Update app.py

app.py

@@ -2,93 +2,101 @@ import streamlit as st
 import pandas as pd
 import joblib
 import matplotlib.pyplot as plt
+from datetime import datetime, timedelta
 from langchain_google_genai import GoogleGenerativeAI
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
 
-# ✅ This must be the first Streamlit command
+# ✅ Streamlit page config (must be first command)
 st.set_page_config(page_title="Interactive Sleep Predictor", layout="wide")
 
-# UI starts here
+# UI Title
 st.title("⏰ Interactive Sleep & Health Predictor")
-st.markdown("Track your sleep & get personalized health tips 💤💪")
+st.markdown("Track your sleep, activity & get personalized health + fitness advice with Gemini 🧠💪")
 
-# Load your trained model
+# Load model
 @st.cache_resource
 def load_model():
-    return joblib.load("log_reg_model.pkl")  # Update with your actual model path
+    return joblib.load("log_reg_model.pkl")  # Update if your model path is different
 
 model = load_model()
 
 # LangChain Setup
 api_key = st.secrets.get('genai_key')
-llm= GoogleGenerativeAI(model="gemini-1.5-pro", google_api_key=api_key)  # or "gpt-4", based on your requirement
+llm = GoogleGenerativeAI(model="gemini-1.5-pro", google_api_key=api_key)
 
-# Health tips prompt template
+# LangChain Prompt Template
 prompt_template = """
-You are a health advisor. Based on the sleep duration (in hours), give personalized sleep and health tips.
-Sleep duration: {sleep_duration} hours.
-Health Tip:
+You are a certified health and fitness advisor.
+
+A user has recorded:
+- Sleep Duration: {sleep_duration} hours
+- Step Count: {step_count} steps
+- Current State: {state} (awake or asleep)
+
+Based on these values:
+1. Give a personalized health and wellness suggestion (max 5 lines).
+2. Give specific exercise tips suitable for their state and activity level (step count).
+3. Mention if their step count is low/average/high and whether they should increase activity.
+
+Start with "👤 Summary for the User:" and then provide your insights.
 """
 
-# LangChain chain for generating health tips
-def generate_health_tips(sleep_duration):
-    prompt = PromptTemplate(input_variables=["sleep_duration"], template=prompt_template)
+# Chain to generate Gemini suggestions
+def generate_personalized_insights(sleep_duration, step_count, state):
+    prompt = PromptTemplate(
+        input_variables=["sleep_duration", "step_count", "state"],
+        template=prompt_template
+    )
     chain = LLMChain(llm=llm, prompt=prompt)
-    return chain.run({"sleep_duration": sleep_duration})
+    return chain.run({
+        "sleep_duration": sleep_duration,
+        "step_count": step_count,
+        "state": state
+    })
 
-# User input form
+# User form
 with st.form("predictor_form"):
-    step = st.number_input("🚶 **Step Count** (Enter your current steps)", min_value=0, step=10, label_visibility="visible")
-    hour = st.slider("⏰ **Hour of the Day** (24h format)", min_value=0, max_value=23, label_visibility="visible")
-    submit_button = st.form_submit_button("Predict Sleep/Wake State")
+    step = st.number_input("🚶 Step Count (today)", min_value=0, step=10)
+    hour = st.slider("⏰ Hour of the Day", min_value=0, max_value=23)
 
-# When the user clicks the predict button
-if submit_button:
-    # Prepare input for the model
-    input_df = pd.DataFrame([[step, hour]], columns=["step", "hour"])
+    col1, col2 = st.columns(2)
+    with col1:
+        sleep_time = st.time_input("🌙 Sleep Onset Time")
+    with col2:
+        wake_time = st.time_input("🌞 Wake-Up Time")
+
+    submit_button = st.form_submit_button("Predict & Get Gemini Tips")
 
+# On Submit
+if submit_button:
     # Predict sleep state (0 = awake, 1 = asleep)
+    input_df = pd.DataFrame([[step, hour]], columns=["step", "hour"])
     prediction = model.predict(input_df)[0]
+    state = "asleep" if prediction == 1 else "awake"
+    emoji = "😴" if state == "asleep" else "🌞"
+
+    # Sleep duration calculation
+    today = datetime.today()
+    sleep_dt = datetime.combine(today, sleep_time)
+    wake_dt = datetime.combine(today, wake_time)
+    if wake_dt < sleep_dt:
+        wake_dt += timedelta(days=1)
 
-    # Calculate sleep duration (use 8 hours if asleep, 0 if awake)
-    sleep_duration = 8 if prediction == 1 else 0
+    sleep_duration = round((wake_dt - sleep_dt).seconds / 3600, 2)
 
     # Display prediction
-    if prediction == 1:
-        st.success(f"😴 **You are likely asleep**. You might sleep for **{sleep_duration} hours**.")
-    else:
-        st.info(f"🌞 **You are likely awake**. Stay active and hydrated today!")
-
-    # Generate and display health tips based on sleep duration
-    health_tips = generate_health_tips(sleep_duration)
-    st.markdown("### Health Tips:")
-    st.write(f"**{health_tips}**")
-
-    # Exercise Tips based on the user's state (asleep vs awake)
-    if prediction == 0:  # Awake
-        exercise_tips = """
-        - 🏃‍♂️ **Go for a walk or jog**: 20-30 minutes of aerobic exercise can boost your energy.
-        - ���‍♀️ **Stretch or do yoga**: Focus on flexibility and relaxation to stay active.
-        - 🏋️‍♂️ **Strength Training**: Include bodyweight exercises like squats and push-ups.
-        """
-    else:  # Asleep
-        exercise_tips = "Rest is the best exercise. Ensure you are getting quality sleep for good health."
-
-    st.markdown("### Exercise Suggestions:")
-    st.write(f"**{exercise_tips}**")
-
-    # Visual representation: Sleep Prediction Bar Chart
-    fig, ax = plt.subplots(figsize=(8, 4))
-    ax.barh(["Predicted Sleep"], sleep_duration, color="lightblue")
-    ax.set_xlim(0, 10)  # Limit max sleep time
-    ax.set_xlabel("Hours of Sleep")
-    ax.set_title("Predicted Sleep Duration")
-    st.pyplot(fig)
+    st.success(f"{emoji} **You're likely {state}**. You've logged **{sleep_duration} hours** of sleep and taken **{step} steps** today.")
 
-# # Footer for the app
-# st.markdown("---")
-# st.markdown("""
-#     Built with ❤️ by **Pavan Manikanta Muthyala** | **Interactive Sleep Predictor** using LangChain and GenAI
-# """)
+    # LangChain Gemini Suggestions
+    insights = generate_personalized_insights(sleep_duration, step, state)
+    st.markdown("### 🧠 Gemini-Generated Tips:")
+    st.markdown(insights)
 
+    # Sleep Visualization
+    fig, ax = plt.subplots(figsize=(8, 4))
+    ax.barh(["Your Sleep Duration"], sleep_duration, color="skyblue")
+    ax.set_xlim(0, 10)
+    ax.set_xlabel("Hours")
+    ax.set_title("Logged Sleep Duration")
+    st.pyplot(fig)