Update app.py
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app.py
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import streamlit as st
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from transformers import
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import tiktoken
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import tensorflow_probability as tfp
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#
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# Load
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tokenizer = AutoTokenizer.from_pretrained(llm_model_name)
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llm_model = AutoModelForCausalLM.from_pretrained(llm_model_name)
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#
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"
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"
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}
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#
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input_ids = tokenizer(prompt, return_tensors="pt").input_ids
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output_ids = llm_model.generate(input_ids, num_beams=num_beams)
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return tokenizer.decode(output_ids[0])
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#
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def welcome_page():
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user_input = st.text_input("Talk to the Therapist", placeholder="Start your conversation")
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if user_input:
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response = dialogflow_agent.text_query(user_input)
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st.write(f"{welcome_message}\n\n{note}\n\n{response.query_result.fulfillment_text}")
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prompt = f"Write about a time when you felt {emotion} about {topic}."
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generated_text = generate_text(prompt)
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st.write("Here are some personalized journaling prompts for you:")
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for line in generated_text.split('\n'):
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st.write(f"- {line}")
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exercise_name = st.radio("Choose your breathing exercise", options=list(breathing_exercises.keys()))
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if exercise_name:
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exercise = breathing_exercises[exercise_name]
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st.write(f"You selected the {exercise_name} exercise.")
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for duration in exercise:
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st.write(f"{duration} seconds...")
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time.sleep(duration)
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st.write("Breathing exercise complete!")
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#
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st.
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if
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elif page_selection == "Journaling":
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journaling_page()
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elif page_selection == "Breathing Exercises":
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breathing_page()
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# app.py
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import streamlit as st
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from transformers import pipeline
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# Function to load Hugging Face models
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def load_model(model_name):
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return pipeline("text-generation", model=model_name, device=0) # Adjust the model type accordingly
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# Page 1: Welcome and Chatbot
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def page_welcome():
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st.title("Welcome to Your Virtual Therapist")
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st.write("Feel free to chat with our virtual therapist!")
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# Load your preferred Hugging Face chatbot model
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chatbot_model = load_model("your-chatbot-model-name")
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user_input = st.text_input("You: ")
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if user_input:
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response = chatbot_model(user_input, max_length=50, num_return_sequences=1)[0]['generated_text']
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st.text_area("Therapist:", response, height=100)
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# Page 2: Journaling
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def page_journaling():
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st.title("Journaling Session")
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st.write("Answer the following questions based on your preferences:")
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# Add your journaling questions here
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journaling_question = st.text_area("Question:", "How was your day?")
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# Process the user's response as needed
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# Page 3: Breathing Exercises
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def page_breathing_exercises():
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st.title("Breathing Exercises")
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st.write("Start your meditation with the breathing exercise timer:")
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# Add a timer or interactive element for breathing exercises
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# Main App
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def main():
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st.sidebar.title("Navigation")
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selection = st.sidebar.radio("Go to", ["Welcome & Chatbot", "Journaling", "Breathing Exercises"])
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if selection == "Welcome & Chatbot":
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page_welcome()
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elif selection == "Journaling":
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page_journaling()
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elif selection == "Breathing Exercises":
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page_breathing_exercises()
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if __name__ == "__main__":
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main()
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