Create app.py

app.py

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+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()