feat: initial commit

.gitignore

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+.venv
+__pycache__

app.py

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+import gradio as gr
+from Levenshtein import ratio
+import json
+
+data_path = "./data.json"
+
+with open(data_path, "r") as f:
+    documents_data = json.load(f)
+
+def search_similar_texts(query, top_n=5):
+    # クエリをベクトル化
+    results = []
+
+    for doc in documents_data:
+
+        score = ratio(query, doc["text"])
+        results.append({
+            "vol": doc["vol"],
+            "page": doc["page"],
+            "score": score,
+            "text": doc["text"]
+        })
+        # print(score)
+
+    results.sort(key=lambda x: x["score"], reverse=True)
+    
+    return results[:top_n]
+
+# Gradioインターフェースの作成
+demo = gr.Interface(
+    fn=search_similar_texts,
+    inputs=[
+        gr.Textbox(label="検索テキスト", placeholder="検索したいテキストを入力してください"),
+        gr.Slider(minimum=1, maximum=10, value=5, step=1, label="表示件数")
+    ],
+    outputs=gr.JSON(),
+    title="校異源氏物語 類似テキスト検索",
+    description="テキストを入力すると、校異源氏物語の類似する箇所を検索します。",
+    allow_flagging="never",
+)
+
+# インターフェースの起動
+demo.launch()

requirements.txt

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+levenshtein
+gradio

src/01_create_data.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from glob import glob\n",
+    "import xml.etree.ElementTree as ET\n",
+    "import json"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "files = glob(\"../../kouigenjimonogatari.github.io/xml/lw/*.xml\")\n",
+    "files.sort()\n",
+    "data = []\n",
+    "\n",
+    "for file in files:\n",
+    "    tree = ET.parse(file)\n",
+    "    root = tree.getroot()\n",
+    "\n",
+    "    vol = int(file.split(\"/\")[-1].split(\".\")[0])\n",
+    "    segs = root.findall(\".//{http://www.tei-c.org/ns/1.0}seg\")\n",
+    "    texts = {}\n",
+    "\n",
+    "    for seg in segs:        \n",
+    "        corresp = seg.attrib[\"corresp\"]\n",
+    "        page = int(corresp.split(\"/\")[-1].split(\"-\")[0])\n",
+    "        text = seg.text\n",
+    "\n",
+    "        if page not in texts:\n",
+    "            texts[page] = []\n",
+    "\n",
+    "        texts[page].append(text)\n",
+    "\n",
+    "    for page in texts:\n",
+    "        text = \" \".join(texts[page])\n",
+    "        data.append({\"vol\": vol, \"page\": page, \"text\": text})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open(\"../data.json\", \"w\") as f:\n",
+    "    json.dump(data, f, ensure_ascii=False, indent=4)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}