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Update app.py
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app.py
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import gradio as gr
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import random
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from openai import OpenAI
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import json
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# ✅
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API_KEY = "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"
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# ✅ OpenRouter
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client = OpenAI(
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base_url="https://openrouter.ai/api/v1",
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api_key=API_KEY
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)
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# ===== Lexileレベル
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materials = {
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300: [
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"The cat is on the mat.",
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]
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}
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# =====
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def generate_question(text):
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prompt = f"""
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Please create one English reading comprehension question about the following passage.
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Format
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{{
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"question": "Question text",
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"choices": ["A) ...", "B) ...", "C) ...", "D) ..."],
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"answer": "A"
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}}
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Passage:
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{text}
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"""
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try:
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response = client.chat.completions.create(
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model="google/gemma-3-27b-it:free",
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messages=[{"role": "user", "content": prompt}],
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max_tokens=300
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)
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data = response.choices[0].message.content.strip()
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q = json.loads(data)
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# ===== テスト初期化 =====
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def start_test():
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"level": 850,
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"asked": [],
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"score": 0,
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"count": 0
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}
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# ===== 最初の問題
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def get_first_question(state):
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text = random.choice(materials[state["level"]])
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state["asked"].append(text)
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return state, "Please start the test first.", "", "", [], ""
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correct = user_choice == state["current_q"]["answer"]
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feedback = "✅ Correct!" if correct else f"❌
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# レベル変動
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if correct:
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# 5問で終了
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if state["count"] >= 5:
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result = f"🎯 Test finished! Your estimated reading
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return state, result, "", "", [], ""
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#
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available = [t for t in materials[state["level"]] if t not in state["asked"]]
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if not available:
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available = materials[state["level"]]
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q = generate_question(text)
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state["current_q"] = q
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return state, text, q["question"], "", q["choices"], feedback
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# ===== Gradio UI =====
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with gr.Blocks() as demo:
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gr.Markdown("## 📘 Adaptive Reading Test
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state = gr.State()
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passage = gr.Textbox(label="Reading Passage", interactive=False)
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question = gr.Textbox(label="Question", interactive=False)
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feedback = gr.Textbox(label="Feedback", interactive=False)
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choices = gr.Radio(label="Your Answer", choices=["A", "B", "C", "D"])
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msg = gr.Textbox(label="
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with gr.Row():
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start_btn = gr.Button("▶️ Start Test")
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next_btn = gr.Button("➡️ Submit & Next")
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demo.launch(share=True)
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import gradio as gr
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import random
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import json
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from openai import OpenAI
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# ✅ APIキーをここに直接指定
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API_KEY = "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"
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# ✅ OpenRouterクライアント設定
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client = OpenAI(
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base_url="https://openrouter.ai/api/v1",
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api_key=API_KEY
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)
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# ===== Lexileレベルごとの教材 =====
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materials = {
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300: [
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"The cat is on the mat.",
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]
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}
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# ===== 問題生成 =====
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def generate_question(text):
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prompt = f"""
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Please create one English reading comprehension question about the following passage.
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Format your output strictly as JSON like this:
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{{
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"question": "Question text",
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"choices": ["A) ...", "B) ...", "C) ...", "D) ..."],
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"answer": "A"
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}}
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The correct answer must not be explicitly revealed in the choices or question text.
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Passage:
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{text}
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"""
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try:
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response = client.chat.completions.create(
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model="google/gemma-3-27b-it:free",
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messages=[{"role": "user", "content": prompt}],
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max_tokens=300,
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temperature=0.7
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)
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data = response.choices[0].message.content.strip()
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q = json.loads(data)
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# ===== テスト初期化 =====
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def start_test():
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state = {
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"level": 850, # 初期レベル(中間)
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"asked": [],
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"score": 0,
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"count": 0
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}
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return state, "✅ Test started! Please read the passage carefully.", "", "", [], ""
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# ===== 最初の問題を取得 =====
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def get_first_question(state):
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text = random.choice(materials[state["level"]])
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state["asked"].append(text)
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return state, "Please start the test first.", "", "", [], ""
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correct = user_choice == state["current_q"]["answer"]
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feedback = "✅ Correct!" if correct else f"❌ Incorrect. The correct answer was {state['current_q']['answer']}."
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# レベル変動
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if correct:
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# 5問で終了
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if state["count"] >= 5:
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result = f"🎯 Test finished! Your estimated reading ability corresponds to approximately {state['level']}L."
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return state, result, "", "", [], ""
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# 新しい教材を重複なしで選択
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available = [t for t in materials[state["level"]] if t not in state["asked"]]
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if not available:
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available = materials[state["level"]]
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q = generate_question(text)
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state["current_q"] = q
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# 次の問題を返す(選択肢リセット)
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return state, text, q["question"], "", q["choices"], feedback
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# ===== Gradio UI =====
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with gr.Blocks() as demo:
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gr.Markdown("## 📘 Adaptive Reading Test")
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state = gr.State()
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passage = gr.Textbox(label="Reading Passage", lines=6, interactive=False)
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question = gr.Textbox(label="Question", lines=2, interactive=False)
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feedback = gr.Textbox(label="Feedback", lines=2, interactive=False)
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choices = gr.Radio(label="Your Answer", choices=["A", "B", "C", "D"], value=None)
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msg = gr.Textbox(label="Message", lines=2, interactive=False)
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with gr.Row():
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start_btn = gr.Button("▶️ Start Test")
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next_btn = gr.Button("➡️ Submit & Next")
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# スタートボタン
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start_btn.click(
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start_test,
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outputs=[state, msg, passage, question, choices, feedback]
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).then(
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get_first_question,
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inputs=state,
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outputs=[state, passage, question, choices, feedback]
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)
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# 次の問題ボタン
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next_btn.click(
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next_step,
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inputs=[state, choices],
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outputs=[state, passage, question, choices, feedback, msg]
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)
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demo.launch(share=True)
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