Update app.py

app.py

@@ -1,178 +1,268 @@
 import gradio as gr
 from openai import OpenAI
-from datasets import load_dataset, Dataset
-from datetime import datetime
+from datasets import Dataset
+from datetime import datetime, timedelta
 import pandas as pd
-import time, os, uuid, tempfile
+import time, os, random, uuid, tempfile, json
 
+# --- API設定 ---
 API_KEY = os.getenv("API_KEY")
 BASE_URL = "https://openrouter.ai/api/v1"
 HF_TOKEN = os.getenv("HF_TOKEN")
+DATASET_REPO = "Toya0421/lexile_test_logging"
+LOG_FILE = "logs.csv"
 
-DATASET_REPO = "Toya0421/reading_exercise_logging"
+client = OpenAI(base_url=BASE_URL, api_key=API_KEY)
 
-client = OpenAI(
-    base_url=BASE_URL,
-    api_key=API_KEY
-)
+# --- 外部CSVとして管理する passsage_id / passage データ ---
+# （例）columns: passage_id, lexile_level, text
+passages_df = pd.read_csv("passage.csv")
 
-# CSV読み込み（lexile_level → level）
-def load_passages():
-    df = pd.read_csv("passage.csv")
-    df["id"] = df["id"].astype(str)
-    df["level"] = df["level"].astype(int)   # ★修正
-    df["passage"] = df["passage"].astype(str)
-    return df
+levels = [300, 600, 850, 1050, 1250]
 
-passages_df = load_passages()
+# --- 状態 ---
+used_passages = set()
+question_count = 0
+current_user_id = None
+action_log = []  # ✅ 選択肢変更ログ
 
-
-# ---------------------------------
-# ★ levelを決定するロジック（学生番号から自動で決定）
-# ---------------------------------
-def decide_level(student_id: str):
-    """
-    学生番号の末尾を使って 1〜5 に自動マッピング
-    """
-    try:
-        last_digit = int(student_id[-1])
-    except:
-        return 1  # 不正な値のときはレベル1
-
-    return last_digit // 2 + 1  # 0-1→1, 2-3→2, ..., 8-9→5
-
-
-# Passage 抽出
-def get_random_passage(level):
-    target_df = passages_df[passages_df["level"] == level]
-    if len(target_df) == 0:
-        return None
-    row = target_df.sample(1).iloc[0]
-    return row["id"], row["passage"]
-
-
-def generate_questions(passage_text):
+# --- AIで問題生成 ---
+def generate_question(text):
     prompt = f"""
-You are an English reading comprehension question generator.
-Create exactly 3 questions for the following passage.
-
-Return JSON in this format:
-{{
-  "q1": "...",
-  "q2": "...",
-  "q3": "..."
-}}
-
-Passage:
-{passage_text}
-"""
+    Read the following passage and create ONE multiple-choice question with 4 options (A–D).
+    Only output the question and options.
+    Format:
+    Q: <question text>
+    A. <option>
+    B. <option>
+    C. <option>
+    D. <option>
+    Passage:
+    {text}
+    """
     response = client.chat.completions.create(
-        model="gpt-4o-mini",
-        messages=[{"role": "user", "content": prompt}]
+        model="google/gemma-3-27b-it:free",
+        messages=[{"role": "user", "content": prompt}],
+        max_tokens=250,
+        temperature=0.7,
     )
-    return response.choices[0].message["content"]
+    return response.choices[0].message.content.strip()
 
-
-def generate_answers(passage_text, questions_json):
+# --- 正誤判定 ---
+def check_answer_with_ai(text, question, user_answer):
     prompt = f"""
-You are an AI that answers questions based on the passage.
-
-Return JSON in this format:
-{{
-  "a1": "...",
-  "a2": "...",
-  "a3": "..."
-}}
-
-Passage:
-{passage_text}
-
-Questions:
-{questions_json}
-"""
+    Read the passage and question below. Decide if the user's answer is correct.
+    Passage:
+    {text}
+    Question:
+    {question}
+    User Answer: {user_answer}
+    Respond with one word: "Correct" or "Incorrect".
+    """
     response = client.chat.completions.create(
-        model="gpt-4o-mini",
-        messages=[{"role": "user", "content": prompt}]
+        model="google/gemma-3-27b-it:free",
+        messages=[{"role": "user", "content": prompt}],
+        max_tokens=10,
+        temperature=0,
     )
-    return response.choices[0].message["content"]
+    return response.choices[0].message.content.strip().lower() == "correct"
+
+# --- 自動難易度調整 ---
+def adaptive_test(prev_level, prev_correct):
+    idx = levels.index(prev_level)
+    if prev_correct and idx < len(levels) - 1:
+        return levels[idx + 1]
+    elif not prev_correct and idx > 0:
+        return levels[idx - 1]
+    return prev_level
+
+# --- passage取得 ---
+def get_passage(level):
+    subset = passages_df[passages_df["lexile_level"] == level]
+    available = [pid for pid in subset["passage_id"] if pid not in used_passages]
+    if not available:
+        available = list(subset["passage_id"])
+    passage_id = random.choice(available)
+    text = subset[subset["passage_id"] == passage_id]["text"].iloc[0]
+    return passage_id, text
+
+# --- ログ追記 & Push ---
+def log_to_csv_and_push(entry):
+    df = pd.DataFrame([entry])
+    if os.path.exists(LOG_FILE):
+        df.to_csv(LOG_FILE, mode="a", index=False, header=False)
+    else:
+        df.to_csv(LOG_FILE, index=False)
+
+    all_logs = pd.read_csv(LOG_FILE)
+    tmp_dir = tempfile.mkdtemp()
+    tmp_path = os.path.join(tmp_dir, "data.parquet")
+    all_logs.to_parquet(tmp_path)
+
+    dataset = Dataset.from_parquet(tmp_path)
+    dataset.push_to_hub(DATASET_REPO, token=HF_TOKEN)
+
+# --- 開始ボタン動作 ---
+def start_test(student_id):
+    global used_passages, question_count, current_user_id, action_log
+    used_passages = set()
+    question_count = 0
+    action_log = []
+
+    if not student_id or student_id.strip() == "":
+        return (
+            "", "", 0, "", "",
+            "⚠️ 学生番号を入力してからテストを開始してください",
+            False, "", "", ""
+        )
 
+    current_user_id = student_id.strip()
 
-def log_to_huggingface(data):
-    tmp_path = f"/tmp/{uuid.uuid4()}.json"
-    ds = Dataset.from_pandas(pd.DataFrame([data]))
-    ds.to_json(tmp_path)
+    level = 850
+    passage_id, text = get_passage(level)
+    used_passages.add(passage_id)
 
-    commit_message = f"Add log {datetime.utcnow().isoformat()}"
+    question = generate_question(text)
+    displayed_time = datetime.utcnow() + timedelta(hours=9)
 
-    try:
-        from huggingface_hub import upload_file
+    return (
+        text, question, level, passage_id, "",
+        "", True, displayed_time.isoformat(), 1, current_user_id
+    )
 
-        upload_file(
-            path_or_fileobj=tmp_path,
-            path_in_repo=f"logs/{data['log_id']}.json",
-            repo_id=DATASET_REPO,
-            repo_type="dataset",
-            token=HF_TOKEN,
-            commit_message=commit_message
+# --- 選択肢変更イベント（ここで操作履歴を保存） ---
+def log_choice_change(choice, question_number, user_id):
+    global action_log
+    if choice:
+        action_log.append({
+            "action": "choice",
+            "choice": choice,
+            "time": (datetime.utcnow() + timedelta(hours=9)).isoformat()
+        })
+    return
+
+# --- 回答送信 ---
+def next_step(prev_level, user_answer, question_text, passage_text,
+              displayed_time, question_number, user_id, passage_id):
+
+    global question_count, used_passages, action_log
+
+    if not user_answer:
+        return (
+            "⚠️ Please select an answer!", passage_text, question_text, prev_level,
+            None, "", True, displayed_time, question_number, user_id, passage_id
         )
-    except Exception as e:
-        return f"Error uploading: {str(e)}"
-
-    return "Log saved."
 
+    submit_time = datetime.utcnow() + timedelta(hours=9)
+    question_count += 1
+
+    correct = check_answer_with_ai(passage_text, question_text, user_answer)
+    new_level = adaptive_test(prev_level, correct)
+
+    # --- ✅ ログ保存 (actionsに選択履歴がすべて入る)
+    entry = {
+        "user_id": user_id,
+        "question_number": question_count,
+        "lexile_level": prev_level,
+        "passage_id": passage_id,
+        "question": question_text,
+        "user_answer": user_answer,
+        "correct": correct,
+        "displayed_time": displayed_time,
+        "submit_time": submit_time.strftime("%Y-%m-%d %H:%M:%S"),
+        "actions": json.dumps(action_log, ensure_ascii=False)
+    }
+    log_to_csv_and_push(entry)
+
+    # ✅ 最終問題なら結果だけ大きく表示
+    if question_count >= 5:
+        return (
+            f"<h1>🎯 Your Reading level: <strong>{new_level}L</strong></h1>",
+            "", "", new_level,
+            None, "", False, "", "", user_id, passage_id
+        )
 
-# ---------------------------------
-# ★ student_id だけ受け取り、内部で level を決定
-# ---------------------------------
-def run_reading_quiz(student_id):
+    # --- 次の問題へ ---
+    next_passage_id, next_text = get_passage(new_level)
+    used_passages.add(next_passage_id)
 
-    # ★ここが最大の変更点
-    level = decide_level(student_id)
+    next_question = generate_question(next_text)
+    next_display_time = datetime.utcnow() + timedelta(hours=9)
 
-    result = get_random_passage(level)
-    if result is None:
-        return "指定されたレベルの文章がありません", "", ""
+    # ✅ 新しい問題のために選択操作ログをリセット
+    action_log = []
 
-    pid, passage = result
+    feedback = "✅ Correct!" if correct else "❌ Incorrect."
 
-    questions = generate_questions(passage)
+    return (
+        feedback + "\n➡️ Loading next question…",
+        next_text, next_question, new_level,
+        None, "", True, next_display_time.isoformat(), question_count + 1, user_id, next_passage_id
+    )
 
-    answers = generate_answers(passage, questions)
+# --- Gradio UI ---
+with gr.Blocks() as demo:
+    gr.Markdown("# 📘 Reading Level Test")
 
-    log_data = {
-        "log_id": str(uuid.uuid4()),
-        "timestamp": datetime.utcnow().isoformat(),
-        "student_id": student_id,
-        "level": level,      # ★levelをログに保存
-        "passage_id": pid,
-        "passage": passage,
-        "questions": questions,
-        "answers": answers,
-    }
+    student_id_input = gr.Textbox(label="Student ID", placeholder="例: B123456")
+    start_btn = gr.Button("▶️ Start Test")
 
-    status = log_to_huggingface(log_data)
+    text_display = gr.Textbox(label="Reading Passage", lines=8, interactive=False)
+    question_display = gr.Textbox(label="Question", lines=6, interactive=False)
+    user_answer = gr.Radio(["A", "B", "C", "D"], label="Your Answer")
+    submit_btn = gr.Button("Submit Answer")
 
-    return passage, questions, answers
+    feedback_display = gr.Markdown()
 
+    hidden_level = gr.Number(visible=False)
+    hidden_passage = gr.Textbox(visible=False)
+    hidden_display_time = gr.Textbox(visible=False)
+    hidden_question_number = gr.Number(visible=False)
+    hidden_user_id = gr.Textbox(visible=False)
+    hidden_passage_id = gr.Textbox(visible=False)
+    test_visible = gr.State(False)
 
-# ---------------------------------
-# ★ UI（level は削除して student_id のみ）
-# ---------------------------------
-with gr.Blocks() as app:
-    gr.Markdown("## 英語リーディング練習")
+    start_btn.click(
+        fn=start_test,
+        inputs=[student_id_input],
+        outputs=[
+            text_display, question_display, hidden_level, hidden_passage_id, user_answer,
+            feedback_display, test_visible, hidden_display_time,
+            hidden_question_number, hidden_user_id
+        ]
+    )
 
-    student_id_input = gr.Textbox(label="学生番号を入力")
+    # ✅ 選択肢変更ログ
+    user_answer.change(
+        fn=log_choice_change,
+        inputs=[user_answer, hidden_question_number, hidden_user_id],
+        outputs=[]
+    )
 
-    btn = gr.Button("問題を生成")
+    # ✅ 回答送信
+    submit_btn.click(
+        fn=next_step,
+        inputs=[hidden_level, user_answer, question_display, text_display,
+                hidden_display_time, hidden_question_number, hidden_user_id, hidden_passage_id],
+        outputs=[
+            feedback_display, text_display, question_display, hidden_level,
+            user_answer, hidden_passage, test_visible, hidden_display_time,
+            hidden_question_number, hidden_user_id, hidden_passage_id
+        ]
+    )
 
-    passage_out = gr.Textbox(label="Passage", lines=6)
-    question_out = gr.Textbox(label="Questions (JSON)")
-    answer_out = gr.Textbox(label="Answers (JSON)")
+    # ✅ 表示のON/OFF制御
+    def toggle_visibility(show):
+        v = bool(show)
+        return (
+            gr.update(visible=v), gr.update(visible=v),
+            gr.update(visible=v), gr.update(visible=v)
+        )
 
-    btn.click(
-        run_reading_quiz,
-        inputs=[student_id_input],
-        outputs=[passage_out, question_out, answer_out]
+    test_visible.change(
+        fn=toggle_visibility,
+        inputs=test_visible,
+        outputs=[text_display, question_display, user_answer, submit_btn]
     )
 
-app.launch()
+demo.launch()