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Pinecone ベクトル検索 API\n\nこのプロジェクトは、Pineconeを使用したベクトル類似度検索APIを提供します。FastAPIフレームワークを使用して構築され、高性能なベクトル検索機能を実現します。\n\n## 概要\n\nこのAPIサービスは、テキスト埋め込み、画像特徴量、または任意の数値ベクトルに対して、高速で正確な類似度検索を提供します。Pineconeのサーバーレスインフラストラクチャを活用し、スケーラブルな検索機能を実現しています。\n\n## セットアップ\n\n### 前提条件\n\n- Python 3.8以上\n- Pinecone アカウントとAPI キー\n\n### インストール手順\n\n1. リポジトリをクローンします：\n```bash\ngit clone [リポジトリURL]\ncd handson-pinecone\n```\n\n2. 必要なパッケージをインストールします：\n```bash\npip install -r requirements.txt\n```\n\n3. 環境変数を設定します：\n`.env`ファイルを作成し、以下の内容を追加します：\n```\nPINECONE_API_KEY=your_api_key_here\n```\n\n### 初期設定\n\nインデックスを作成するには、以下のスクリプトを実行します：\n```bash\npython quick-start.py\n```\n\n## 主な機能\n\n- **ベクトルデータの追加・更新** (`/upsert`)\n- **類似ベクトル検索** (`/search`)\n- **インデックス状態の確認** (`/status`)\n\n## APIエンドポイント\n\n### 1. ベクトル検索 `/search`\n- **メソッド**: POST\n- **説明**: クエリベクトルに最も類似したベクトルを検索\n- **リクエスト例**:\n```json\n{\n    \"query_vector\": [0.1, 0.2]\n}\n```\n\n### 2. ベクトル追加 `/upsert`\n- **メソッド**: POST\n- **説明**: 新しいベクトルデータをインデックスに追加\n\n### 3. ステータス確認 `/status`\n- **メソッド**: GET\n- **説明**: インデックスの状態と統計情報を取得\n\n## 使用例\n\n### APIサーバーの起動\n```bash\nuvicorn main:app --reload\n```\n\n### Swagger UIへのアクセス\nAPIサーバー起動後、以下のURLでSwagger UIにアクセスできます：\n```\nhttp://localhost:8000/docs\n```\n\n## 利用シーン\n\n- 類似文書検索システム\n- 画像類似度検索\n- レコメンデーションシステム\n- セマンティック検索エンジン\n\n## 技術スタック\n\n- FastAPI\n- Pinecone\n- Python 3.8+\n- uvicorn\n- pydantic\n\n## 注意事項\n\n- 本番環境での使用前に、適切なセキュリティ設定を行ってください\n- Pineconeの利用料金に注意してください\n- ベクトルのディメンション数は2に設定されています（テスト用）\n\n## ライセンス\n\nこのプロジェクトはMITライセンスの下で公開されています。\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftimeless-residents%2Fhandson-pinecone","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftimeless-residents%2Fhandson-pinecone","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftimeless-residents%2Fhandson-pinecone/lists"}