generate_text_based_on_mood(emotion, response_type):
     try:
-        # Create a dynamic prompt based on the detected emotion.
-        prompt = f"Generate a light-hearted joke or motivational message for someone who is feeling {emotion}."
-
+        if response_type == "Joke":
+            prompt = f"Generate a light-hearted joke for someone who is feeling {emotion}."
+        else:  # Motivational Message
+            prompt = f"Generate a motivational message for someone who is feeling {emotion}."
+        
         # Call OpenAI's API using GPT-4.
         response = openai.ChatCompletion.create(
-            model="gpt-4",  # Specify the GPT-4 model.
+            model="gpt-4",  # Specify the GPT-4 model
             messages=[
                 {"role": "user", "content": prompt}
             ]
@@ -89,7 +91,7 @@ def text_to_speech(text):
 # Main function to create the Streamlit web application.
 def main():
     st.title("Facial Expression Mood Detector")
-    st.write("Upload an image of a face to detect mood and receive uplifting messages or jokes.")
+    st.write("Upload an image of a face to detect mood and receive a response.")
 
     # Upload image.
     uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
@@ -103,17 +105,21 @@ def main():
         emotion = query_emotion(image)
         st.write(f"Detected emotion: {emotion}")
 
-        # Generate text based on detected emotion.
-        message = generate_text_based_on_mood(emotion)
-        st.write("Here's something to remind you:")
-        st.write(message)
+        # Dropdown for selecting response type.
+        response_type = st.selectbox("Select the type of response:", ["Joke", "Motivational Message"])
+
+        # Generate text based on detected emotion and user preference.
+        if st.button("Get Response"):
+            message = generate_text_based_on_mood(emotion, response_type)
+            st.write("Here's your response:")
+            st.write(message)
 
-        # Convert the generated message to audio.
-        audio_file = text_to_speech(message)
+            # Convert the generated message to audio.
+            audio_file = text_to_speech(message)
 
-        # Provide an audio player in the Streamlit app if audio file exists.
-        if audio_file:
-            st.audio(audio_file)  # Streamlit will handle playback.
+            # Provide an audio player in the Streamlit app if audio file exists.
+            if audio_file:
+                st.audio(audio_file)  # Streamlit will handle playback.
 
 #############################################################################################################################
 # Run the application.