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# app.py
import streamlit as st
from groq import Groq
import time
import os
import re
# Page Configuration
st.set_page_config(
page_title="HealthAI Advisor",
page_icon="πΏ",
layout="centered",
initial_sidebar_state="expanded"
)
# Initialize Groq client
with st.sidebar:
# API key input for Groq
st.session_state["GROQ_API_KEY"] = st.text_input("GROQ API Key", type="password")
st.sidebar.markdown("π [Get Groq API Key](https://console.groq.com/keys)")
# Initialize Groq client
if st.session_state["GROQ_API_KEY"]:
client = Groq(api_key=st.session_state["GROQ_API_KEY"])
else :
client = Groq(api_key=os.environ.get("GROQ_API_KEY", st.secrets.get("GROQ_API_KEY", "sk-your-key")))
# Custom CSS
st.markdown("""
<style>
/* Base styles */
.recommendation-box {
padding: 1.5rem;
border-radius: 10px;
margin-top: 1rem;
background-color: var(--background-color);
border: 1px solid var(--secondary-background-color);
color: var(--text-color);
}
/* Theme-aware text colors */
.st-emotion-cache-10trblm {
color: var(--text-color) !important;
}
/* Progress bar styling */
.st-emotion-cache-1ii7l3v {
background-color: var(--secondary-background-color) !important;
}
.st-emotion-cache-keje6w {
background-color: var(--primary-color) !important;
}
</style>
""", unsafe_allow_html=True)
# Helper Functions
def get_groq_response(prompt, model="llama-3.3-70b-versatile"):
try:
response = client.chat.completions.create(
messages=[{"role": "user", "content": prompt}],
model=model,
temperature=0.3,
)
return response.choices[0].message.content
except Exception as e:
return f"Error: {str(e)}"
def calculate_bmi(weight, height):
return weight / ((height / 100) ** 2)
# Main App
def main():
st.sidebar.title("π± Navigation")
page = st.sidebar.radio("Choose Section",
["π Dashboard", "π Diet Planner", "πͺ Workout Generator", "π§ Yoga Advisor", "π€ AI Coach"])
# Dashboard
if page == "π Dashboard":
st.header("π HealthAI Dashboard")
st.divider()
with st.container():
col1, col2 = st.columns(2)
with col1:
st.subheader("Body Metrics")
weight = st.number_input("Weight (kg)", min_value=30.0, max_value=200.0, value=65.0)
height = st.number_input("Height (cm)", min_value=100.0, max_value=250.0, value=170.0)
if st.button("Calculate BMI"):
bmi = calculate_bmi(weight, height)
st.metric("BMI", f"{bmi:.1f}")
# Calculate progress value (0-1 scale)
progress_value = min(max((bmi - 15)/(40 - 15), 0), 1)
# Create a layout for the progress bar with label
col_a, col_b = st.columns([4, 1])
with col_a:
st.progress(progress_value)
with col_b:
st.caption("15 β· 40")
with col2:
st.subheader("Daily Goals")
st.metric("Water Intake", "2.4L", "+0.6L remaining")
st.metric("Steps", "8,432", "12k goal")
st.metric("Active Minutes", "45", "60min target")
st.divider()
st.subheader("Weekly Progress")
col1, col2, col3 = st.columns(3)
col1.metric("Calories Burned", "12,430", "1,234 today")
col2.metric("Exercise Minutes", "324", "45 today")
col3.metric("Sleep Average", "7.2h", "-0.8h from goal")
# Diet Planner
elif page == "π Diet Planner":
st.header("π AI Nutritionist")
st.divider()
with st.form("diet_form"):
col1, col2 = st.columns(2)
with col1:
diet_goal = st.selectbox("Primary Goal",
["Weight Loss", "Muscle Gain", "Maintenance", "Improve Digestion"])
allergies = st.multiselect("Allergies/Dietary Restrictions",
["Dairy", "Gluten", "Nuts", "Eggs", "Vegetarian", "Vegan"])
with col2:
calorie_target = st.slider("Daily Calorie Target", 1200, 3000, 2000)
preferred_cuisine = st.selectbox("Preferred Cuisine",
["Any", "Mediterranean", "Asian", "Mexican", "Continental"])
if st.form_submit_button("π³ Generate Meal Plan"):
with st.spinner("Cooking up your personalized plan..."):
prompt = f"""Create a {diet_goal} meal plan for {calorie_target} calories,
considering {allergies} restrictions and {preferred_cuisine} cuisine preference.
Include breakfast, lunch, dinner, and snacks with macros with attractive emogies and attractive format"""
response = get_groq_response(prompt)
st.subheader("π½οΈ Your Personalized Meal Plan")
# st.markdown(f'<div class="recommendation-box">\n\n{response}</div>', unsafe_allow_html=True)
think_match = re.search(r'<think>(.*?)</think>', response, re.DOTALL)
if think_match:
think_text = think_match.group(1).strip()
# Remove the <think>...</think> part from the original response
response_without_think = re.sub(r'<think>.*?</think>', '', response, flags=re.DOTALL).strip()
else:
think_text = ""
response_without_think = response
# Print the think part using a Streamlit expander if it exists
if think_text:
with st.expander("Internal Thoughts"):
st.write(think_text)
# Print the remaining response using st.markdown
st.markdown(f'<div class="recommendation-box">\n\n{response_without_think}</div>', unsafe_allow_html=True)
# Workout Generator
elif page == "πͺ Workout Generator":
st.header("πͺ AI Fitness Coach")
st.divider()
with st.form("workout_form"):
col1, col2 = st.columns(2)
with col1:
fitness_level = st.selectbox("Fitness Level",
["Beginner", "Intermediate", "Advanced"])
workout_type = st.selectbox("Workout Type",
["Full Body", "Upper Body", "Lower Body", "Cardio", "HIIT"])
with col2:
equipment = st.multiselect("Available Equipment",
["Dumbbells", "Resistance Bands", "None", "Barbell", "Kettlebells"])
duration = st.slider("Duration (minutes)", 15, 120, 45)
if st.form_submit_button("ποΈ Generate Workout"):
with st.spinner("Building your workout routine..."):
prompt = f"""Create a {duration}-minute {workout_type} workout for a {fitness_level}
using {equipment}. Include warm-up, exercises with sets/reps, and cool-down with attractive emogies and attractive format"""
response = get_groq_response(prompt)
st.subheader("π Your Custom Workout Plan")
# st.markdown(f'<div class="recommendation-box">\n\n{response}</div>', unsafe_allow_html=True)
think_match = re.search(r'<think>(.*?)</think>', response, re.DOTALL)
if think_match:
think_text = think_match.group(1).strip()
# Remove the <think>...</think> part from the original response
response_without_think = re.sub(r'<think>.*?</think>', '', response, flags=re.DOTALL).strip()
else:
think_text = ""
response_without_think = response
# Print the think part using a Streamlit expander if it exists
if think_text:
with st.expander("Internal Thoughts"):
st.write(think_text)
# Print the remaining response using st.markdown
st.markdown(f'<div class="recommendation-box">\n\n{response_without_think}</div>', unsafe_allow_html=True)
# Yoga Advisor
elif page == "π§ Yoga Advisor":
st.header("π§ AI Yoga Guide")
st.divider()
with st.form("yoga_form"):
col1, col2 = st.columns(2)
with col1:
yoga_goal = st.selectbox("Session Focus",
["Stress Relief", "Flexibility", "Strength", "Balance", "Morning Energy"])
experience_level = st.selectbox("Experience Level",
["Beginner", "Intermediate", "Advanced"])
with col2:
duration = st.slider("Session Duration (minutes)", 10, 90, 30)
intensity = st.select_slider("Intensity",
options=["Gentle", "Moderate", "Vigorous"])
if st.form_submit_button("π§ Generate Yoga Routine"):
with st.spinner("Creating your zen session..."):
prompt = f"""Create a {duration}-minute {yoga_goal} yoga routine for {experience_level}
practitioners with {intensity} intensity. Include warm-up, sequence of poses,
and final relaxation with attractive emogies and attractive format"""
response = get_groq_response(prompt)
st.subheader("πΈ Your Yoga Sequence")
# st.markdown(f'<div class="recommendation-box">\n\n{response}</div>', unsafe_allow_html=True)
think_match = re.search(r'<think>(.*?)</think>', response, re.DOTALL)
if think_match:
think_text = think_match.group(1).strip()
# Remove the <think>...</think> part from the original response
response_without_think = re.sub(r'<think>.*?</think>', '', response, flags=re.DOTALL).strip()
else:
think_text = ""
response_without_think = response
# Print the think part using a Streamlit expander if it exists
if think_text:
with st.expander("Internal Thoughts"):
st.write(think_text)
# Print the remaining response using st.markdown
st.markdown(f'<div class="recommendation-box">\n\n{response_without_think}</div>', unsafe_allow_html=True)
# AI Coach
elif page == "π€ AI Coach":
st.markdown('<p class="header-text">AI Wellness Coach</p>', unsafe_allow_html=True)
st.header("π€ AI Wellness Coach")
st.divider()
if "messages" not in st.session_state:
st.session_state.messages = []
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])
if prompt := st.chat_input("Ask about health, nutrition, or fitness..."):
st.session_state.messages.append({"role": "user", "content": prompt})
with st.chat_message("user"):
st.markdown(prompt)
with st.chat_message("assistant"):
with st.spinner("Analyzing..."):
response = get_groq_response(prompt)
# st.session_state.messages.append({"role": "assistant", "content": response})
# Extract the internal "think" part from the response
think_match = re.search(r'<think>(.*?)</think>', response, re.DOTALL)
if think_match:
think_text = think_match.group(1).strip()
# Remove the <think>...</think> part from the response
response_without_think = re.sub(r'<think>.*?</think>', '', response, flags=re.DOTALL).strip()
else:
think_text = ""
response_without_think = response
# Display the internal thoughts (if any) inside an expander
if think_text:
with st.expander("Internal Thoughts"):
st.write(think_text)
# Display the remaining response in the recommendation box
st.markdown(f'<div class="recommendation-box">\n\n{response_without_think}</div>', unsafe_allow_html=True)
if __name__ == "__main__":
main()
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