Update app.py

app.py

@@ -1,77 +1,52 @@
 import streamlit as st
-from transformers import pipeline
-from gtts import gTTS
-import os
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import pyttsx3
 from youtubesearchpython import VideosSearch
 
-# Page configuration
-st.set_page_config(page_title="Grief Support Bot", layout="wide")
-st.markdown("<style>.stApp {background-color: #f0f5f9;}</style>", unsafe_allow_html=True)
-
-# Load the pre-trained chatbot model
-chatbot = pipeline("conversational", model="microsoft/DialoGPT-medium")
-
-# Function for voice output
-def speak_text(text):
-    tts = gTTS(text, lang='en')
-    tts.save("response.mp3")
-    os.system("mpg321 response.mp3")  # This plays the audio
-    st.audio("response.mp3")
-
-# Function to search for YouTube videos
-def get_video_links(query, max_results=3):
-    search = VideosSearch(query, max_results=max_results)
-    results = search.result()['result']
-    return [(video['title'], video['link']) for video in results]
-
-# Function to detect crisis keywords
-crisis_keywords = ["suicide", "hopeless", "alone", "depressed"]
-
-def detect_crisis(input_text):
-    return any(word in input_text.lower() for word in crisis_keywords)
-
-# Function to suggest hobbies
-def suggest_hobbies():
-    return ["Painting", "Gardening", "Writing", "Yoga", "Learning an instrument"]
-
-# App header
+# Load model and tokenizer
+model_name = "microsoft/DialoGPT-medium"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# 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
 st.title("Grief and Loss Support Bot")
-
-# Maintain conversation history using session state
-if 'history' not in st.session_state:
-    st.session_state['history'] = []
-
-# User input
-user_input = st.text_input("You:")
-
-# If there is input, process the conversation
-if user_input:
-    # Crisis detection
-    if detect_crisis(user_input):
-        st.warning("We care about you. If you're in crisis, please reach out to a trusted person or call emergency services.")
-        st.markdown("Hotline resources: [Link to emergency contacts]")
+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:
-        # Generate chatbot response
-        response = chatbot(user_input)
-        generated_text = response[0]['generated_text']
-        
-        # Append to history and display response
-        st.session_state['history'].append(("You", user_input))
-        st.session_state['history'].append(("Bot", generated_text))
-        
-        # Display conversation history
-        for speaker, text in st.session_state['history']:
-            st.write(f"**{speaker}:** {text}")
-        
-        # Voice output
-        speak_text(generated_text)
-
-# Display hobby suggestions
-st.markdown("### Hobby Suggestions")
-st.markdown(", ".join(suggest_hobbies()))
+        st.write("Please enter a message.")
 
-# Provide interactive YouTube video links
-st.markdown("### Videos to Help You Cope with Grief")
-video_links = get_video_links("coping with grief and loss", max_results=3)
-for title, link in video_links:
-    st.markdown(f"- [{title}]({link})")
+# Footer
+st.write("Remember, you are not alone. If you're in crisis, please reach out to a trusted source or helpline.")