app.py

import streamlit as st
from transformers import AutoModelForCausalLM, AutoTokenizer
from google.cloud import dialogflow
import kaleido
import cohere
import openai
import tiktoken
import tensorflow_probability as tfp

# Define model paths
dialogflow_agent_path = "path/to/dialogflow_agent.json"
journaling_model_path = "path/to/journaling_model.pt"
llm_model_name = "gpt-j-6B"

# Load models
dialogflow_agent = dialogflow.Agent.from_json(dialogflow_agent_path)
tokenizer = AutoTokenizer.from_pretrained(llm_model_name)
llm_model = AutoModelForCausalLM.from_pretrained(llm_model_name)

# Define emotion and topic choices
emotions = ["Grateful", "Happy", "Sad", "Angry", "Anxious"]
topics = ["Relationships", "Work", "Personal Growth", "Overall Wellbeing"]

# Define breathing exercises
breathing_exercises = {
    "4-7-8 Breathing": [4, 7, 8],
    "Box Breathing": [4, 4, 4, 4],
}

# Function to generate text with LLM
def generate_text(prompt, num_beams=5):
    input_ids = tokenizer(prompt, return_tensors="pt").input_ids
    output_ids = llm_model.generate(input_ids, num_beams=num_beams)
    return tokenizer.decode(output_ids[0])

# Define individual page functions
def welcome_page():
    user_input = st.text_input("Talk to the Therapist", placeholder="Start your conversation")
    if user_input:
        response = dialogflow_agent.text_query(user_input)
        st.write(f"{welcome_message}\n\n{note}\n\n{response.query_result.fulfillment_text}")

def journaling_page():
    emotion = st.radio("Choose your emotion", options=emotions)
    topic = st.radio("Choose your topic", options=topics)
    if emotion and topic:
        prompt = f"Write about a time when you felt {emotion} about {topic}."
        generated_text = generate_text(prompt)
        st.write("Here are some personalized journaling prompts for you:")
        for line in generated_text.split('\n'):
            st.write(f"- {line}")

def breathing_page():
    exercise_name = st.radio("Choose your breathing exercise", options=list(breathing_exercises.keys()))
    if exercise_name:
        exercise = breathing_exercises[exercise_name]
        st.write(f"You selected the {exercise_name} exercise.")
        for duration in exercise:
            st.write(f"{duration} seconds...")
            time.sleep(duration)
        st.write("Breathing exercise complete!")

# Streamlit app layout
st.title("Flow: Self-Healing, Wellness, and Goal-Setting")
st.write("Welcome to your journey towards self-healing, wellness, and goal achievement.")

page_selection = st.sidebar.selectbox("Choose your page", options=["Welcome", "Journaling", "Breathing Exercises"])

if page_selection == "Welcome":
    welcome_page()
elif page_selection == "Journaling":
    journaling_page()
elif page_selection == "Breathing Exercises":
    breathing_page()