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import streamlit as st
import os
from langchain_groq import ChatGroq
from langchain_core.prompts import ChatPromptTemplate
from dotenv import load_dotenv
# Load environment variables
load_dotenv()
groq_api_key = os.getenv('GROQ_API_KEY')
# Set page title and description
st.title("🥗 Nutrition & Health Food Assistant")
st.markdown("Your personal guide for nutrition advice, dietary recommendations, and healthy eating!")
# Initialize Groq LLM
llm = ChatGroq(
groq_api_key=groq_api_key,
model_name="Llama3-8b-8192"
)
# Create nutrition-specific prompt template
nutrition_prompt = ChatPromptTemplate.from_template(
"""You are a knowledgeable nutritionist and dietary expert specialized in providing advice about:
- Nutritional values and benefits of different foods
- Dietary recommendations for specific health conditions
- Essential vitamins, minerals, and nutrients
- Healthy meal planning and food combinations
- Natural remedies and food-based solutions for common health issues
If the question is not related to nutrition, diet, or food, respond with: 'This chat is trained only for nutrition and dietary guidance.'
User Question: {user_input}
Please provide a detailed, professional response focusing on nutritional and dietary guidance.
When recommending foods, always mention their nutritional benefits and important minerals/vitamins they contain."""
)
# Initialize chat history in session state
if "messages" not in st.session_state:
st.session_state.messages = []
# Display chat history
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])
# Chat input
if prompt := st.chat_input("Ask me about nutrition, healthy foods, or dietary advice!"):
# Add user message to chat history
st.session_state.messages.append({"role": "user", "content": prompt})
with st.chat_message("user"):
st.markdown(prompt)
# Generate response
with st.chat_message("assistant"):
with st.spinner("Analyzing nutritional advice..."):
# Create the full prompt with the user's input
formatted_prompt = nutrition_prompt.format(user_input=prompt)
# Get response from Groq
response = llm.invoke(formatted_prompt)
# Display the response
st.markdown(response.content)
# Add assistant response to chat history
st.session_state.messages.append({"role": "assistant", "content": response.content})
# Add nutritional information categories in the sidebar
with st.sidebar:
st.markdown("""
### 🍎 Nutrition Guidelines
#### Essential Categories:
- **Macronutrients**
- Proteins
- Carbohydrates
- Healthy Fats
- **Micronutrients**
- Vitamins
- Minerals
- Antioxidants
#### Health Conditions:
- Diabetes Management
- Heart Health
- Digestive Issues
- Weight Management
- Food Allergies
- Immune System Support
#### Special Diets:
- Vegetarian/Vegan
- Gluten-Free
- Low-Carb
- Mediterranean
- DASH Diet
Ask specific questions about any of these topics!
""") |