# 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
user_direction = st.text_area(
    "Let's get cooking! What do you feel like making?",
    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.",
        "gpt_instruction": "a quick and easy recipe with simple/straightfoward ingredients and instructions."
    }
    "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.",
        "gpt_instruction": "intermediate recipe with some intricate ingredients and instructional steps."
    }
    "Professional": {
        "description": "Complex recipes that demand a high level of skill and precision. Suited for seasoned cooks aspiring to professional-level sophistication and creativity.",
        "gpt_instruction": "restaurant quality dish that is innovative and even experimental. may use a variety of ingredients and techniques."
    }
}

selected_difficulty = st.radio(
    "Choose a difficulty level for your recipe.",
    [
        difficulty_dictionary[0], 
        difficulty_dictionary[1], 
        difficulty_dictionary[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",
    )

user_inputs = {
    "user_direction" : user_direction,
    "exclusions": exclusions,
    "serving_size": serving_size,
    "difficulty": difficulty_dictionary['selected_difficulty']['gpt_instruction']
}

    
def generate_recipe(user_inputs):
    with st.spinner('Building the perfect recipe for you...'):
        context = """Provide me a recipe based on the user input.
        Output this in a valid JSON object with the following properties:
        recipe_name (string): the name of the recipe
        recipe_serving_size (string): the serving size of the recipe (example: "4 people")
        recipe_time (string): the amount of time required to make the recipe (example: "60 minutes (Preparation: 20 minutes, Baking: 40 minutes)")
        recipe_ingredients (string): python list of ingredients required to make the recipe
        recipe_instructions (string): python list of instructions to make the recipe
        """
        messages = [
            {"role": "system", "content": context},
            {"role": "user", "content": str(user_inputs)}
            ]
        
        st.session_state.gpt_response = openai.ChatCompletion.create(
            model="gpt-3.5-turbo",
            messages=messages,
            temperature=0.5
        )


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']['content'])
    st.header(loaded_recipe['recipe_name'])
    st.write(f"**Serving Size: {loaded_recipe['recipe_serving_size']}**")
    st.write(f"**Time To Make: {loaded_recipe['recipe_time']}**")
    st.subheader("Ingredients:")
    md_ingredients = ''
    for ingredient in loaded_recipe['recipe_ingredients']:
        md_ingredients += "- " + ingredient + "\n"
    st.markdown(md_ingredients)
    st.subheader("Instructions:")
    md_instructions = ''
    for instruction in loaded_recipe['recipe_instructions']:
        md_instructions += "- " + instruction + "\n"
    st.markdown(md_instructions)