Update app.py

app.py

@@ -1,3 +1,5 @@
+# -*- coding: utf-8 -*-
+
 import json
 import os
 import random
@@ -15,8 +17,6 @@ output_dir = "./question_bank"
 # 載入題庫字典(question_bank_dict)，格式為 { "年級_學期": [題庫檔名列表] }
 question_bank_dict = json.load(open(f"{output_dir}/question_bank_dict.json", "r"))
 
-print(question_bank_dict)
-
 def random_questions_with_limit(data, limit=20000):
     """
     隨機從 data 中挑選題目，並將總字串長度限制在 limit 字元數內（至少不小於 5000）。
@@ -68,7 +68,7 @@ def generate_math_questions(grade, term, qtype="Unspecified", num_questions=10):
         if os.path.exists(f"{output_dir}/md/{doc_path.replace('.pdf', '.md')}")
     ]
 
-    print(raw_questions)
+    print(f"Retrieved {len(raw_questions)} document(s)")
 
     # 隨機選取並限制字串長度的題庫內容
     input_question_bank = random_questions_with_limit(raw_questions, 20000)
@@ -108,7 +108,7 @@ def generate_math_questions(grade, term, qtype="Unspecified", num_questions=10):
 
             Requirements for the generated questions:
             - Number of new questions: {num_questions}
-            - Include the following types: [{qtype}]
+            - Include the following types: {qtype}
 
             Example Output Format:
             1. Question: [New Question 1]
@@ -125,7 +125,7 @@ def generate_math_questions(grade, term, qtype="Unspecified", num_questions=10):
 
     # 使用 InferenceClient 呼叫 API 模型產生新題目
     completion = client.chat.completions.create(
-        model="mistralai/Mistral-Nemo-Instruct-2407",
+        model="mistralai/Mistral-7B-Instruct-v0.3",
         messages=messages,
         max_tokens=num_questions * 200
     )