[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8},"actionData","errors","root",{"_101":102,"_103":104},"routes/embed.x.$handle.$name.$",{"_9":10,"_11":12,"_13":14,"_15":16,"_17":18,"_19":20,"_21":-5},"handle","konnnitiha","name","honnyakuki","path","main.ts","project",{"_22":45,"_11":12,"_33":46,"_47":-5,"_48":42,"_49":50,"_51":50,"_52":53,"_54":-5,"_55":56,"_57":25,"_58":32,"_59":-5,"_60":-5,"_61":62,"_63":64,"_65":-5,"_66":-5,"_67":-5,"_68":-5,"_69":70,"_71":70,"_72":73,"_74":73,"_75":73,"_76":70,"_77":70,"_78":79,"_80":81,"_82":83,"_84":42},"file",{"_22":23,"_11":14,"_24":25,"_26":-5,"_27":28,"_29":30,"_31":32,"_33":34,"_35":36,"_37":38,"_39":40,"_41":42,"_43":-5,"_13":44},"permalink","https://www.val.town/x/konnnitiha/honnyakuki/code/main.ts","extension","id","251b5bd7-812e-4d18-9a3f-c6bf4237188d","fileId","7c50c494-ab5e-11f1-a3b3-1607ee4eb77e","parentId","branchId","629ec275-bda2-4a65-97cf-97226800cc44","branchVersion",4,"latest",true,"createdAt",["D",1788855917477],"version",3,"fileType","http","content","/** @jsxImportSource npm:hono@3/jsx */\nimport { Hono } from \"npm:hono\";\n// 貼り付け後に「ドット」を「.`」に修正してください\nimport { sqlite } from \"https://esm.town/v/std/sqlite\";\nimport { OpenAI } from \"https://esm.town/v/std/openai\";\n\nconst app = new Hono();\nconst openai = new OpenAI();\n\n// --- データベースの初期化（過去の解読履歴用） ---\nawait sqlite.execute(`\n CREATE TABLE IF NOT EXISTS kobun_history (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n source_text TEXT NOT NULL,\n translated_text TEXT NOT NULL,\n analysis_text TEXT NOT NULL,\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP\n )\n`);\n\n// --- 共通のレイアウトHTML ---\nconst Layout = ({ title, children }: { title: string; children: any }) => (\n \n \n \n \n {title}\n \n \n \n

\n ⛩️ 古文自動現代語解読装置\n

\n \n 🏠\n \n

{children}

\n \n © 古文自動現代語解読装置 - Powered by AI\n \n \n \n);\n// 1. トップ画面（入力フォーム＆過去の解読履歴一覧）\napp.get(\"/\", async (c) => {\n // 過去の解読履歴を最新順に10件取得\n const result = await sqlite.execute(\n \"SELECT id, source_text, translated_text, created_at FROM kobun_history ORDER BY created_at DESC LIMIT 10\",\n );\n\n const idIdx = result.columns.indexOf(\"id\");\n const sourceIdx = result.columns.indexOf(\"source_text\");\n const transIdx = result.columns.indexOf(\"translated_text\");\n const dateIdx = result.columns.indexOf(\"created_at\");\n\n return c.html(\n \n

古文を入力してください

\n \n

\n\n

最近の解読履歴（最新10件）

\n {result.rows.length === 0\n ? (\n

\n まだ解読履歴がありません。最初の古文を上のフォームに入力してみましょう！\n

\n )\n : (\n result.rows.map((row: any) => {\n const id = row[idIdx];\n const source = row[sourceIdx];\n const trans = row[transIdx];\n const date = row[dateIdx];\n\n return (\n

\n {date}\n

\n \n 📄 {source.length > 30\n ? `${source.substring(0, 30)}...`\n : source}\n \n

\n 訳:{\" \"}\n {trans.length > 40 ? `${trans.substring(0, 40)}...` : trans}\n

\n );\n })\n )}\n

\n ,\n );\n});\n// 2. 古文をAIで解析・解読する処理\napp.post(\"/decode\", async (c) => {\n const body = await c.req.parseBody();\n const kobunText = body.kobun_text as string;\n\n if (!kobunText || kobunText.trim() === \"\") {\n return c.redirect(\"/\");\n }\n\n try {\n // 🧠 AI（OpenAI）に対して高度な古文解読を指示するプロンプト\n const response = await openai.chat.completions.create({\n model: \"gpt-4o-mini\", // 軽量で高速なモデルを使用\n messages: [\n {\n role: \"system\",\n content: `あなたは非常に優秀な古典文学の学者であり、古文の教師です。\n入力された古文に対して、以下の3つのステップで徹底的に解読してください。\n\n1. 【現代語訳】: \n 省略されている「主語」や「目的語」を適切に（かっこ）などで補いながら、初心者にも非常に分かりやすい、自然で美しい現代語訳を作成してください。\n\n2. 【重要単語と文法解説】: \n 文中に含まれる重要な古文単語（現代語と意味が異なるものなど）を抜き出し、その意味を解説してください。また、「係り結び」や重要な助動詞（過去・推量・完了など）、主語判定のポイントがあれば箇条書きで分かりやすく解説してください。\n\n出力のフォーマットは、必ず以下の区切り線（===）を正確に使って、2つのパートに綺麗に分けて出力してください。このフォーマットを崩さないでください。\n\n【現代語訳】\n（ここに分かりやすい現代語訳を書く）\n===\n【解説】\n（ここに重要単語や文法、主語の補完理由などを箇条書きで書く）`,\n },\n {\n role: \"user\",\n content: kobunText,\n },\n ],\n temperature: 0.3,\n });\n\n const aiResponse = response.choices[0].message.content || \"\";\n\n // AIのレスポンスを「現代語訳」と「解説」に分解する\n let translatedText = \"翻訳に失敗しました。\";\n let analysisText = \"解説の生成に失敗しました。\";\n\n if (aiResponse.includes(\"===\")) {\n const parts = aiResponse.split(\"===\");\n translatedText = parts[0].replace(\"【現代語訳】\", \"\").trim();\n analysisText = parts[1].replace(\"【解説】\", \"\").trim();\n } else {\n translatedText = aiResponse;\n analysisText = \"詳細な文法解説は生成されませんでした。\";\n }\n\n // ⌚️ 日本時間（JST）の現在時刻を計算\n const nowJST = new Date(Date.now() + 9 * 60 * 60 * 1000)\n .toISOString()\n .replace(\"T\", \" \")\n .substring(0, 19);\n\n // データベースに結果を保存\n const dbResult = await sqlite.execute({\n sql:\n \"INSERT INTO kobun_history (source_text, translated_text, analysis_text, created_at) VALUES (:source, :trans, :analysis, :created)\",\n args: {\n source: kobunText,\n trans: translatedText,\n analysis: analysisText,\n created: nowJST,\n },\n });\n\n // 新しく生成された履歴のIDを取得して、その詳細結果画面へリダイレクト\n // 通常のラストインサートIDの取得（Val Town SQLite互換仕様）\n const newId = dbResult.lastInsertRowid\n ? dbResult.lastInsertRowid.toString()\n : \"1\";\n return c.redirect(`/history/${newId}`);\n } catch (e) {\n return c.text(`AI解読中にエラーが発生しました: ${e.message}`, 500);\n }\n});\n// 3. 個別の解読結果・履歴表示画面\napp.get(\"/history/:id\", async (c) => {\n const id = c.param(\"id\");\n\n const result = await sqlite.execute({\n sql:\n \"SELECT id, source_text, translated_text, analysis_text, created_at FROM kobun_history WHERE id = :id\",\n args: { id },\n });\n\n if (result.rows.length === 0) {\n return c.html(\n \n

指定された解読履歴が見つかりませんでした。

\n ← トップへ戻る\n

\n ,\n 404,\n );\n }\n\n const row = result.rows[0];\n const sourceIdx = result.columns.indexOf(\"source_text\");\n const transIdx = result.columns.indexOf(\"translated_text\");\n const analysisIdx = result.columns.indexOf(\"analysis_text\");\n const dateIdx = result.columns.indexOf(\"created_at\");\n\n return c.html(\n \n

\n 解読日時: {row[dateIdx]}\n\n

🔍 入力された古文

\n \n {row[sourceIdx]}\n

\n\n

✨ 現代語訳（AIによる主語補完あり）

\n \n {row[transIdx]}\n

\n\n

📖 重要単語・文法解説

\n {row[analysisIdx]}\n

\n\n ← トップ画面（履歴一覧）へ戻る\n

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