Update app.py

app.py

@@ -4,16 +4,31 @@ import json
 import os
 import random
 import gradio as gr
+from google import genai
+from google.genai import types
 
 # 取得 Hugging Face Token，用於 API 調用推論服務
-from huggingface_hub import InferenceClient
+# from huggingface_hub import InferenceClient
 
-API_KEY = os.environ.get("GROQ_API_KEY")
-API_BASE_URL = os.environ.get("GROQ_API_BASE_URL")
-client = InferenceClient(
-    api_key=API_KEY,
-    base_url=API_BASE_URL
-)
+# API_KEY = os.environ.get("GROQ_API_KEY")
+# API_BASE_URL = os.environ.get("GROQ_API_BASE_URL")
+
+# client = InferenceClient(
+#     api_key=API_KEY,
+#     base_url=API_BASE_URL
+# )
+
+API_KEY = os.environ.get("GOOGLE_API_KEY")
+client = genai.Client(api_key=API_KEY)
+
+def generate_content(model="gemini-2.0-pro-exp-02-05", sys_prompt=None, user_prompt=None):
+    response = client.models.generate_content(
+        model=model,
+        config=types.GenerateContentConfig(
+            system_instruction=sys_prompt),
+        contents=user_prompt
+    )
+    return response.text
 
 # 載入問答資料庫路徑
 output_dir = "./question_bank"
@@ -98,7 +113,7 @@ def generate_math_questions(grade, term, qtype="Unspecified", num_questions=10):
     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, 1000)
+    input_question_bank = random_questions_with_limit(raw_questions, 5000)
 
     # 系統訊息 (system) 與使用者要求 (user) 的對話內容
     # 說明給模型：要產生新的英文題目，保持難度與風格類似，但不要直接抄題庫原文
@@ -106,7 +121,7 @@ def generate_math_questions(grade, term, qtype="Unspecified", num_questions=10):
         {
             "role": "system",
             "content": """
-            You are an advanced AI assistant designed to generate educational questions. Your task is to create new and diverse questions based on existing question banks. The new questions should be similar in difficulty, style, and structure to the input questions but must not directly replicate them. **All responses must be in English.**
+            You are an advanced AI assistant designed to generate educational questions. Your task is to create new and diverse questions based on existing question banks. The new questions should be similar in difficulty, style, and structure to the input questions but must not directly replicate them. **All responses must be in Traditional Chinese.**
 
             Key Instructions:
             1. Maintain the educational purpose of the questions.
@@ -124,7 +139,7 @@ def generate_math_questions(grade, term, qtype="Unspecified", num_questions=10):
             - Clearly distinguish the new question and the answer.
             - If multiple questions are generated, number them sequentially.
             - Ensure clarity and correctness in all generated content.
-            - Respond only in **English**."""
+            - Respond only in **Traditional Chinese**."""
         },
         {
             "role": "user",
@@ -160,16 +175,23 @@ 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-7B-Instruct-v0.3",
-        model="deepseek-r1-distill-qwen-32b",
-        # model="mistralai/Mistral-Nemo-Instruct-2407", 
-        messages=messages,
-        max_tokens=1024
-    )
+    # # 使用 InferenceClient 呼叫 API 模型產生新題目
+    # completion = client.chat.completions.create(
+    #     # model="mistralai/Mistral-7B-Instruct-v0.3",
+    #     model="deepseek-r1-distill-qwen-32b",
+    #     # model="mistralai/Mistral-Nemo-Instruct-2407", 
+    #     messages=messages,
+    #     max_tokens=1024
+    # )
 
-    response = completion.choices[0].message.content
+    # response = completion.choices[0].message.content
+
+    response = generate_content(
+        sys_prompt=messages[0]['content'], 
+        user_prompt=messages[1]['content']
+    )
+    print(response)
+    
     response = remove_think_tags(response)
     print(response)