PROWEB-35 改成使用Gemini

ai/views.py

@@ -1,59 +1,151 @@
-from django.shortcuts import render
-from openai import OpenAI
+from google import genai
 import os
 from django.http import JsonResponse
-from django.views.decorators.csrf import csrf_exempt
-# from .models import DifficultyEvaluation, DifficultyEvaluationQuestion
+from django.contrib.auth.decorators import login_required
+from .models import DifficultyEvaluation
+from questions.models import Question, QuestionHistory
 
-client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
+client = genai.Client(api_key=os.getenv("GEMINI_API_KEY"))
 
-@csrf_exempt
+def _payload_from_request(data):
+    return {
+        "title": data.get('title') or "",
+        "content": data.get('content') or "",
+        "level": data.get('level') or "",
+        "input_format": data.get('input_format') or "",
+        "output_format": data.get('output_format') or "",
+        "input_example": data.get('input_example') or "",
+        "output_example": data.get('output_example') or "",
+        "answer": data.get('answer') or "",
+        "hint": data.get('hint') or "",
+        "reference": data.get('reference') or "",
+    }
+
+@login_required
 def analyze_question(request):
     if request.method == "POST":
         data = request.POST
 
-        title = data.get('title')
-        level = data.get('level')
-        content = data.get('content')
-        input_format = data.get('input_format')
-        output_format = data.get('output_format')
-        input_example = data.get('input_example')
-        output_example = data.get('output_example')
-        answer = data.get('answer')
-        hint = data.get('hint')
-        reference = data.get('reference')
-        topics = data.getlist('topics')
-        tags = data.getlist('tags')
-
-        # 組合完整 prompt 給 AI
-        full_question = (
-            f"題目描述：{content}\n"
-            f"輸入格式：{input_format}\n"
-            f"輸出格式：{output_format}\n"
-            f"輸入範例：{input_example}\n"
-            f"輸出範例：{output_example}\n"
-            f"提示：{hint}\n"
-        )
-
         try:
-            completion = client.chat.completions.create(
-                model="gpt-4o",
-                messages=[
-                    {"role": "system", "content": "你是一個用來評估程式設計題目難度的 AI 助理，請根據以下標準分析學生所出的題目，並給出：1.題目難度（簡單／中等／困難），2.評估依據（簡短說明使用哪些語法或概念)，3,改進建議（可提供提升題目設計品質的建議，像是題目敘述完整度、方便閱讀程度、輸入/輸出格式表達正確度等等），4.題目標籤(格式為:#for迴圈、#函式等等）。難度評估標準如下:簡單:只需要使用基本的語法或概念，例如變數、條件判斷、迴圈等，若沒有跳出基本概念(如複雜的條件判斷)應判定為簡單。中等:需要使用較多的語法或概念，例如巢狀迴圈、陣列、字典、函式等。困難:需要使用複雜的語法或概念，例如遞迴、動態規劃、圖論、狀態轉移等。不要重複敘述題目內容和對解題方法給出建議，僅需要針對題目難度給出評估與建議。注意:如果你發現輸入內容是程式碼或是無關的文字而不是題目敘述，不要進行難度評估，僅回覆：「請提供題目敘述內容，才能進行難度分析喔 🙂」。題目可能以文字冒險、角色扮演、指令模擬等方式表達，不要因為語氣或敘事風格而誤判為非題目敘述，只要有明確任務與邏輯要求，即應視為程式設計題目。"},
-                    {"role": "user", "content": full_question},
-                ],
-                temperature=0.2,
+            # 整理 payload
+            payload = _payload_from_request(data)
+
+            # 建立/更新草稿 Question
+            draft_q = None
+            incoming_qid = data.get('question_id')
+            if incoming_qid:
+                try:
+                    draft_q = Question.objects.get(id=incoming_qid)
+                    # 覆寫草稿內容
+                    for k, v in payload.items():
+                        if hasattr(draft_q, k):
+                            setattr(draft_q, k, v)
+                    if hasattr(draft_q, "is_active"):
+                        draft_q.is_active = False
+                    if hasattr(draft_q, "is_approved"):
+                        draft_q.is_approved = False
+                    draft_q.save()
+                except Question.DoesNotExist:
+                    draft_q = None
+
+            if draft_q is None:
+                # 第一次做 AI 分析：建一筆草稿
+                create_kwargs = {k: v for k, v in payload.items() if hasattr(Question, k)}
+                if hasattr(Question, "is_active"):
+                    create_kwargs["is_active"] = False
+                if hasattr(Question, "is_approved"):
+                    create_kwargs["is_approved"] = False
+
+                create_kwargs['user'] = request.user
+                draft_q = Question.objects.create(**create_kwargs)
+
+            if 'tags' in request.POST:
+                draft_q.tags.set(request.POST.getlist('tags'))
+            if 'topics' in request.POST:
+                draft_q.topics.set(request.POST.getlist('topics'))
+            draft_q.save()
+
+            # 建立 QuestionHistory
+            latest = QuestionHistory.objects.filter(question=draft_q).order_by('-version').first()
+            next_ver = (latest.version if latest else 0) + 1
+            hist = QuestionHistory.objects.create(
+                question=draft_q,
+                user=request.user if request.user.is_authenticated else None,
+                title=draft_q.title,
+                content=draft_q.content,
+                level=draft_q.level,
+                input_format=draft_q.input_format,
+                output_format=draft_q.output_format,
+                input_example=draft_q.input_example,
+                output_example=draft_q.output_example,
+                answer=getattr(draft_q, "answer", ""),
+                hint=getattr(draft_q, "hint", ""),
+                reference=getattr(draft_q, "reference", ""),
+                version=next_ver
             )
-            difficulty_content = completion.choices[0].message.content
-
-            # # 將 AI 分析結果存到資料庫
-            # difficulty_evaluation = DifficultyEvaluation.objects.create(
-            #     difficulty_score="待解析",  # 可以後續解析 difficulty_content 來提取具體分數
-            #     feedback=difficulty_content
-            # )
-
-            return JsonResponse({'result': difficulty_content})
+            if hasattr(hist, "tags") and hasattr(draft_q, "tags"):
+                hist.tags.set(draft_q.tags.all())
+            if hasattr(hist, "topics") and hasattr(draft_q, "topics"):
+                hist.topics.set(draft_q.topics.all())
+
+            system_instruction = (
+                "你是一個用來評估程式設計題目難度的 AI 助理，請根據以下標準分析學生所出的題目，並給出："
+                "1.題目難度（簡單／中等／困難），"
+                "2.評估依據（簡短說明使用哪些語法或概念)，"
+                "3.改進建議（可提供提升題目設計品質的建議，像是題目敘述完整度、方便閱讀程度、輸入/輸出格式表達正確度等等），"
+                "4.題目標籤(格式為:#for迴圈、#函式等等）。"
+                "難度評估標準如下:"
+                "簡單:只需要使用基本的語法或概念，例如變數、條件判斷、迴圈等，若沒有跳出基本概念(如複雜的條件判斷)應判定為簡單。"
+                "中等:需要使用較多的語法或概念，例如巢狀迴圈、陣列、字典、函式等。"
+                "困難:需要使用複雜的語法或概念，例如遞迴、動態規劃、圖論、狀態轉移等。"
+                "不要重複敘述題目內容和對解題方法給出建議，僅需要針對題目難度給出評估與建議。"
+                "注意:如果你發現輸入內容是程式碼或是無關的文字而不是題目敘述，不要進行難度評估，僅回覆：「請提供題目敘述內容，才能進行難度分析喔 🙂」。"
+                "題目可能以文字冒險、角色扮演、指令模擬等方式表達，不要因為語氣或敘事風格而誤判為非題目敘述，只要有明確任務與邏輯要求，即應視為程式設計題目。"
+            )
+
+            user_message = (
+                f"題目標題：{payload['title']}\n"
+                f"題目描述：{payload['content']}\n"
+                f"輸入格式：{payload['input_format']}\n"
+                f"輸出格式：{payload['output_format']}\n"
+                f"輸入範例：{payload['input_example']}\n"
+                f"輸出範例：{payload['output_example']}\n"
+                f"提示：{payload['hint']}\n"
+            )
+
+            chat = client.chats.create(
+                model='gemini-2.5-flash',
+                config=genai.types.GenerateContentConfig(
+                    system_instruction=system_instruction,
+                    temperature=0.1
+                )
+            )
+
+            response = chat.send_message(user_message)
+            difficulty_content = response.text
+
+            # 難度判斷
+            difficulty_score = "未知"
+            if "困難" in difficulty_content:
+                difficulty_score = "困難"
+            elif "中等" in difficulty_content:
+                difficulty_score = "中等"
+            elif "簡單" in difficulty_content:
+                difficulty_score = "簡單"
+
+            difficulty_evaluation = DifficultyEvaluation.objects.create(
+                difficulty_score=difficulty_score,
+                feedback=difficulty_content
+            )
+
+            return JsonResponse({
+                'result': difficulty_content,
+                'evaluation_id': difficulty_evaluation.id,
+                'difficulty_score': difficulty_score,
+                'question_id': draft_q.id
+            })
         except Exception as e:
             return JsonResponse({'error': str(e)}, status=500)
 
     return JsonResponse({'error': '只接受POST請求'}, status=400)
+

questions/views.py

@@ -6,21 +6,43 @@
 from answers.models import Answer
 from reviews.models import PeerReview
 from .forms import QuestionForm, QuestionDetailForm
+from ai.models import DifficultyEvaluation, DifficultyEvaluationQuestion
 from features.decorators import feature_required
 
 @login_required
 @feature_required('question_create')
 def question_create(request):
     if request.method == 'POST':
-        form = QuestionForm(request.POST, user=request.user)
+        question_id = request.POST.get('question_id')
+        instance = None
+        if question_id:
+            try:
+                instance = Question.objects.get(id=question_id)
+            except Question.DoesNotExist:
+                instance = None
+        form = QuestionForm(request.POST, instance=instance, user=request.user)
         if form.is_valid():
             question = form.save()
+             # 建立與AI分析關聯
+            evaluation_id = request.POST.get('evaluation_id')
+            if evaluation_id:
+                try:
+                    evaluation = DifficultyEvaluation.objects.get(id=evaluation_id)
+                    DifficultyEvaluationQuestion.objects.create(
+                        evaluation=evaluation,
+                        question=question
+                    )
+                except DifficultyEvaluation.DoesNotExist:
+                    pass
             # 記錄創建問題的日誌
             QuestionLog.objects.create(
                 question=question,
                 user=request.user,
                 action='created'
             )
+
+            latest = QuestionHistory.objects.filter(question=question).order_by('-version').first()
+            next_ver = (latest.version if latest else 0) + 1
             # 創建問題的歷史記錄
             history = QuestionHistory.objects.create(
                 question=question,
@@ -35,7 +57,7 @@ def question_create(request):
                 answer=question.answer,
                 hint=question.hint,
                 reference=question.reference,
-                version=1
+                version=next_ver
             )
             # 設置多對多關係
             history.tags.set(question.tags.all())

requirements.txt

@@ -1,4 +1,6 @@
 django==5.2.3
 psycopg2==2.9.10
 pillow==11.2.1
-python-dotenv==1.0.1
+python-dotenv==1.0.1
+google-genai==1.31.0
+google-auth==2.40.3

static/js/questions/create.js

@@ -351,6 +351,16 @@ function aiAnalysis() {
       $("#ai-analysis-button").prop("disabled", true).text("AI分析完成").off("click");
       showToast("AI分析完成", 'success');
 
+      // 儲存 evaluation_id 供後續題目提交時使用
+      if (response.evaluation_id) {
+        $("#questionForm input[name='evaluation_id']").remove();
+        $("#questionForm").append(`<input type=\"hidden\" name=\"evaluation_id\" value=\"${response.evaluation_id}\">`);
+      }
+      if (response.question_id) {
+        $("#questionForm input[name='question_id']").remove();
+        $("#questionForm").append(`<input type="hidden" name="question_id" value="${response.question_id}">`);
+      }
+
       // 恢復提交按鈕
       $("button[type='submit']").prop("disabled", false).text("提交問題");
     },