add fxn

app.py

@@ -1,39 +1,58 @@
 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]
+    ingredients: list[Ingredient]
+    steps : list[Steps]
+
 
-# This is a placeholder for your actual function
 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
-    dummy_recipe = {
-        "mealName": meal_name,
-        "ingredients": [
-            {"quantity": "2", "unit": "large", "name": "eggs"},
-            {"quantity": "1/4", "unit": "cup", "name": "onion, diced"}
+
+    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}
         ],
-        "steps": [
-            {"stepNumber": 1, "instruction": "Crack the eggs into a bowl."},
-            {"stepNumber": 2, "instruction": "Whisk the eggs and add diced onions."}
-        ]
-    }
-    return ProduceRecipe(**dummy_recipe)
+        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"

requirements.txt

@@ -0,0 +1,2 @@
+openai
+pydantic