app.py

import os
import openai
import streamlit as st
from dotenv import load_dotenv
import boto3
import base64
import datetime
import json

load_dotenv()
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
client = openai.OpenAI(api_key=OPENAI_API_KEY)

dynamodb = boto3.resource(
    'dynamodb',
    aws_access_key_id=os.getenv('AWS_ACCESS_KEY_ID'), 
    aws_secret_access_key=os.getenv('AWS_SECRET_ACCESS_KEY'),
    region_name='ap-northeast-2'  # 원하는 리전으로 변경
)
table = dynamodb.Table('ChatbotConversations')

original_allowed_usernames = os.getenv('ALLOWED_NAMES')
original_allowed_usernames = original_allowed_usernames.strip()

# JSON 파싱을 수행합니다.
allowed_usernames = json.loads(original_allowed_usernames)


def is_valid_username(username):
    return username in allowed_usernames

st.title(':male-teacher: AI ROBLOX Tutor')
st.header(':one: Tutor: Ask questions for programming your own Roblox game!')

user_id = st.text_input(label='Assigned ID.')


if is_valid_username(user_id):
    st.write(f'ID: :violet[{user_id}]')
    query = st.text_input(
        label='Write your question.',
        placeholder='ex. What properties should I adjust to change the transparency of a Roblox Part?'
    )

    st.write(f'Query: :violet[{query}]')

    query_1 = 'AT_TUTOR_1: ' + query
    
    # 이미지 입력
    image_uploaded1 = st.file_uploader("OPTIONAL: Upload an image", type=["png", "jpg", "jpeg"])

    def tutor_persona_query(query, image_data=None):
        import openai
        openai.api_key = OPENAI_API_KEY

        VISION_PROMPT_MESSAGES = [
            {
                "role": "system",
                "content": "Your role: You are an AI tutor providing interactive learning support for students engaged in constructionist gaming. Your goal is to offer personalized assistance that aligns with the learner’s objectives. Context: - The learner is building a game using [Roblox/Lua-based scripting]. - The learner is a pre-service teacher in a digital literacy course. - The learner is engaged in design-based, constructionist learning, working on ill-structured problems. - The learner may need help with computational thinking (CT) concepts such as decomposition, abstraction, algorithmic thinking, and pattern recognition. User Input: - The learner describes a challenge related to game design, programming logic, or debugging. - The learner may request alternative approaches, idea generation, or clarification of CT principles. Expected AI Response: 1. **Restate the learner's problem** in a concise and structured way to confirm understanding. 2. **Provide step-by-step guidance** for solving the problem (e.g., break it into subtasks, suggest a debugging strategy). 3. **Generate alternative approaches** if applicable. 4. **Explain relevant computational thinking concepts** (e.g., if the learner is struggling with loops, explain iteration and suggest a simplified example). 5. **Encourage self-reflection** by prompting the learner to apply the solution to their project. 6. If applicable, **provide a relevant external resource or documentation link**."
            },
            {"role": "user", "content": query},
        ]

        if image_data is not None:
            encoded_image = base64.b64encode(image_data).decode("utf-8")
            VISION_PROMPT_MESSAGES.append({"role": "user", "content": encoded_image})


        params = {
            "model": "gpt-4o-mini",
            "messages": VISION_PROMPT_MESSAGES,
            "max_tokens": 3000, # 1024,
        }

        trimmed_answer = ""  # trimmed_answer 초기화
        try:
            full_answer = openai.chat.completions.create(**params)
            trimmed_answer = full_answer.choices[0].message.content
        except Exception as e:
            print(f"Error: {e}")
            trimmed_answer = f"Error: {e}"  # 오류 메시지를 trimmed_answer에 할당

        return trimmed_answer

    # 버튼 클릭
    button1 = st.button(':sparkles: ask :sparkles:')
    

    def save_message(user_id, message, timestamp=None):
        if timestamp is None:
            timestamp = datetime.datetime.now()

        # datetime 객체를 DynamoDB 지원 타입으로 변환
        if isinstance(timestamp, datetime.datetime):
            timestamp = int(timestamp.timestamp())  # Unix 타임스탬프(초 단위 정수)로 변환

        table.put_item(
            Item={
                'UserID': user_id,
                'Timestamp': timestamp,
                'Message': message
            }
        )


    if button1:
        query_1 = query_1
        save_message(user_id, query_1) 

        if image_uploaded1 is not None:
            image_data = image_uploaded1.read()
            answer = tutor_persona_query(query, image_data)
        else:
            answer = tutor_persona_query(query)
        
        answer_1 = 'AT_TUTOR_1: ' + answer
        save_message(user_id, answer_1)
        st.write(f'{answer}')
    

else:
    st.warning("Invalid username. Please enter a valid username.")