# imports import streamlit as st import numpy as np import pandas as pd import re import json import openai openai.api_key = st.secrets["open_ai_key"] # state management if 'gpt_response' not in st.session_state: st.session_state.gpt_response = None # app st.title("Let's get cooking") user_direction = st.text_area( "What do you want to cook? Describe anything - a dish, cuisine, event, or vibe.", placeholder="quick snack, asian style bowl with either noodles or rice, something italian", ) serving_size = st.number_input( "How many people are you cooking for?", min_value=1, max_value=100, value=2, step=1 ) difficulty_dictionary = { "Quick & Easy": { "description": "Easy recipes with straightforward instructions. Ideal for beginners or those seeking quick and simple cooking.", }, "Intermediate": { "description": "Recipes with some intricate steps that invite a little challenge. Perfect for regular cooks wanting to expand their repertoire with new ingredients and techniques.", }, "Professional": { "description": "Complex recipes that demand a high level of skill and precision. Suited for seasoned cooks aspiring to professional-level sophistication and creativity.", } } selected_difficulty = st.radio( "Choose a difficulty level for your recipe.", [ list(difficulty_dictionary.keys())[0], list(difficulty_dictionary.keys())[1], list(difficulty_dictionary.keys())[2] ], captions = [ difficulty_dictionary["Quick & Easy"]["description"], difficulty_dictionary["Intermediate"]["description"], difficulty_dictionary["Professional"]["description"] ] ) exclusions = st.text_area( "Any ingredients you want to exclude?", placeholder="gluten, dairy, nuts, cilantro", ) fancy_exclusions ="" if selected_difficulty == "Professional": exclude_fancy = st.checkbox( "Exclude cliche professional ingredients? (gold leaf, truffle, edible flowers, microgreens)", value=True) fancy_exclusions = "gold leaf, truffle, edible flowers, microgreens" user_inputs = { "user_direction" : user_direction, "exclusions": f"{exclusions}, {fancy_exclusions}", "serving_size": serving_size, "difficulty": selected_difficulty } def create_detailed_prompt(user_direction, exclusions, serving_size, difficulty): if difficulty == "Quick & Easy": prompt = ( f"Please provide a 'Quick and Easy' recipe for {user_direction} with a serving size of {serving_size}. " f"It should require as few ingredients as possible and should be ready as little time as possible. " f"The steps should be simple, and the ingredients should be commonly found in a household pantry. " f"Ensure to exclude {exclusions} from the recipe." ) elif difficulty == "Intermediate": prompt = ( f"I'm looking for a recipe for a classic {user_direction} with a serving size of {serving_size} that offers a bit of a cooking challenge " f"but doesn't require professional skills.The recipe should feature traditional ingredients and techniques that are authentic to its cuisine. " f"Please provide a step-by-step guide that explains the process in detail. " f"Ensure to exclude {exclusions} from the recipe." ) elif difficulty == "Professional": prompt = ( f"Create an advanced recipe for {user_direction} with a serving size of {serving_size} that pushes the boundaries of culinary arts." f"This recipe should integrate unique ingredients, advanced cooking techniques, and innovative presentations." f"I'm aiming for a dish that could be served at a high-end restaurant or would impress at a gourmet food competition." f"Please detail the preparation and cooking process, considering that complexity and creativity are more important than prep and cooking time. " f"Ensure to exclude {exclusions} from the recipe." ) return prompt def generate_recipe(user_inputs): with st.spinner('Building the perfect recipe for you...'): functions = [ { "name": "provide_recipe", "description": "Provides a detailed recipe strictly adhering to the user input/specifications, especially ingredient exclusions and the recipe difficulty", "parameters": { "type": "object", "properties": { "name": { "type": "string", "description": "A creative name for the recipe" }, "description": { "type": "string", "description": "a brief one-sentence description of the provided recipe" }, "ingredients": { "type": "array", "items": { "type": "object", "properties": { "name": { "type": "string", "description": "Name of the ingredient" } } } }, "instructions": { "type": "array", "items": { "type": "object", "properties": { "step_number": { "type": "number", "description": "The sequence number of this step" }, "instruction": { "type": "string", "description": "Detailed description of what to do in this step" } } } } }, "required": [ "name", "description", "ingredients", "instructions" ], }, } ] prompt = create_detailed_prompt(user_inputs['user_direction'], user_inputs['exclusions'], user_inputs['serving_size'], user_inputs['difficulty']) messages = [{"role": "user", "content": prompt}] st.session_state.gpt_response = openai.ChatCompletion.create( model="gpt-4", messages=messages, temperature=0.75, top_p=0.75, functions=functions, function_call={"name":"provide_recipe"}, # auto is default, but we'll be explicit ) st.button(label='Submit', on_click=generate_recipe, kwargs=dict(user_inputs=user_inputs)) if st.session_state.gpt_response is not None: st.divider() loaded_recipe = json.loads(st.session_state.gpt_response['choices'][0]['message']["function_call"]["arguments"]) st.header(loaded_recipe['name']) # st.write(f"**Serving Size: {loaded_recipe['recipe_serving_size']}**") st.write(f"**Description:** {loaded_recipe['description']}") st.subheader("Ingredients:") try: md_ingredients = '' for ingredient in loaded_recipe['ingredients']: md_ingredients += f"- {ingredient['name']} \n" st.markdown(md_ingredients) except: st.write(loaded_recipe['ingredients']) st.subheader("Instructions:") try: md_instructions = '' for instruction in loaded_recipe['instructions']: md_instructions += f"{instruction['step_number']}. {instruction['instruction']} \n" st.markdown(md_instructions) except: st.write(loaded_recipe['instructions'])