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import os
import streamlit as st
from dotenv import load_dotenv
import google.generativeai as gen_ai
# Load environment variables
load_dotenv()
# Configure Streamlit page settings
st.set_page_config(
page_title="Health Assistant Chatbot",
page_icon="🩺",
layout="wide",
)
# Custom CSS for styling
st.markdown(
"""
<style>
body, .stApp {
background-color: #E3F2FD;
}
body {
background-color: #ADD8E6;
}
.stTabs [data-baseweb="tab-list"] {
justify-content: center;
}
.stTabs [data-baseweb="tab"] {
background-color: #E3F2FD;
border-radius: 20px;
font-weight: bold;
color: black;
padding: 10px;
}
.stTabs [data-baseweb="tab"][aria-selected="true"] {
background-color: #1E90FF;
color: white;
border-radius: 20px;
}
h2 {
color: #003366;
}
</style>
""",
unsafe_allow_html=True,
)
# Retrieve the Google API key from the environment
GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
if not GOOGLE_API_KEY:
st.error("🚨 API key not found! Please set the GOOGLE_API_KEY in your .env file.")
st.stop()
# Configure the Generative AI model
try:
gen_ai.configure(api_key=GOOGLE_API_KEY)
model = gen_ai.GenerativeModel("gemini-1.5-pro") # Using a model for health-related queries
except Exception as e:
st.error(f"❌ Error initializing the Gemini-Pro model: {e}")
st.stop()
# Initialize the chat session
if "chat_session" not in st.session_state:
try:
st.session_state.chat_session = model.start_chat(history=[])
except Exception as e:
st.error(f"❌ Error initializing chat session: {e}")
st.stop()
# Display chatbot title
st.title("🩺 Health Assistant Chatbot")
# Symptom categories for the user to select
symptom_tabs = ["🤧 Sneezing", "😷 Headache", "🤢 Stomach Ache", "🦠 Fever", "💪 Fatigue"]
selected_symptom_tab = st.tabs(symptom_tabs)
# Sample symptoms and associated treatment information
symptom_treatment = {
"🤧 Sneezing": [
"Possible cause: Allergies or common cold.",
"Treatment recommendation: Try antihistamines for allergies or rest and fluids for a cold."
],
"😷 Headache": [
"Possible cause: Tension, dehydration, or migraines.",
"Treatment recommendation: Drink water, take over-the-counter pain relievers, or rest in a dark room."
],
"🤢 Stomach Ache": [
"Possible cause: Indigestion, food poisoning, or gas.",
"Treatment recommendation: Drink ginger tea, rest, and avoid heavy meals."
],
"🦠 Fever": [
"Possible cause: Infection or viral illness.",
"Treatment recommendation: Take fever reducers like acetaminophen, stay hydrated, and rest."
],
"💪 Fatigue": [
"Possible cause: Stress, sleep deprivation, or illness.",
"Treatment recommendation: Ensure proper sleep, hydrate, and reduce stress."
]
}
# Display symptom recommendations under the selected tab
for i, tab in enumerate(selected_symptom_tab):
with tab:
st.subheader(f"📌 {symptom_tabs[i]} Symptoms")
for recommendation in symptom_treatment[symptom_tabs[i]]:
st.write(f"- {recommendation}")
# Input field for user's symptoms
user_symptom = st.chat_input("💬 Enter your symptom...")
if user_symptom:
# Display the user's symptom
st.chat_message("user").markdown(user_symptom)
# Send symptom message to Gemini-Pro for response
try:
gemini_response = st.session_state.chat_session.send_message(
f"Provide possible causes and treatments for the following symptom: {user_symptom}"
)
# Display AI response
with st.chat_message("assistant"):
st.markdown(gemini_response.text)
except Exception as e:
st.error(f"❌ Error processing your message: {e}")
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