app.py

import openai
import gradio as gr
import os

#OpenAi call
def gpt3(texts):
    openai.api_key = os.environ["Secret"]
    response = openai.Completion.create(
      engine="text-davinci-002",
      prompt= texts,
          temperature=0,
          max_tokens=750,
          top_p=1,
          frequency_penalty=0.0,
          presence_penalty=0.0,
          stop = (";", "/*", "</code>")
    )
    x = response.choices[0].text 
    
    return x

# Function to elicit sql response from model
def greet(prompt):
    food= (f'''Here we will share a best guess for the predominant ingredients in the following food /*Food: {prompt}*/ \n —-Here is a list of the ingredients in the food item:\n''')

    ingred = gpt3(food)

  

    total = (f'''Expert one sentence summary and rating (on a scale of 1/10, with 10 having no impact) of the food and ingredients comparative climate impact, from rationalist climate perspective /*Food, ingredients: {prompt},{ingred}*/ \n —-Impact Summary and Climate Score:\n''')
    score = gpt3(total) 
    return score


#Code to set up Gradio UI
iface = gr.Interface(greet, inputs = ["text"], outputs = ["text"],title="Food Impact Analysis", description="Get a climate analysis back from any food!")
iface.launch()