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| import numpy as np | |
| from sentence_transformers import SentenceTransformer | |
| from gtts import gTTS | |
| import gradio as gr | |
| from transformers import pipeline | |
| # Load Sentiment Analysis and Emotion Detection models | |
| sentiment_analyzer = pipeline("sentiment-analysis") | |
| emotion_detector = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base") | |
| # Load a smaller pre-trained text generation model for faster output | |
| text_generator = pipeline("text-generation", model="distilgpt2") # Smaller model for faster inference | |
| # Analyze sentiment and emotion | |
| def analyze_sentiment_and_emotion(user_input): | |
| sentiment = sentiment_analyzer(user_input)[0]['label'] | |
| emotion = emotion_detector(user_input)[0]['label'] | |
| return sentiment, emotion | |
| # Generate response based on sentiment and emotion with a supportive approach | |
| def generate_response(user_input, sentiment, emotion): | |
| # Construct response prompts based on detected sentiment and emotion | |
| if sentiment == "POSITIVE": | |
| prompt = ( | |
| f"I’m glad to hear that you’re feeling {emotion}. Maintaining positive energy is so important, " | |
| f"and it's wonderful to hear about your good state. Here are a few ways you can continue to nurture " | |
| f"this happiness: focus on the things that bring you joy, spend time with people who uplift you, " | |
| f"and take moments to appreciate your achievements, big and small. Remember, happiness is often found " | |
| f"in appreciating the little things in life. Keep this positivity going, and know that your good " | |
| f"energy can also inspire others around you. Is there anything specific that brings you joy?" | |
| ) | |
| else: # Assume sentiment is NEGATIVE | |
| prompt = ( | |
| f"I’m here to listen and support you. It’s completely normal to feel {emotion} sometimes, and it’s " | |
| f"okay to acknowledge these feelings. Often, difficult emotions are a way for our minds to tell us " | |
| f"that something needs attention. Take your time, and consider ways to care for yourself. Whether it’s " | |
| f"reaching out to loved ones, taking a break, or reflecting on what brings you peace, there are steps " | |
| f"you can take. Remember, emotions are part of life’s journey, and finding meaning through challenging " | |
| f"times can lead to growth. You’re not alone in this; I’m here to help guide you. " | |
| ) | |
| # Generate the response from the model | |
| response = text_generator(prompt, max_length=250, num_return_sequences=1, do_sample=True)[0]["generated_text"] | |
| return response | |
| # Convert text response to audio | |
| def text_to_audio(response_text): | |
| tts = gTTS(response_text, lang='en') | |
| tts.save("response.mp3") | |
| return "response.mp3" # Return the file path for Gradio to play audio | |
| # Process the input and generate output | |
| def gradio_interface(user_input): | |
| if not user_input: | |
| return "Please provide complete input and submit.", None, None, None | |
| # Perform sentiment analysis and emotion detection | |
| sentiment, emotion = analyze_sentiment_and_emotion(user_input) | |
| # Generate a response from the text generation model | |
| response_text = generate_response(user_input, sentiment, emotion) | |
| # Convert to audio and return both text and audio output | |
| audio_file = text_to_audio(response_text) | |
| return response_text, audio_file, sentiment, emotion | |
| # Create the Gradio interface | |
| iface = gr.Interface( | |
| fn=gradio_interface, | |
| inputs="text", | |
| outputs=["text", "audio", "text", "text"], # Outputs: response, audio, sentiment, emotion | |
| live=False, # Disable live updates to require submitting | |
| title="Virtual Psychologist App", | |
| description="Enter your thoughts or feelings, and the app will provide a thoughtful response based on your input. It also provides sentiment and emotion analysis.", | |
| allow_flagging="never" # Optional: Disable flagging | |
| ) | |
| # Launch the app | |
| iface.launch() | |