Update app.py

app.py

@@ -1,52 +1,42 @@
 import streamlit as st
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import pyttsx3
+from transformers import pipeline
+from gtts import gTTS
 from youtubesearchpython import VideosSearch
+import os
 
-# Load model and tokenizer
-model_name = "microsoft/DialoGPT-medium"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
+# Initialize the chatbot pipeline using a pre-trained model from Hugging Face
+chatbot = pipeline("text-generation", model="microsoft/DialoGPT-medium")
 
-# Initialize text-to-speech engine
-engine = pyttsx3.init()
-engine.setProperty('rate', 150)
-engine.setProperty('voice', 'english+f3')  # Choose a calm, soothing voice
-
-# Function to generate a response
-def chat_with_bot(input_text):
-    input_ids = tokenizer.encode(input_text + tokenizer.eos_token, return_tensors="pt")
-    response_ids = model.generate(input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id)
-    response = tokenizer.decode(response_ids[:, input_ids.shape[-1]:][0], skip_special_tokens=True)
-    return response
-
-# Function to search for YouTube videos related to grief and loss
-def get_video_links(query):
-    videos_search = VideosSearch(query, limit=3)
-    return videos_search.result()["result"]
-
-# Streamlit app interface
+# Streamlit app title
 st.title("Grief and Loss Support Bot")
-st.write("Welcome! This bot provides support and resources to help you cope with grief and loss.")
-
-user_input = st.text_input("You: ", placeholder="Type your message here...")
-if st.button("Send"):
-    if user_input:
-        # Generate and display response
-        bot_response = chat_with_bot(user_input)
-        st.write("Bot:", bot_response)
-
-        # Speak the response using text-to-speech
-        engine.say(bot_response)
-        engine.runAndWait()
-
-        # Display interactive content links
-        st.write("Here are some helpful resources:")
-        video_results = get_video_links("grief and loss support")
-        for video in video_results:
-            st.write(f"[{video['title']}]({video['link']})")
-    else:
-        st.write("Please enter a message.")
 
-# Footer
-st.write("Remember, you are not alone. If you're in crisis, please reach out to a trusted source or helpline.")
+# Text input for user queries
+user_input = st.text_input("You:", "")
+
+# Respond to user input
+if user_input:
+    # Generate a response from the chatbot
+    response = chatbot(user_input, max_length=50, num_return_sequences=1)[0]['generated_text']
+    st.text_area("Bot:", response, height=100)
+
+    # Convert the response to speech using gTTS and save as an audio file
+    tts = gTTS(text=response, lang='en')
+    tts.save("response.mp3")
+    audio_file = open("response.mp3", "rb")
+    audio_bytes = audio_file.read()
+    st.audio(audio_bytes, format="audio/mp3")
+    audio_file.close()
+    os.remove("response.mp3")  # Clean up the audio file after playback
+
+# YouTube search functionality for coping resources
+st.header("Helpful Videos")
+search_query = st.text_input("Enter a topic for video suggestions:")
+if search_query:
+    # Search for videos using YouTubeSearchPython
+    video_search = VideosSearch(search_query, limit=3)
+    results = video_search.result()
+    for video in results['result']:
+        st.write(f"[{video['title']}]({video['link']})")
+
+# Display a note for users
+st.write("**Note:** This bot is designed for general emotional support. For urgent help, please reach out to professional resources.")