app.py

import gradio as gr
import openai
import os
from dotenv import load_dotenv
import logging

# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Load environment variables
load_dotenv()

# Configure OpenAI
openai.api_key = os.getenv("OPENAI_API_KEY")
if not openai.api_key:
    raise ValueError("OPENAI_API_KEY environment variable is not set")

def generate_recipe(query, diet_preference=None, cuisine_type=None):
    """Generate a recipe with optional diet and cuisine preferences"""
    logger.info(f"Generating recipe for query: {query}, diet: {diet_preference}, cuisine: {cuisine_type}")
    
    if not query:
        raise ValueError("Recipe query is required")

    # Create a detailed prompt for the recipe
    prompt = f"""Create a detailed recipe for {query}"""
    if diet_preference:
        prompt += f" that is {diet_preference}"
    if cuisine_type:
        prompt += f" in {cuisine_type} style"
    
    prompt += """\n\nFormat the recipe in markdown with the following sections:
    1. Brief Description
    2. Ingredients (as a bulleted list)
    3. Instructions (as numbered steps)
    4. Tips (as a bulleted list)
    5. Nutritional Information (as a bulleted list)
    
    Use markdown formatting like:
    - Headers (###)
    - Bold text (**)
    - Lists (- and 1.)
    - Sections (>)
    """

    try:
        # Generate recipe text
        completion = openai.chat.completions.create(
            model="gpt-3.5-turbo",
            messages=[
                {"role": "system", "content": "You are a professional chef who provides detailed recipes with ingredients, instructions, nutritional information, and cooking tips. Format your responses in markdown."},
                {"role": "user", "content": prompt}
            ],
            temperature=0.7
        )
        recipe_text = completion.choices[0].message.content

        # Generate recipe image
        image_response = openai.images.generate(
            model="dall-e-3",
            prompt=f"Professional food photography of {query}, appetizing, high-quality, restaurant style",
            n=1,
            size="1024x1024"
        )
        image_url = image_response.data[0].url

        # Get learning resources (simplified version)
        learning_resources = [
            {
                "title": f"Master the Art of {query}",
                "url": f"https://cooking-school.example.com/learn/{query.lower().replace(' ', '-')}",
                "type": "video"
            },
            {
                "title": f"Tips and Tricks for Perfect {query}",
                "url": f"https://recipes.example.com/tips/{query.lower().replace(' ', '-')}",
                "type": "article"
            }
        ]

        return recipe_text, image_url, learning_resources

    except Exception as e:
        logger.error(f"Error generating recipe: {str(e)}")
        raise

def format_learning_resources(resources):
    """Format learning resources as a markdown list"""
    if not resources:
        return "No learning resources available."
    
    return "\n".join([f"- **{r['title']}** ({r['type']}): {r['url']}" for r in resources])

def recipe_generation_app():
    """Create Gradio interface for recipe generation"""
    # Inputs
    recipe_input = gr.Textbox(label="Recipe Query", placeholder="Enter a recipe name (e.g., chocolate chip cookies)")
    diet_input = gr.Dropdown(
        label="Diet Preference", 
        choices=["None", "Vegetarian", "Vegan", "Gluten-Free", "Keto"],
        value="None"
    )
    cuisine_input = gr.Dropdown(
        label="Cuisine Type", 
        choices=["None", "Italian", "Mexican", "Chinese", "Indian", "French"],
        value="None"
    )

    # Outputs
    recipe_output = gr.Markdown(label="Generated Recipe")
    image_output = gr.Image(label="Recipe Image")
    resources_output = gr.Markdown(label="Learning Resources")

    # Define the app interface
    demo = gr.Interface(
        fn=lambda query, diet, cuisine: (
            *generate_recipe(
                query, 
                diet if diet != "None" else None, 
                cuisine if cuisine != "None" else None
            )[:2],
            format_learning_resources(generate_recipe(
                query, 
                diet if diet != "None" else None, 
                cuisine if cuisine != "None" else None
            )[2])
        ),
        inputs=[recipe_input, diet_input, cuisine_input],
        outputs=[recipe_output, image_output, resources_output],
        title="🍳 AI Recipe Assistant",
        description="Generate delicious recipes with AI-powered suggestions!"
    )

    return demo

# Launch the Gradio app
if __name__ == "__main__":
    app = recipe_generation_app()
    app.launch(share=True)