app.py

import streamlit as st
from PIL import Image
from phi.agent import Agent
from phi.model.google import Gemini
from phi.tools.firecrawl import FirecrawlTools
import google.generativeai as genai
import io
from dotenv import load_dotenv
import os

# Load environment variables
load_dotenv()

# Configure Gemini
API_KEY = os.getenv("GOOGLE_API_KEY")
if API_KEY:
    genai.configure(api_key=API_KEY)

# Page Configuration with custom CSS
st.set_page_config(
    page_title="AI Shopping Partner",
    page_icon="🛍️",
    layout="wide"
)

# Custom CSS
st.markdown("""
    <style>
    .main {
        padding: 2rem;
    }
    .stTitle {
        color: #1E88E5;
        font-family: 'Helvetica Neue', sans-serif;
    }
    .stHeader {
        color: #333;
        font-family: 'Helvetica Neue', sans-serif;
    }
    .upload-section {
        background-color: #f8f9fa;
        padding: 2rem;
        border-radius: 10px;
        box-shadow: 0 2px 4px rgba(0,0,0,0.1);
    }
    .results-section {
        background-color: white;
        padding: 2rem;
        border-radius: 10px;
        box-shadow: 0 2px 4px rgba(0,0,0,0.1);
        margin-top: 2rem;
    }
    .stTextInput input {
        border-radius: 5px;
    }
    .stButton button {
        border-radius: 5px;
        background-color: #1E88E5;
        color: white;
        font-weight: bold;
    }
    .stTextArea textarea {
        border-radius: 5px;
        height: 100px;
    }
    </style>
""", unsafe_allow_html=True)

# App Header
col1, col2, col3 = st.columns([1,2,1])
with col2:
    st.title("🛍️ AI Shopping Partner")
    st.markdown("##### Powered by Agno and Google Gemini")

def get_gemini_response(api_key, prompt, image):   
    model = genai.GenerativeModel(model_name="gemini-2.0-flash-exp")
    response = model.generate_content([prompt, image])
    return response.text

def initialize_agent():
    return Agent(
        name="Shopping Partner",
        model=Gemini(id="gemini-2.0-flash-exp"),  
        instructions=[
            "You are a product recommender agent specializing in finding products that match user preferences.",
            "Prioritize finding products that satisfy as many user requirements as possible, but ensure a minimum match of 50%.",
            "Search for products only from authentic and trusted e-commerce websites.",
            "Verify that each product recommendation is in stock and available for purchase.",
            "Avoid suggesting counterfeit or unverified products.",
            "Format recommendations in a clean, organized manner with clear product attributes.",
        ],
        tools=[FirecrawlTools()],
        markdown=True
    )

# Initialize the Agent
multimodal_Agent = initialize_agent()

# Main content area
st.markdown('<div class="upload-section">', unsafe_allow_html=True)

# File Upload Section
uploaded_file = st.file_uploader(
    "Upload a product image to analyze",
    type=["jpg", "jpeg", "png"],
    help="Maximum file size: 200MB"
)

if uploaded_file:
    image = Image.open(uploaded_file)
    
    # Display image and initial analysis
    col1, col2 = st.columns([1, 2])
    with col1:
        st.image(image, caption="Uploaded Image", use_container_width=True)
    with col2:
        with st.spinner("Analyzing image..."):
            initial_response = get_gemini_response(API_KEY, "What is in this photo?", image)
            st.info(f"**Product Identified:** {initial_response}")

    # Preference Collection
    st.markdown("### Your Preferences")
    col1, col2, col3 = st.columns(3)
    with col1:
        color_pref = st.text_input("🎨 Desired Color", placeholder="e.g., Navy Blue")
    with col2:
        purpose = st.text_input("🎯 Intended Purpose", placeholder="e.g., Casual wear")
    with col3:
        budget = st.text_input("💰 Budget Range", placeholder="e.g., Under $100")

    specific_requirements = st.text_area(
        "✨ Additional Requirements",
        placeholder="Any specific features or requirements you're looking for?"
    )

    if st.button("🔍 Find Similar Products", type="primary"):
        if not specific_requirements:
            st.warning("Please specify your requirements to get better recommendations.")
        else:
            st.markdown('<div class="results-section">', unsafe_allow_html=True)
            with st.spinner("Searching for perfect matches..."):
                analysis_prompt = f"""
                I am looking for {initial_response}
                with the following preferences:
                Color: {color_pref}
                Purpose: {purpose}
                Budget: {budget}
                Additional Requirements: {specific_requirements}
                Please provide recommendations with direct product links.
                """
                
                response = multimodal_Agent.run(analysis_prompt, image=image)
                
                st.markdown("### 🌟 Recommended Products")
                st.markdown(response.content)
            st.markdown('</div>', unsafe_allow_html=True)

st.markdown('</div>', unsafe_allow_html=True)

# Footer
st.markdown("---")
st.markdown(
    """
    <div style='text-align: center; color: #666;'>
        <p>Made with ❤️ by AI Shopping Partner</p>
    </div>
    """, 
    unsafe_allow_html=True
)