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Update app.py
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app.py
CHANGED
@@ -1,68 +1,54 @@
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import streamlit as st
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import openai
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import time
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import gspread
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from oauth2client.service_account import ServiceAccountCredentials
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#
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scope = ["https://spreadsheets.google.com/feeds", "https://www.googleapis.com/auth/drive"]
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creds = ServiceAccountCredentials.from_json_keyfile_name("genexam-2c8c645ecc0d.json", scope)
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client_gs = gspread.authorize(creds)
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# เปิด Google Sheets โดยใช้ชื่อของ sheet
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sheet = client_gs.open("GeneXam user").sheet1 # ใส่ชื่อจริงของ Google Sheet
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# ฟังก์ชันตรวจสอบ username ใน Google Sheets
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def check_user_in_sheet(username):
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try:
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users_list = sheet.col_values(1)
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if username in users_list:
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return True
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return False
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except Exception as e:
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st.error(f"Error checking user: {str(e)}")
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return False
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# ฟังก์ชันอัปเดตการใช้ API ของผู้ใช้
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def update_api_usage(username):
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try:
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users_list = sheet.col_values(1)
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row_number = users_list.index(username) + 1
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api_usage = int(sheet.cell(row_number, 2).value)
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api_usage += 1
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sheet.update_cell(row_number, 2, api_usage)
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except Exception as e:
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st.error(f"Error updating API usage: {str(e)}")
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# รีเซ็ตการใช้ API เมื่อถึงเวลารีเซ็ตทุกวัน (ถ้าจำเป็น)
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def reset_api_usage_daily():
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try:
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users_list = sheet.col_values(1)
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for i, user in enumerate(users_list):
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sheet.update_cell(i + 1, 2, 0) # รีเซ็ตคอลัมน์ที่ 2 (การใช้ API) เป็น 0
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except Exception as e:
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st.error(f"Error resetting API usage: {str(e)}")
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# ตั้งค่า OpenAI API key จาก Hugging Face Secrets
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openai.api_key = st.secrets["OPENAI_API_KEY"]
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# ฟังก์ชันการสร้างข้อสอบโดยใช้ OpenAI API และมี retry logic
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def generate_questions_with_retry(knowledge_material, question_type, cognitive_level, extra_instructions, case_based, num_choices=None, max_retries=3):
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# Adjust
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if question_type == "Multiple Choice":
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num_questions = 3
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elif question_type == "Fill in the Blank":
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num_questions = 10
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elif question_type == "True/False":
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num_questions = 5
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else: # Open-ended
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num_questions = 3
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# Base prompt
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prompt = f"Generate {num_questions} {question_type.lower()} exam questions based on {cognitive_level.lower()} level from the following material: {knowledge_material}. {extra_instructions}"
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#
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if case_based:
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prompt = f"Generate {num_questions} {question_type.lower()} exam questions based on {cognitive_level.lower()} level from the following medical material: {knowledge_material}. The questions should be based on case-based medical situations, such as patient scenarios. {extra_instructions}"
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if question_type != "Fill in the Blank":
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retries = 0
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while retries < max_retries:
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try:
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response =
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model="
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messages=[
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{"role": "system", "content": "You are a helpful assistant for generating exam questions."},
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{"role": "user", "content": prompt}
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]
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)
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return response.choices[0].message.content
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except
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retries += 1
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time.sleep(2) # Wait for 2 seconds before retrying
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if retries == max_retries:
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st.error("Failed to
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return None
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# ระบบ login
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if 'username' not in st.session_state:
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import streamlit as st
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import openai
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from openai import OpenAI
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import time
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import gspread
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from oauth2client.service_account import ServiceAccountCredentials
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# Set up OpenAI client
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client = OpenAI(api_key=st.secrets["OPENAI_API_KEY"])
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# Google Sheets setup remains the same
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scope = ["https://spreadsheets.google.com/feeds", "https://www.googleapis.com/auth/drive"]
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creds = ServiceAccountCredentials.from_json_keyfile_name("genexam-2c8c645ecc0d.json", scope)
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client_gs = gspread.authorize(creds)
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sheet = client_gs.open("GeneXam user").sheet1
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def check_user_in_sheet(username):
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try:
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users_list = sheet.col_values(1)
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if username in users_list:
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return True
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return False
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except Exception as e:
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st.error(f"Error checking user: {str(e)}")
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return False
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def update_api_usage(username):
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try:
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users_list = sheet.col_values(1)
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row_number = users_list.index(username) + 1
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api_usage = int(sheet.cell(row_number, 2).value)
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api_usage += 1
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sheet.update_cell(row_number, 2, api_usage)
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except Exception as e:
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st.error(f"Error updating API usage: {str(e)}")
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def generate_questions_with_retry(knowledge_material, question_type, cognitive_level, extra_instructions, case_based, num_choices=None, max_retries=3):
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# Adjust number of questions based on type
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if question_type == "Multiple Choice":
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num_questions = 3
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elif question_type == "Fill in the Blank":
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num_questions = 10
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elif question_type == "True/False":
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num_questions = 5
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else: # Open-ended
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num_questions = 3
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# Base prompt
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prompt = f"Generate {num_questions} {question_type.lower()} exam questions based on {cognitive_level.lower()} level from the following material: {knowledge_material}. {extra_instructions}"
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# Modify prompt for case-based medical situations
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if case_based:
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prompt = f"Generate {num_questions} {question_type.lower()} exam questions based on {cognitive_level.lower()} level from the following medical material: {knowledge_material}. The questions should be based on case-based medical situations, such as patient scenarios. {extra_instructions}"
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if question_type != "Fill in the Blank":
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retries = 0
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while retries < max_retries:
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try:
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response = client.chat.completions.create(
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model="GPT-4o mini", # or your preferred model
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messages=[
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{"role": "system", "content": "You are a helpful assistant for generating exam questions."},
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{"role": "user", "content": prompt}
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]
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)
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return response.choices[0].message.content
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except Exception as e:
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retries += 1
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if retries == max_retries:
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st.error(f"Failed to generate questions after {max_retries} attempts. Error: {str(e)}")
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return None
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time.sleep(2) # Wait before retrying
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# ระบบ login
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if 'username' not in st.session_state:
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