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.serena/.gitignore

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/cache

.serena/project.yml

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# language of the project (csharp, python, rust, java, typescript, go, cpp, or ruby)
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# * For C, use cpp
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# * For JavaScript, use typescript
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# Special requirements:
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# * csharp: Requires the presence of a .sln file in the project folder.
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language: typescript
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# whether to use the project's gitignore file to ignore files
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# Added on 2025-04-07
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# initial prompt for the project. It will always be given to the LLM upon activating the project
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# (contrary to the memories, which are loaded on demand).
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initial_prompt: ""
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# the name by which the project can be referenced within Serena
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project_name: "llm-ts-example"
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# list of mode names to that are always to be included in the set of active modes
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# The full set of modes to be activated is base_modes + default_modes.
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# If the setting is undefined, the base_modes from the global configuration (serena_config.yml) apply.
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# Otherwise, this setting overrides the global configuration.
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# Set this to [] to disable base modes for this project.
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# Set this to a list of mode names to always include the respective modes for this project.
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base_modes:
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# list of mode names that are to be activated by default.
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# The full set of modes to be activated is base_modes + default_modes.
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# If the setting is undefined, the default_modes from the global configuration (serena_config.yml) apply.
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# Otherwise, this overrides the setting from the global configuration (serena_config.yml).
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# This setting can, in turn, be overridden by CLI parameters (--mode).
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default_modes:
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# list of tools to include that would otherwise be disabled (particularly optional tools that are disabled by default)
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included_optional_tools: []
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# fixed set of tools to use as the base tool set (if non-empty), replacing Serena's default set of tools.
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# This cannot be combined with non-empty excluded_tools or included_optional_tools.
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fixed_tools: []
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# the encoding used by text files in the project
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# For a list of possible encodings, see https://docs.python.org/3.11/library/codecs.html#standard-encodings
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encoding: utf-8
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# list of languages for which language servers are started; choose from:
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# al bash clojure cpp csharp
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# csharp_omnisharp dart elixir elm erlang
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# fortran fsharp go groovy haskell
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# java julia kotlin lua markdown
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# matlab nix pascal perl php
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# powershell python python_jedi r rego
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# ruby ruby_solargraph rust scala swift
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# terraform toml typescript typescript_vts vue
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# yaml zig
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# (This list may be outdated. For the current list, see values of Language enum here:
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# https://github.com/oraios/serena/blob/main/src/solidlsp/ls_config.py
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# For some languages, there are alternative language servers, e.g. csharp_omnisharp, ruby_solargraph.)
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# Note:
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# - For C, use cpp
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# - For JavaScript, use typescript
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# - For Free Pascal/Lazarus, use pascal
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# Special requirements:
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# Some languages require additional setup/installations.
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# See here for details: https://oraios.github.io/serena/01-about/020_programming-languages.html#language-servers
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# When using multiple languages, the first language server that supports a given file will be used for that file.
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# The first language is the default language and the respective language server will be used as a fallback.
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# Note that when using the JetBrains backend, language servers are not used and this list is correspondingly ignored.
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languages:
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- typescript

README.md

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# llm-ts-example
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- [basic chat by LangChain.js with LangGraph.js](./basic/)
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- [RAG by LangChain.js with LangGraph.js](./rag/)
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- [Mastra](./agents/agent-mastra/)
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- [LangChain.js Agent](./agents/agent-langchain/)
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- [Claude Agent SDK](./agents/agent-sdk/)
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- [Strands TypeScript SDK](./agents/agent-strands/)
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- [VoltAgent](./agents/agent-voltagent/)
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LLM (Large Language Model) の実装例を集めたTypeScriptプロジェクトです。LangChain.js、LangGraph.js、Next.js、MCPなど様々なフレームワークとツールを使用したAIエージェントとアプリケーションの実装を紹介しています。
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## プロジェクト一覧
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### Basic Chat
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- [Basic Chat](./basic/) - LangChain.jsとLangGraph.jsを使用した基本的なチャットボット
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### RAG (Retrieval Augmented Generation)
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- [RAG](./rag/) - LangChain.jsとLangGraph.jsを使用したRAG実装例
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### Chat App
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- [Chat App](./chat-app/) - Next.jsとAI SDKを使用したチャットアプリケーション
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### Agents
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- [Mastra](./agents/agent-mastra/) - Mastraフレームワークによるエージェント実装
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- [LangChain.js Agent](./agents/agent-langchain/) - LangChain.jsによるエージェント実装
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- [LangChain.js Agent (Next.js)](./agents/agent-langchain-nextjs/) - Next.jsとLangChain.jsによるエージェント実装
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- [Claude Agent SDK](./agents/agent-sdk/) - Claude Agent SDKによるエージェント実装
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- [Strands TypeScript SDK](./agents/agent-strands/) - Strands TypeScript SDKによるエージェント実装
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### MCP (Model Context Protocol)
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- [MCP Servers](./mcp/servers/) - MCPサーバーの実装例
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- [Weather](./mcp/servers/weather/) - 天気予報MCPサーバー
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- [Weather HTTP](./mcp/servers/weather-http/) - HTTP経由の天気予報MCPサーバー
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- [MCP Clients](./mcp/clients/) - MCPクライアントの実装例
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- [TypeScript Client](./mcp/clients/mcp-client-typescript/) - TypeScriptによるMCPクライアント
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- [HTTP Client](./mcp/clients/mcp-client-http/) - HTTP経由のMCPクライアント
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### Common
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- [Common](./common/) - 共通ユーティリティとコンポーネント
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## 技術スタック
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- **言語**: TypeScript
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- **パッケージマネージャー**: pnpm
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- **LLM**: LangChain.js, LangGraph.js, AI SDK
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- **フロントエンド**: Next.js, Solid.js
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- **インフラ**: AWS CDK
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- **MCP**: Model Context Protocol SDK
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## 開発環境のセットアップ
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```bash
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pnpm install
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```
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## テスト
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```bash
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pnpm test
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```
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## リント
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```bash
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pnpm lint
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```
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This is a [Next.js](https://nextjs.org) project bootstrapped with [`create-next-app`](https://nextjs.org/docs/app/api-reference/cli/create-next-app).
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# LangChain.js Agent with Next.js
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## Getting Started
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LangChain.js、LangGraph.js、Next.jsを使用したAIエージェントアプリケーションです。
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First, run the development server:
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## 技術スタック
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- **Next.js 16** - Reactフレームワーク
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- **LangChain.js** - LLMアプリケーションフレームワーク
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- **LangGraph.js** - エージェントの状態管理
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- **AWS Bedrock** - LLMプロバイダー
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- **OpenInference** - OpenTelemetryトレーシング
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- **Radix UI** - UIコンポーネント
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- **Tailwind CSS** - スタイリング
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## セットアップ
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依存関係をインストールします:
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```bash
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npm run dev
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# or
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yarn dev
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# or
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pnpm dev
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# or
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bun dev
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pnpm install
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```
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Open [http://localhost:3000](http://localhost:3000) with your browser to see the result.
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## 開発サーバーの起動
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You can start editing the page by modifying `app/page.tsx`. The page auto-updates as you edit the file.
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This project uses [`next/font`](https://nextjs.org/docs/app/building-your-application/optimizing/fonts) to automatically optimize and load [Geist](https://vercel.com/font), a new font family for Vercel.
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```bash
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pnpm dev
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```
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## Learn More
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ブラウザで [http://localhost:3000](http://localhost:3000) を開いてアプリケーションを確認します。
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To learn more about Next.js, take a look at the following resources:
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## ビルド
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- [Next.js Documentation](https://nextjs.org/docs) - learn about Next.js features and API.
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- [Learn Next.js](https://nextjs.org/learn) - an interactive Next.js tutorial.
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```bash
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pnpm build
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```
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You can check out [the Next.js GitHub repository](https://github.com/vercel/next.js) - your feedback and contributions are welcome!
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## 本番環境での実行
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## Deploy on Vercel
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```bash
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pnpm start
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```
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The easiest way to deploy your Next.js app is to use the [Vercel Platform](https://vercel.com/new?utm_medium=default-template&filter=next.js&utm_source=create-next-app&utm_campaign=create-next-app-readme) from the creators of Next.js.
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## リント
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Check out our [Next.js deployment documentation](https://nextjs.org/docs/app/building-your-application/deploying) for more details.
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```bash
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pnpm lint
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```

basic/app/README.md

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# solid-frame-poku-example
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# Basic Chatbot App
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## Farm + Solid
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LangChain.jsを使用した基本的なチャットボットアプリケーションです。
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This template should help you start developing using Solid and TypeScript in Farm.
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## セットアップ
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### Setup
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Install the dependencies:
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依存関係をインストールします:
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```bash
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pnpm install
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```
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### Get Started
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Start the dev server:
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## 開発サーバーの起動
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```bash
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pnpm start
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```
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Build the app for production:
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## ビルド
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```bash
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pnpm build
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```
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Preview the Production build product:
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## プレビュー
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```bash
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pnpm preview
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```
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Clear persistent cache local files
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## テスト
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```bash
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pnpm test
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```
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## リント
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```bash
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pnpm clean
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pnpm lint
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pnpm lint-fix
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```
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## 機能
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- 基本的なチャットインターフェース
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- LangChain.jsを使用したLLM統合
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- Solid.jsによるリアクティブUI
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## 技術スタック
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- **Solid.js** - リアクティブUIフレームワーク
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- **TypeScript** - プログラミング言語
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- **Vite** - ビルドツール
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- **LangChain.js** - LLMアプリケーションフレームワーク

chat-app/README.md

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This is a [Next.js](https://nextjs.org) project bootstrapped with [`create-next-app`](https://nextjs.org/docs/app/api-reference/cli/create-next-app).
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# Chat App with AI SDK
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## Getting Started
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Next.jsとAI SDKを使用したチャットアプリケーションです。
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First, run the development server:
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## 技術スタック
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- **Next.js 16** - Reactフレームワーク
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- **AI SDK** - Vercel AI SDK
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- **Amazon Bedrock** - LLMプロバイダー
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- **Radix UI** - UIコンポーネント
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- **Tailwind CSS** - スタイリング
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- **Zod** - データバリデーション
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## セットアップ
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依存関係をインストールします:
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```bash
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npm run dev
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# or
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yarn dev
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# or
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pnpm dev
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# or
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bun dev
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pnpm install
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```
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Open [http://localhost:3000](http://localhost:3000) with your browser to see the result.
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環境変数を設定します:
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You can start editing the page by modifying `app/page.tsx`. The page auto-updates as you edit the file.
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`.env.local` ファイルを作成し、以下の環境変数を設定してください:
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This project uses [`next/font`](https://nextjs.org/docs/app/building-your-application/optimizing/fonts) to automatically optimize and load [Geist](https://vercel.com/font), a new font family for Vercel.
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```env
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AWS_REGION=your-region
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AWS_ACCESS_KEY_ID=your-access-key
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AWS_SECRET_ACCESS_KEY=your-secret-key
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```
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## 開発サーバーの起動
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```bash
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pnpm dev
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```
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## Learn More
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ブラウザで [http://localhost:3000](http://localhost:3000) を開いてアプリケーションを確認します。
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To learn more about Next.js, take a look at the following resources:
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## ビルド
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- [Next.js Documentation](https://nextjs.org/docs) - learn about Next.js features and API.
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- [Learn Next.js](https://nextjs.org/learn) - an interactive Next.js tutorial.
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```bash
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pnpm build
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```
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You can check out [the Next.js GitHub repository](https://github.com/vercel/next.js) - your feedback and contributions are welcome!
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## 本番環境での実行
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## Deploy on Vercel
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```bash
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pnpm start
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```
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The easiest way to deploy your Next.js app is to use the [Vercel Platform](https://vercel.com/new?utm_medium=default-template&filter=next.js&utm_source=create-next-app&utm_campaign=create-next-app-readme) from the creators of Next.js.
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## リント
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Check out our [Next.js deployment documentation](https://nextjs.org/docs/app/building-your-application/deploying) for more details.
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```bash
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pnpm lint
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pnpm lint-fix
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```
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# MPC HTTP Client with Amazon Bedrock by TypeScript
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# HTTP MCP Client with Amazon Bedrock
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## run
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HTTP経由でMCPサーバーと通信するAmazon Bedrockクライアントです。
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```shell
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## セットアップ
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依存関係をインストールします:
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```bash
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pnpm -r build
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```
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## 実行
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Weather HTTPサーバーとHTTP MCPクライアントを並行して実行します:
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```bash
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pnpm -r --parallel --filter weather-http --filter mcp-client-http start
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```
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## 機能
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- HTTP経由のMCPサーバー通信
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- Amazon Bedrockとの統合
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- 並行実行による効率的な開発
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## 技術スタック
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- **TypeScript** - プログラミング言語
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- **MCP SDK** - Model Context Protocol SDK
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- **Amazon Bedrock SDK** - AWS SDK for JavaScript
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- **pnpm workspaces** - モノレpo管理

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