app.py

import streamlit as st
import openai
from googletrans import Translator
# Set up OpenAI API credentials
openai.api_key = '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'

def translate_text(text, target_language):
    translator = Translator()
    translation = translator.translate(text, dest=target_language)
    return translation.text

def get_food_recommendation(prompt):
    # Generate a response using the ChatGPT API
    response = openai.Completion.create(
        engine='text-davinci-003',
        prompt=prompt,
        max_tokens=500,
        n=1,
        stop=None,
        temperature=0.7
    )

    # Extract the recommended food from the API response
    recommendation = response.choices[0].text.strip()

    return recommendation

def korean_text():
    st.title("식품 및 영양 권장 시스템")
    st.write("식품 및 영양 권장 시스템에 오신 것을 환영합니다")
    st.markdown("웹페이지에서 도움이 될 수 있는 몇 가지 예시입니다:")
    st.markdown("- 200칼로리 음식 한국어")
    st.markdown("- 소고기 볶음밥 레시피")
    st.markdown("- 쌀 새우 스파이스 레시피")
    st.markdown("- 당뇨병에 좋은 음식 한국어")


def eng_func():
    st.title("Food and Nutrition Recommendation System")
    st.write("Welcome to Food and Nutrition Recommendation System")
    st.markdown('''The following are some examples that the webpage can help with :
    
    - 200-calorie foods Korean    
    - recipe for beef fried rice    
    - rice shrimp spices recipe   
    - foods for diabetes Korean''')

# Streamlit app
def main():
    target_language = "ko"  # Set the target language to Korean

    col1, col2 = st.columns(2)

    with col1:
        eng_func()

    with col2:
        korean_text()

    prompt = st.text_area("Enter your request for food recommendation/ 음식 추천 요청을 입력하세요 ")

    if st.button("Get Recommendation/추천 받기"):
        if prompt:
            recommendation_prompt = f"I'm looking for a food recommendation with the complete ingredients list based on the following criteria: {prompt}"
            recommendation = get_food_recommendation(recommendation_prompt)
            translated_recommendation = translate_text(recommendation, target_language)

            st.markdown("Recommendation (English / Korean):")
            col3, col4 = st.columns(2)

            with col3:
                st.write(recommendation)

            with col4:
                st.write(translated_recommendation)
        else:
            st.warning("Please enter your request.")

if __name__ == "__main__":
    main()