update

app.py

@@ -4,6 +4,7 @@ import openai
 import streamlit as st
 from PIL import Image
 from dotenv import load_dotenv
+import time
 
 # Load environment variables from .env file
 load_dotenv()
@@ -27,15 +28,26 @@ def query_emotion(filename):
         st.error("Error detecting facial expression: " + response.text)
         return None
 
-# Function to generate a joke or motivational text using OpenAI
+# Function to generate a response using OpenAI based on detected emotion
 def generate_text_based_on_mood(emotion):
     try:
-        # Create a prompt for OpenAI
-        prompt = f"Generate a light-hearted joke or a motivational quote for someone who is feeling {emotion}."
-        
+        # Create a dynamic prompt based on the detected emotion
+        if emotion == "happy":
+            prompt = "Give a motivational quote to celebrate happiness."
+        elif emotion == "sad":
+            prompt = "Provide a comforting message for someone feeling sad."
+        elif emotion == "angry":
+            prompt = "Suggest a way to calm down someone who is feeling angry."
+        elif emotion == "fear":
+            prompt = "Give an encouraging message for someone feeling fearful."
+        elif emotion == "surprised":
+            prompt = "Offer a fun fact or light-hearted comment for someone feeling surprised."
+        elif emotion == "neutral":
+            prompt = "Provide a general motivational quote."
+
         # Call OpenAI's API
         response = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",  # Use the desired model
+            model="gpt-4",  # Use GPT-4 model
             messages=[
                 {"role": "user", "content": prompt}
             ]
@@ -47,7 +59,7 @@ def generate_text_based_on_mood(emotion):
 
     except Exception as e:
         st.error(f"Error generating text: {e}")
-        return "Sorry, I couldn't come up with a joke or motivation at this moment."
+        return "Sorry, I couldn't come up with a message at this moment."
 
 # Function to convert text to speech using gTTS
 def text_to_speech(text):
@@ -63,7 +75,7 @@ def text_to_speech(text):
 
 # Streamlit UI
 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 uplifting messages or motivations.")
 
 # Upload image
 uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
@@ -85,12 +97,12 @@ if uploaded_file is not None:
         st.write(f"Detected emotion: {emotion}")
 
         # Generate text based on detected emotion
-        joke = generate_text_based_on_mood(emotion)
+        message = generate_text_based_on_mood(emotion)
         st.write("Here's something to cheer you up:")
-        st.write(joke)
+        st.write(message)
 
-        # Convert the generated joke to audio
-        audio_file = text_to_speech(joke)
+        # 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: