import streamlit as st
import os
from openai import OpenAI
from PIL import Image
import io
import base64

st.set_page_config(
    page_title="Your App",
    layout="wide",
    initial_sidebar_state="expanded"
)

# Custom CSS for better styling
def apply_custom_css():
    st.markdown("""
        <style>
        .stApp {
            max-width: 1200px;
            margin: 0 auto;
        }
        .upload-box {
            border: 2px dashed #4CAF50;
            border-radius: 10px;
            padding: 20px;
            text-align: center;
            background-color: #f8f9fa;
        }
        .sidebar-content {
            padding: 20px;
            background-color: #f1f3f4;
            border-radius: 10px;
        }
        .response-box {
            background-color: #ffffff;
            padding: 20px;
            border-radius: 10px;
            box-shadow: 0 2px 4px rgba(0,0,0,0.1);
        }
        .title-text {
            color: #1E88E5;
            text-align: center;
            font-size: 2.5rem;
            margin-bottom: 2rem;
        }
        </style>
    """, unsafe_allow_html=True)

def initialize_session_state():
    if 'history' not in st.session_state:
        st.session_state.history = []

def encode_image_to_base64(image):
    buffered = io.BytesIO()
    image.save(buffered, format="PNG")
    return base64.b64encode(buffered.getvalue()).decode('utf-8')

def analyze_image(image, question, api_key):
    try:
        client = OpenAI(api_key=api_key)
        base64_image = encode_image_to_base64(image)
        
        completion = client.chat.completions.create(
            model="gpt-4o-mini",
            messages=[
                {
                    "role": "user",
                    "content": [
                        {"type": "text", "text": question},
                        {
                            "type": "image_url",
                            "image_url": {
                                "url": f"data:image/png;base64,{base64_image}"
                            }
                        },
                    ],
                }
            ],
            max_tokens=500
        )
        return completion.choices[0].message.content
    except Exception as e:
        return f"Error: {str(e)}"

def main():
    apply_custom_css()
    initialize_session_state()
    
    # st.set_page_config(
    #     page_title="Smart Image Analyzer",
    #     page_icon="🔍",
    #     layout="wide"
    # )

    # Sidebar Configuration
    with st.sidebar:
        st.markdown('<div class="sidebar-content">', unsafe_allow_html=True)
        st.image("https://your-logo-url.com/logo.png", width=100)  # Add your logo
        st.header("⚙️ Configuration")
        api_key = st.text_input("OpenAI API Key:", type="password")
        
        st.markdown("### 🎯 Quick Prompts")
        quick_prompts = [
            "Suggest receipe based on ingredients"
            "Describe this image in detail",
            "What objects are present?",
            "Analyze the composition",
            "Identify any text in the image",

        ]
        selected_prompt = st.selectbox("Select a prompt:", quick_prompts)
        st.markdown("</div>", unsafe_allow_html=True)

    # Main Content
    st.markdown('<h1 class="title-text">🔍 AI Receipe Generator</h1>', unsafe_allow_html=True)

    # Image Upload Section
    col1, col2, col3 = st.columns([1, 2, 1])
    with col2:
        st.markdown('<div class="upload-box">', unsafe_allow_html=True)
        uploaded_file = st.file_uploader(
            "Drop your image here or click to upload",
            type=['png', 'jpg', 'jpeg'],
            help="Supported formats: PNG, JPG, JPEG"
        )
        st.markdown('</div>', unsafe_allow_html=True)

    if uploaded_file:
        image = Image.open(uploaded_file)
        
        # Image Display and Analysis Section
        col1, col2 = st.columns([1, 1])
        
        with col1:
            st.image(image, use_container_width=True, caption="Uploaded Image")
            
        with col2:
            st.markdown('<div class="response-box">', unsafe_allow_html=True)
            question = st.text_input(
                "Your Question:",
                value=selected_prompt,
                key="question_input"
            )
            
            if st.button("🔍 Analyze", use_container_width=True):
                if not api_key:
                    st.error("⚠️ Please enter your OpenAI API key in the sidebar.")
                else:
                    with st.spinner("🔄 Analyzing your image..."):
                        response = analyze_image(image, question, api_key)
                        st.markdown("### 📝 Analysis Result:")
                        st.write(response)
                        
                        # Add to history
                        st.session_state.history.append({
                            "question": question,
                            "response": response,
                            "timestamp": st.session_state.get("timestamp", "")
                        })
            st.markdown('</div>', unsafe_allow_html=True)

        # History Section
        if st.session_state.history:
            st.markdown("### 📜 Previous Analyses")
            for item in reversed(st.session_state.history[-5:]):
                with st.expander(f"Q: {item['question'][:50]}..."):
                    st.write(item['response'])

    # Footer
    st.markdown("---")
    st.markdown(
        """
        <div style='text-align: center'>
            <p>Built with ❤️ using Streamlit and OpenAI GPT-4 Vision API</p>
            <p>© 2024 Smart Image Analyzer</p>
        </div>
        """,
        unsafe_allow_html=True
    )

if __name__ == "__main__":
    main()