GH111 commited on
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08185a7
1 Parent(s): e36951d

Update app.py

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  1. app.py +41 -62
app.py CHANGED
@@ -1,74 +1,53 @@
 
 
1
  import streamlit as st
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- from transformers import AutoModelForCausalLM, AutoTokenizer
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- from google.cloud import dialogflow
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- import kaleido
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- import cohere
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- import openai
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- import tiktoken
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- import tensorflow_probability as tfp
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- # Define model paths
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- dialogflow_agent_path = "path/to/dialogflow_agent.json"
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- journaling_model_path = "path/to/journaling_model.pt"
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- llm_model_name = "gpt-j-6B"
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- # Load models
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- dialogflow_agent = dialogflow.Agent.from_json(dialogflow_agent_path)
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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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- # Define emotion and topic choices
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- emotions = ["Grateful", "Happy", "Sad", "Angry", "Anxious"]
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- topics = ["Relationships", "Work", "Personal Growth", "Overall Wellbeing"]
 
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- # Define breathing exercises
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- breathing_exercises = {
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- "4-7-8 Breathing": [4, 7, 8],
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- "Box Breathing": [4, 4, 4, 4],
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- }
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- # Function to generate text with LLM
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- def generate_text(prompt, num_beams=5):
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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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- # Define individual page functions
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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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- def journaling_page():
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- emotion = st.radio("Choose your emotion", options=emotions)
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- topic = st.radio("Choose your topic", options=topics)
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- if emotion and topic:
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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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- def breathing_page():
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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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- # Streamlit app layout
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- st.title("Flow: Self-Healing, Wellness, and Goal-Setting")
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- st.write("Welcome to your journey towards self-healing, wellness, and goal achievement.")
 
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- page_selection = st.sidebar.selectbox("Choose your page", options=["Welcome", "Journaling", "Breathing Exercises"])
 
 
 
 
 
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- if page_selection == "Welcome":
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- welcome_page()
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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()
 
1
+ # app.py
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+
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  import streamlit as st
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+ from transformers import pipeline
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+
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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()