Update app.py

app.py

@@ -1,199 +1,109 @@
-import gradio as gr
-from openai import OpenAI
+import os
 import random
+import gradio as gr
 
-# ✅ OpenRouter APIキー（ここに直接書く）
+# OpenRouter APIキーを指定
 API_KEY = "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"
-BASE_URL = "https://openrouter.ai/api/v1"
-
-# --- Lexile難易度別教材（各3文） ---
-texts = {
-    300: [
-        "Tom has a red ball. He plays with it in the park. The sun is bright.",
-        "A dog runs after a stick. The boy laughs as the dog brings it back.",
-        "The girl eats an apple under the tree while the wind blows softly."
+
+# Lexileレベルごとの文章セット（各3問）
+texts_by_level = {
+    400: [
+        {"text": "Tom has a little dog. The dog likes to run in the park.", "question": "What does Tom's dog like to do?", "options": ["Run in the park", "Sleep all day", "Eat candy", "Climb trees"], "answer": "Run in the park"},
+        {"text": "The sun is bright today. Many children are playing outside.", "question": "Where are the children playing?", "options": ["Outside", "In school", "At night", "In the house"], "answer": "Outside"},
+        {"text": "Anna has a red ball. She throws it to her friend in the garden.", "question": "Where does Anna throw the ball?", "options": ["In the garden", "In the kitchen", "In the school", "In the store"], "answer": "In the garden"},
     ],
     600: [
-        "A young boy found a lost puppy near the river. He decided to take care of it.",
-        "Mary saw a rainbow after the rain stopped and felt happy.",
-        "The teacher asked the students to write a short story about friendship."
+        {"text": "Sara goes to the library every Saturday. She likes to read mystery books.", "question": "What kind of books does Sara like?", "options": ["Mystery books", "Science books", "History books", "Cooking books"], "answer": "Mystery books"},
+        {"text": "A frog can jump far. It uses its strong legs to move fast.", "question": "What helps the frog jump far?", "options": ["Its strong legs", "Its arms", "Its eyes", "Its color"], "answer": "Its strong legs"},
+        {"text": "Ben plants some seeds in the garden. After a few days, small plants grow.", "question": "What happens after a few days?", "options": ["Small plants grow", "The seeds disappear", "It starts to snow", "The garden becomes empty"], "answer": "Small plants grow"},
     ],
-    850: [
-        "Sarah enjoyed reading stories about ancient civilizations and their discoveries.",
-        "During the festival, people decorated the streets with lights and music.",
-        "James wanted to learn how airplanes could stay in the sky for so long."
+    800: [
+        {"text": "David wanted to learn how machines work. He took apart an old radio to see the parts inside.", "question": "Why did David take apart the radio?", "options": ["To see the parts inside", "To break it", "To sell it", "To clean it"], "answer": "To see the parts inside"},
+        {"text": "In winter, many animals rest or sleep for a long time. This is called hibernation.", "question": "What do animals do during hibernation?", "options": ["Sleep for a long time", "Eat more food", "Play outside", "Travel to other countries"], "answer": "Sleep for a long time"},
+        {"text": "Lisa looked through the telescope and saw bright stars in the night sky.", "question": "What did Lisa use to see the stars?", "options": ["A telescope", "A microscope", "A flashlight", "A magnifier"], "answer": "A telescope"},
     ],
-    1050: [
-        "The scientist developed a new hypothesis about the evolution of animal behavior.",
-        "Farmers began to adopt sustainable methods to protect soil health.",
-        "A historian analyzed old letters to understand social changes during the war."
+    1000: [
+        {"text": "Plants use sunlight to make food. This process is called photosynthesis.", "question": "What do plants use to make food?", "options": ["Sunlight", "Wind", "Soil", "Rain"], "answer": "Sunlight"},
+        {"text": "Electric cars are better for the environment because they produce less pollution.", "question": "Why are electric cars better for the environment?", "options": ["They produce less pollution", "They are faster", "They use gasoline", "They make noise"], "answer": "They produce less pollution"},
+        {"text": "The computer stores data in its memory. This allows users to save their work.", "question": "What does the computer store in its memory?", "options": ["Data", "Food", "Games", "Pictures only"], "answer": "Data"},
     ],
-    1250: [
-        "Philosophers have long debated the intricate relationship between free will and determinism.",
-        "Modern architecture often reflects both functionality and aesthetic simplicity.",
-        "Researchers in neuroscience continue to explore how memory is formed and stored."
+    1200: [
+        {"text": "The scientist observed how the new medicine affected the cells under a microscope.", "question": "What did the scientist use to see the cells?", "options": ["A microscope", "A telescope", "A camera", "A ruler"], "answer": "A microscope"},
+        {"text": "During the experiment, the temperature was carefully controlled to ensure accurate results.", "question": "Why was the temperature controlled?", "options": ["To ensure accurate results", "To make it hotter", "To test faster", "To make it colder"], "answer": "To ensure accurate results"},
+        {"text": "Researchers developed a new algorithm that can predict weather patterns more accurately.", "question": "What can the new algorithm do?", "options": ["Predict weather patterns", "Make maps", "Control the wind", "Measure temperature"], "answer": "Predict weather patterns"},
     ]
 }
 
-levels = [300, 600, 850, 1050, 1250]
-
-# --- OpenAIクライアント設定 ---
-client = OpenAI(base_url=BASE_URL, api_key=API_KEY)
-
-# --- 出題済みテキストを管理するセット ---
-used_texts = set()
-
-# --- AIに問題生成を依頼 ---
-def generate_question(text):
-    prompt = f"""
-    Read the following passage and generate ONE multiple-choice question with 4 options (A–D).
-    Clearly mark the correct answer with an asterisk (*).
-    The format must be:
-
-    Q: <question text>
-    A. <option>
-    B. <option>
-    C. <option>
-    D. <option>
-
-    Passage:
-    {text}
-    """
+# 状態管理
+state = {
+    "current_level": 600,
+    "question_count": 0,
+    "used_texts": set(),
+    "correct_count": 0,
+    "finished": False
+}
 
-    response = client.chat.completions.create(
-        model="google/gemma-3-27b-it:free",
-        messages=[{"role": "user", "content": prompt}],
-        max_tokens=400,
-        temperature=0.7,
-    )
-    raw_output = response.choices[0].message.content.strip()
-
-    # --- 正解の抽出 ---
-    correct_option = None
-    for line in raw_output.splitlines():
-        if line.lower().startswith("correct:"):
-            correct_option = line.split(":")[1].strip().upper()
-            break
-
-    # --- アスタリスク除去（*印があっても削除） ---
-    cleaned_lines = []
-    for line in raw_output.splitlines():
-        if "*" in line:
-            line = line.replace("*", "").strip()
-        # Correct行は表示しない
-        if not line.lower().startswith("correct:"):
-            cleaned_lines.append(line)
-
-    cleaned_output = "\n".join(cleaned_lines)
-    return cleaned_output, correct_option
-
-
-# --- 適応型テストの進行 ---
-def adaptive_test(prev_level, prev_correct):
-    idx = levels.index(prev_level)
-    if prev_correct and idx < len(levels) - 1:
-        new_level = levels[idx + 1]
-    elif not prev_correct and idx > 0:
-        new_level = levels[idx - 1]
-    else:
-        new_level = prev_level
-    return new_level
-
-
-# --- 未使用の文章を取得 ---
-def get_unused_text(level):
-    available = [t for t in texts[level] if (level, t) not in used_texts]
+def get_next_question():
+    level_texts = texts_by_level[state["current_level"]]
+    available = [t for t in level_texts if t["text"] not in state["used_texts"]]
     if not available:
-        # すべて使った場合はリセット
-        used_texts.clear()
-        available = texts[level]
-    chosen = random.choice(available)
-    used_texts.add((level, chosen))
-    return chosen
-
-
-# --- テスト開始 ---
-def start_test():
-    level = 850  # 中間レベルから開始
-    text = get_unused_text(level)
-    question, correct = generate_question(text)
-    return f"Lexile: {level}L", text, question, level, correct, ""
-
-
-# --- 回答を処理して次へ ---
-def next_step(prev_level, user_answer, question_text, correct_option):
-    if correct_option is None:
-        feedback = "⚠️ No correct answer found in the generated question."
-        return feedback, f"Lexile: {prev_level}L", "", "", prev_level, None, ""
-
-    correct = (user_answer == correct_option)
-
-    # レベルを更新
-    new_level = adaptive_test(prev_level, correct)
-    new_text = get_unused_text(new_level)
-    new_question, new_correct = generate_question(new_text)
-
-    feedback = "✅ Correct!" if correct else "❌ Incorrect."
-    if new_level == prev_level:
-        feedback += f"\n🎯 Your estimated reading level is **{new_level}L** (final)."
-    else:
-        feedback += f"\n➡️ Moving to next level: **{new_level}L**"
-
-    return (
-        feedback,
-        f"Lexile: {new_level}L",
-        new_text,
-        new_question,
-        new_level,
-        new_correct,
-        ""
-    )
+        return None
+    question = random.choice(available)
+    state["used_texts"].add(question["text"])
+    return question
+
+def check_answer(user_answer):
+    correct = state["current_question"]["answer"]
+    return user_answer == correct
+
+def quiz_flow(user_answer=None):
+    if state["finished"]:
+        return "テストはすでに終了しています。再開するにはページをリロードしてください。", None, None, None
+
+    # 回答処理
+    if user_answer is not None:
+        if check_answer(user_answer):
+            state["correct_count"] += 1
+            state["current_level"] = min(state["current_level"] + 200, 1200)
+        else:
+            state["current_level"] = max(state["current_level"] - 200, 400)
+        state["question_count"] += 1
+
+    # 5問で終了
+    if state["question_count"] >= 5:
+        state["finished"] = True
+        return f"✅ テスト終了！あなたの推定読解レベルは {state['current_level']}L です。", None, None, None
+
+    # 次の問題取得
+    question = get_next_question()
+    if not question:
+        state["finished"] = True
+        return f"📘 これ以上の問題がありません。あなたの推定レベルは {state['current_level']}L です。", None, None, None
+
+    state["current_question"] = question
+    return question["text"], question["question"], question["options"], None
+
+# Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("## 📖 英文読解テスト（全5問）")
 
+    passage = gr.Textbox(label="文章", interactive=False, lines=4)
+    question_box = gr.Textbox(label="問題", interactive=False)
+    options = gr.Radio(label="選択肢", choices=[])
+    result = gr.Textbox(label="結果表示", interactive=False)
 
-# --- Gradio UI ---
-with gr.Blocks() as demo:
-    gr.Markdown("# 📘 Adaptive Reading Level Test (Lexile-based)")
-
-    start_btn = gr.Button("▶️ Start Test")
-
-    level_display = gr.Textbox(label="Current Level", interactive=False)
-    text_display = gr.Textbox(label="Reading Passage", lines=6, interactive=False)
-    question_display = gr.Textbox(label="Generated Question", lines=8, interactive=False)
-
-    user_answer = gr.Radio(choices=["A", "B", "C", "D"], label="Your Answer")
-    submit_btn = gr.Button("Submit Answer")
-
-    feedback_display = gr.Markdown()
-    hidden_level = gr.Number(visible=False)
-    hidden_correct = gr.Textbox(visible=False)
-
-    # --- Start Test ---
-    start_btn.click(
-        fn=start_test,
-        inputs=[],
-        outputs=[
-            level_display,
-            text_display,
-            question_display,
-            hidden_level,
-            hidden_correct,
-            feedback_display,
-        ],
-    )
+    next_btn = gr.Button("次へ")
 
-    # --- Submit & Move to Next ---
-    submit_btn.click(
+    def next_step(user_choice):
+        return quiz_flow(user_choice)
+
+    next_btn.click(
         fn=next_step,
-        inputs=[hidden_level, user_answer, question_display, hidden_correct],
-        outputs=[
-            feedback_display,
-            level_display,
-            text_display,
-            question_display,
-            hidden_level,
-            hidden_correct,
-            feedback_display,
-        ],
+        inputs=[options],
+        outputs=[passage, question_box, options, result],
     )
 
+    # 初期化時に最初の問題表示
+    demo.load(fn=quiz_flow, inputs=None, outputs=[passage, question_box, options, result])
+
 demo.launch()