app.py

import gradio as gr
import json
from pydantic import BaseModel
from pydantic import BaseModel
from openai import OpenAI
from typing import List
import os
API_KEY = os.getenv('api_key')

client = OpenAI(
    api_key=API_KEY
)


# Define the Pydantic models
class Ingredient(BaseModel):
    """An ingredient for a recipe"""
    quantity: str
    unit: str
    name: str

class Steps(BaseModel):
    """Steps to make a recipe"""
    stepNumber: int
    instruction: str


class ProduceRecipe(BaseModel):
    """Makes a recipe for a meal"""
    mealName: str
    ingredients: list[Ingredient]
    steps : list[Steps]


def generate_recipe(meal_name: str, calories: int, meal_time: str) -> ProduceRecipe:
    # This is where you'll implement your recipe generation logic
    # For now, we'll return a dummy recipe

    meal_template = f'''
        "role": "user", "content": "Create a recipe for a {meal_time} of {meal_name} with the following ingredients that is roughly {calories} calories."
        '''
    

    completion = client.beta.chat.completions.parse(
        model="gpt-4o-2024-08-06",
        messages=[
            {"role": "system", "content": "You are an expert chef and nutritionalist. You will be given a meal request and should convert it into a structured Recipe at the correct calories."},
            {"role": "user", "content": meal_template}
        ],
        response_format=ProduceRecipe,
    )


    recipe = completion.choices[0].message.parsed
    return recipe

def format_recipe(recipe: ProduceRecipe) -> str:
    formatted = f"<h2>{recipe.mealName}</h2>\n\n"
    
    formatted += "<h3>Ingredients:</h3>\n<ul>\n"
    for ingredient in recipe.ingredients:
        formatted += f"<li>{ingredient.quantity} {ingredient.unit} {ingredient.name}</li>\n"
    formatted += "</ul>\n\n"
    
    formatted += "<h3>Instructions:</h3>\n<ol>\n"
    for step in recipe.steps:
        formatted += f"<li>{step.instruction}</li>\n"
    formatted += "</ol>"
    
    return formatted

def recipe_interface(meal_name: str, calories: int, meal_time: str) -> str:
    recipe = generate_recipe(meal_name, calories, meal_time)
    return format_recipe(recipe)

demo = gr.Interface(
    fn=recipe_interface,
    inputs=[
        gr.Textbox(label="Meal Name"),
        gr.Number(label="Calories"),
        gr.Dropdown(["breakfast", "lunch", "dinner"], label="Meal Time")
    ],
    outputs=gr.HTML(label="Recipe"),
    title="Meal Recipe Generator",
    description="Generate a recipe based on meal name, calories, and meal time."
)

demo.launch()