import gradio as gr
import base64
import requests
import io
from PIL import Image
import json
import os
from together import Together
import tempfile
import uuid

def encode_image_to_base64(image_path):
    """Convert image to base64 encoding"""
    with open(image_path, "rb") as image_file:
        return base64.b64encode(image_file.read()).decode('utf-8')

def save_uploaded_image(image):
    """Save uploaded image to a temporary file and return the path"""
    if image is None:
        return None
    
    with tempfile.NamedTemporaryFile(delete=False, suffix='.jpg') as temp_file:
        if isinstance(image, dict) and "path" in image:
            with open(image["path"], "rb") as img_file:
                temp_file.write(img_file.read())
        elif isinstance(image, Image.Image):
            image.save(temp_file.name, format="JPEG")
        else:
            try:
                Image.open(image).save(temp_file.name, format="JPEG")
            except Exception:
                return None
    
    return temp_file.name

def analyze_single_image(client, img_path):
    """Analyze a single image to identify ingredients"""
    system_prompt = """You are a culinary expert AI assistant that specializes in identifying ingredients in images.
    Your task is to analyze the provided image and list all the food ingredients you can identify.
    Be specific and detailed about what you see. Only list ingredients, don't suggest recipes yet."""
    
    user_prompt = "Please identify all the food ingredients visible in this image. List each ingredient on a new line."
    
    try:
        with open(img_path, "rb") as image_file:
            base64_image = base64.b64encode(image_file.read()).decode('utf-8')
            
            content = [
                {"type": "text", "text": user_prompt},
                {
                    "type": "image_url",
                    "image_url": {
                        "url": f"data:image/jpeg;base64,{base64_image}"
                    }
                }
            ]
            
            response = client.chat.completions.create(
                model="meta-llama/Llama-Vision-Free",
                messages=[
                    {"role": "system", "content": system_prompt},
                    {"role": "user", "content": content}
                ],
                max_tokens=500,
                temperature=0.2
            )
            
            return response.choices[0].message.content
    except Exception as e:
        return f"Error analyzing image: {str(e)}"

def get_recipe_suggestions(api_key, images, num_recipes=3, dietary_restrictions="None", cuisine_preference="Any"):
    """Get recipe suggestions based on the uploaded images of ingredients"""
    if not api_key:
        return "Please provide your Together API key."
    
    if not images or len(images) == 0 or all(img is None for img in images):
        return "Please upload at least one image of ingredients."
    
    valid_images = [img for img in images if img is not None]
    
    if len(valid_images) == 0:
        return "No valid images were uploaded. Please try again."
    
    image_paths = []
    for img in valid_images:
        img_path = save_uploaded_image(img)
        if img_path:
            image_paths.append(img_path)
    
    if not image_paths:
        return "Failed to process the uploaded images."
    
    try:
        client = Together(api_key=api_key)
        
        all_ingredients = []
        for img_path in image_paths:
            ingredients_text = analyze_single_image(client, img_path)
            all_ingredients.append(ingredients_text)
        
        combined_ingredients = "\n\n".join([f"Image {i+1} ingredients:\n{ingredients}" 
                                          for i, ingredients in enumerate(all_ingredients)])
        
        system_prompt = """You are a culinary expert AI assistant that specializes in creating recipes based on available ingredients.
        You will be provided with lists of ingredients identified from multiple images. Your task is to suggest creative, 
        detailed recipes that use as many of the identified ingredients as possible.
        
        For each recipe suggestion, include:
        1. Recipe name
        2. Brief description of the dish
        3. Complete ingredients list (including estimated quantities and any additional staple ingredients that might be needed)
        4. Step-by-step cooking instructions
        5. Approximate cooking time
        6. Difficulty level (Easy, Medium, Advanced)
        7. Nutritional highlights
        
        Consider any dietary restrictions and cuisine preferences mentioned by the user."""
        
        user_prompt = f"""Based on the following ingredients identified from multiple images, suggest {num_recipes} creative and delicious recipes.
        
        {combined_ingredients}
        
        Dietary restrictions to consider: {dietary_restrictions}
        Cuisine preference: {cuisine_preference}
        
        Please be creative with your recipe suggestions and try to use ingredients from multiple images if possible."""
        
        response = client.chat.completions.create(
            model="meta-llama/Llama-Vision-Free",
            messages=[
                {"role": "system", "content": system_prompt},
                {"role": "user", "content": user_prompt}
            ],
            max_tokens=2048,
            temperature=0.7
        )
        
        for img_path in image_paths:
            try:
                os.unlink(img_path)
            except:
                pass
        
        result = "## 📋 Ingredients Identified\n\n"
        result += combined_ingredients
        result += "\n\n---\n\n"
        result += "## 🍽️ Recipe Suggestions\n\n"
        result += response.choices[0].message.content
        
        return result
        
    except Exception as e:
        for img_path in image_paths:
            try:
                os.unlink(img_path)
            except:
                pass
        return f"Error: {str(e)}"

custom_css = """
@import url('https://fonts.googleapis.com/css2?family=Poppins:wght@300;400;500;600;700&display=swap');
:root {
    --primary-color: #E67E22;
    --primary-dark: #D35400;
    --secondary-color: #2ECC71;
    --accent-color: #F1C40F;
    --background-color: #FFFFFF;
    --text-color: #4A4A4A;
    --card-background: #F8F9FA;
    --border-radius: 10px;
    --font-family: 'Poppins', sans-serif;
}
body {
    font-family: var(--font-family);
    background-color: var(--background-color);
    color: var(--text-color);
    margin: 0;
    padding: 0;
}
.container {
    max-width: 1200px;
    margin: 0 auto;
    padding: 20px;
}
.app-header {
    background-color: var(--primary-color);
    color: white;
    padding: 40px 20px;
    text-align: center;
    border-radius: 0 0 20px 20px;
    box-shadow: 0 4px 10px rgba(0,0,0,0.1);
}
.app-title {
    font-size: 2.5em;
    margin-bottom: 10px;
    font-weight: 700;
}
.app-subtitle {
    font-size: 1.2em;
    font-weight: 300;
    max-width: 600px;
    margin: 0 auto;
}
.input-section, .output-section {
    background-color: var(--card-background);
    border-radius: var(--border-radius);
    padding: 30px;
    box-shadow: 0 4px 15px rgba(0,0,0,0.05);
    margin-bottom: 30px;
}
.section-header {
    font-size: 1.5em;
    font-weight: 600;
    color: var(--text-color);
    margin-bottom: 20px;
    border-bottom: 2px solid var(--primary-color);
    padding-bottom: 10px;
}
.image-upload-container {
    border: 2px dashed var(--secondary-color);
    border-radius: var(--border-radius);
    padding: 40px;
    text-align: center;
    background-color: rgba(46, 204, 113, 0.05);
    transition: all 0.3s ease;
}
.image-upload-container:hover {
    border-color: var(--primary-color);
    background-color: rgba(230, 126, 34, 0.05);
}
button.primary-button {
    background-color: var(--primary-color);
    color: white;
    border: none;
    padding: 15px 30px;
    border-radius: 5px;
    font-size: 1.1em;
    cursor: pointer;
    transition: all 0.3s ease;
    box-shadow: 0 2px 5px rgba(0,0,0,0.1);
    width: 100%;
}
button.primary-button:hover {
    background-color: var(--primary-dark);
    box-shadow: 0 4px 10px rgba(0,0,0,0.15);
}
.gallery-container {
    display: grid;
    grid-template-columns: repeat(auto-fill, minmax(150px, 1fr));
    gap: 15px;
    margin-top: 20px;
}
.gallery-item {
    border-radius: 8px;
    overflow: hidden;
    box-shadow: 0 2px 5px rgba(0,0,0,0.1);
    transition: transform 0.3s ease;
}
.gallery-item:hover {
    transform: scale(1.05);
}
.recipe-output {
    font-size: 1.1em;
    line-height: 1.6;
    color: var(--text-color);
    max-height: 600px;
    overflow-y: auto;
    padding-right: 10px;
}
.recipe-output h2 {
    color: var(--primary-color);
    margin-top: 30px;
    font-size: 1.8em;
}
.recipe-output h3 {
    color: var(--secondary-color);
    font-size: 1.4em;
    margin-top: 20px;
}
.loading-container {
    display: flex;
    flex-direction: column;
    justify-content: center;
    align-items: center;
    position: fixed;
    top: 0;
    left: 0;
    width: 100%;
    height: 100%;
    background-color: rgba(0, 0, 0, 0.5);
    z-index: 1000;
    opacity: 0;
    visibility: hidden;
    transition: opacity 0.3s ease, visibility 0.3s ease;
}
.loading-container.visible {
    opacity: 1;
    visibility: visible;
}
.loading-spinner {
    border: 8px solid #f3f3f3;
    border-top: 8px solid var(--primary-color);
    border-radius: 50%;
    width: 60px;
    height: 60px;
    animation: spin 1s linear infinite;
}
@keyframes spin {
    0% { transform: rotate(0deg); }
    100% { transform: rotate(360deg); }
}
.loading-text {
    color: white;
    font-size: 1.2em;
    margin-top: 20px;
}
.footer {
    background-color: var(--card-background);
    padding: 40px 20px;
    text-align: center;
    color: var(--text-color);
    font-size: 1em;
    box-shadow: 0 -2px 10px rgba(0,0,0,0.05);
}
.footer-content {
    max-width: 800px;
    margin: 0 auto;
}
.footer-brand {
    font-weight: 700;
    color: var(--primary-color);
}
.footer-links a {
    color: var(--secondary-color);
    text-decoration: none;
    margin: 0 15px;
    transition: color 0.3s ease;
}
.footer-links a:hover {
    color: var(--primary-color);
}
"""

html_header = """
<div class="app-header">
    <div class="app-title">🍲 Visual Recipe Assistant</div>
    <div class="app-subtitle">Upload images of ingredients you have on hand and get personalized recipe suggestions powered by AI</div>
</div>
<div id="loading-overlay" class="loading-container">
    <div class="loading-spinner"></div>
    <div class="loading-text">Generating your recipes...</div>
</div>
<script>
    function showLoading() {
        document.getElementById('loading-overlay').classList.add('visible');
    }
    
    function hideLoading() {
        document.getElementById('loading-overlay').classList.remove('visible');
    }
</script>
"""

html_footer = """
<div class="footer">
    <div class="footer-content">
        <p><span class="footer-brand">🍲 Visual Recipe Assistant</span></p>
        <p>Powered by Meta's Llama-Vision-Free Model & Together AI</p>
        <p>Upload multiple ingredient images for more creative recipe combinations</p>
        <div class="footer-links">
            <a href="#" target="_blank">How It Works</a>
            <a href="#" target="_blank">Privacy Policy</a>
            <a href="#" target="_blank">Contact Us</a>
        </div>
    </div>
</div>
<script>
    document.addEventListener('DOMContentLoaded', function() {
        const submitBtn = document.querySelector('button.primary-button');
        if (submitBtn) {
            submitBtn.addEventListener('click', function() {
                showLoading();
                setTimeout(function() {
                    const output = document.querySelector('.recipe-output');
                    if (output && output.textContent.trim().length > 0) {
                        hideLoading();
                    } else {
                        const checkInterval = setInterval(function() {
                            if (output && output.textContent.trim().length > 0) {
                                hideLoading();
                                clearInterval(checkInterval);
                            }
                        }, 1000);
                        setTimeout(function() {
                            hideLoading();
                            clearInterval(checkInterval);
                        }, 30000);
                    }
                }, 3000);
            });
        }
    });
</script>
"""

with gr.Blocks(css=custom_css) as app:
    gr.HTML(html_header)
    
    with gr.Row():
        with gr.Column(scale=1):
            with gr.Group(elem_classes="input-section"):
                gr.HTML('<h3 class="section-header">API Configuration</h3>')
                api_key_input = gr.Textbox(
                    label="Together API Key", 
                    placeholder="Enter your Together API key here...",
                    type="password",
                    elem_classes="input-group"
                )
                
                gr.HTML('<h3 class="section-header">Upload Ingredients</h3>')
                file_upload = gr.File(
                    label="Upload images of ingredients",
                    file_types=["image"],
                    file_count="multiple",
                    elem_classes="image-upload-container"
                )
                
                image_input = gr.Gallery(
                    label="Uploaded Ingredients", 
                    elem_id="ingredient-gallery",
                    columns=3,
                    rows=2,
                    height="auto",
                    visible=False
                )
                
                gr.HTML('<h3 class="section-header">Recipe Preferences</h3>')
                with gr.Row():
                    num_recipes = gr.Slider(
                        minimum=1, 
                        maximum=5, 
                        value=3, 
                        step=1, 
                        label="Number of Recipe Suggestions",
                        elem_classes="input-group"
                    )
                
                with gr.Row():
                    with gr.Column():
                        dietary_restrictions = gr.Dropdown(
                            choices=["None", "Vegetarian", "Vegan", "Gluten-Free", "Dairy-Free", "Low-Carb", "Keto", "Paleo"],
                            value="None",
                            label="Dietary Restrictions",
                            elem_classes="input-group"
                        )
                        
                    with gr.Column():
                        cuisine_preference = gr.Dropdown(
                            choices=["Any", "Italian", "Asian", "Mexican", "Mediterranean", "Indian", "American", "French", "Middle Eastern"],
                            value="Any",
                            label="Cuisine Preference",
                            elem_classes="input-group"
                        )
                
                submit_button = gr.Button("Get Recipe Suggestions", elem_classes="primary-button")
        
        with gr.Column(scale=1):
            with gr.Group(elem_classes="output-section"):
                gr.HTML('<h3 class="section-header">Your Personalized Recipes</h3>')
                output = gr.Markdown(elem_classes="recipe-output")
    
    gr.HTML(html_footer)
    
    def update_gallery(files):
        if not files:
            return gr.Gallery.update(visible=False)
        return gr.Gallery.update(value=[file.name for file in files], visible=True)
    
    file_upload.change(fn=update_gallery, inputs=file_upload, outputs=image_input)
    
    def process_recipe_request(api_key, files, num_recipes, dietary_restrictions, cuisine_preference):
        if not files:
            return "Please upload at least one image of ingredients."
        images = [file.name for file in files]
        return get_recipe_suggestions(api_key, images, num_recipes, dietary_restrictions, cuisine_preference)
    
    submit_button.click(
        fn=process_recipe_request,
        inputs=[api_key_input, file_upload, num_recipes, dietary_restrictions, cuisine_preference],
        outputs=output
    )

if __name__ == "__main__":
    app.launch()