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| import streamlit as st | |
| from transformers import pipeline | |
| from gtts import gTTS | |
| from io import BytesIO | |
| import random | |
| import requests | |
| from youtubesearchpython import VideosSearch | |
| # Initialize the empathy bot pipeline | |
| empathy_bot = pipeline("text2text-generation", model="mrm8488/t5-base-finetuned-empathy") | |
| # Function to process the user's input and generate a dynamic response | |
| def generate_dynamic_response(user_input): | |
| # Generate an empathetic response using the model | |
| response = empathy_bot(user_input) | |
| empathetic_response = response[0]['generated_text'] | |
| # Possible activities to suggest | |
| activities = { | |
| "relaxation": [ | |
| "Deep Breathing Exercises", | |
| "Guided Meditation", | |
| "Mindfulness Breathing" | |
| ], | |
| "creative": [ | |
| "Journaling your thoughts", | |
| "Drawing or doodling", | |
| "Writing a poem" | |
| ], | |
| "exercise": [ | |
| "Try some yoga", | |
| "Go for a walk outside", | |
| "Stretching exercises to release tension" | |
| ], | |
| "self-care": [ | |
| "Take a warm bath", | |
| "Listen to calming music", | |
| "Treat yourself with some relaxation time" | |
| ] | |
| } | |
| # Logic to determine context of user input (e.g., stress, sadness, etc.) | |
| if "sad" in user_input or "overwhelmed" in user_input: | |
| suggested_activity = random.choice(activities["relaxation"]) | |
| elif "bored" in user_input or "unmotivated" in user_input: | |
| suggested_activity = random.choice(activities["creative"]) | |
| elif "stressed" in user_input or "tired" in user_input: | |
| suggested_activity = random.choice(activities["exercise"]) | |
| else: | |
| suggested_activity = random.choice(activities["self-care"]) | |
| # Search YouTube for relevant videos based on the activity suggestion | |
| video_keywords = suggested_activity | |
| video_results = search_youtube_videos(video_keywords) | |
| return empathetic_response, suggested_activity, video_results | |
| # Function to search for YouTube videos | |
| def search_youtube_videos(query): | |
| videos_search = VideosSearch(query, limit=3) | |
| results = videos_search.result() | |
| # Collect video details | |
| video_links = [] | |
| for video in results['videos']: | |
| title = video['title'] | |
| link = video['link'] | |
| video_links.append((title, link)) | |
| return video_links | |
| # Streamlit UI | |
| st.title("Grief and Loss Support Bot 🌿") | |
| st.markdown("Your compassionate companion in tough times 💚") | |
| user_input = st.text_input("Share what's on your mind...") | |
| if user_input: | |
| empathetic_response, suggested_activity, video_results = generate_dynamic_response(user_input) | |
| # Display the empathetic response | |
| st.write(f"**Bot's Response:**") | |
| st.write(empathetic_response) | |
| # Suggest an activity | |
| st.write(f"Here's a suggestion to help you cope:") | |
| st.write(f"**Activity to try:** {suggested_activity}") | |
| # Display YouTube video suggestions | |
| if video_results: | |
| st.write("Here are some YouTube videos that may help:") | |
| for title, link in video_results: | |
| st.write(f"[{title}]({link})") | |
| # Generate and play an audio response using gTTS | |
| tts = gTTS(empathetic_response, lang='en') | |
| audio_file = BytesIO() | |
| tts.save(audio_file) | |
| audio_file.seek(0) | |
| st.audio(audio_file, format="audio/mp3", use_container_width=True) | |