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AIエージェント のサーバー向け SDK です。","maintainers":[{"name":"ss-ravi","email":"ravi.souza@super-studio.jp"},{"name":"ss-saitho","email":"shinsuke.saito@super-studio.jp"},{"name":"satoru.kikuchi","email":"satoru.kikuchi@super-studio.jp"},{"name":"kmurakami","email":"murakami@super-studio.jp"},{"name":"rkawabata","email":"ryosuke.kawabata@super-studio.jp"},{"name":"spst-ryo","email":"ryo.nakagawa@super-studio.jp"},{"name":"hiroaki-murase","email":"hiroaki.murase@super-studio.jp"},{"name":"ss-aimori","email":"ai.mori@super-studio.jp"}],"readme":"# `@super_studio/ecforce-ai-agent-server`\n\necforce AIエージェント のサーバー向け SDK です。\n\n主に次の 2 つを提供します。\n\n- API SDK: `createClient()` で AI Agent の内部 API を呼ぶ\n- Proxy provider: `spst()` で Vercel AI SDK から内部プロキシ経由でモデルを使う\n\n## インストール\n\n```bash\npnpm add @super_studio/ecforce-ai-agent-server\n```\n\n`spst()` は Vercel AI SDK と一緒に使います。\n\n```bash\npnpm add ai\n```\n\nGoogle Search などで `@ai-sdk/google-vertex` のツールも使う場合は追加で入れてください。\n\n```bash\npnpm add @ai-sdk/google-vertex\n```\n\n## 環境変数\n\n通常は `AI_AGENT_API_KEY` だけ設定すれば動きます。\n\n```env\nAI_AGENT_API_KEY=your-api-key\n```\n\ndev / preview 環境へ向けたい場合だけ、接続先を上書きします。\n\n```env\nAI_AGENT_API_ENDPOINT=https://dev-agent.ec-force.com\n```\n\n- `AI_AGENT_API_KEY`: 必須。管理画面で発行した API キー\n- `AI_AGENT_API_ENDPOINT`: 任意。省略時は本番 `https://agent.ec-force.com`\n\n## 使い分け\n\n### `createClient()`\n\n内部 API を直接呼びたいときに使います。\n\n用途:\n\n- AI Agent セッション発行\n- 管理用の内部 API 呼び出し\n- 利用量サマリー取得\n\n### `spst()`\n\nVercel AI SDK の `generateText()` / `streamText()` などから、ecforce AIエージェント の proxy provider を使いたいときに使います。\n\n用途:\n\n- OpenAI / Google / Anthropic を内部プロキシ経由で呼ぶ\n- `projectId` / `email` / `callerApp` をヘッダーに載せて課金・利用元を紐付ける\n- アプリ側から AI SDK のままテキスト生成やストリームを実行する\n\n## API SDK\n\n### `createClient()` の基本\n\n```ts\nimport { createClient } from \"@super_studio/ecforce-ai-agent-server\";\n\nconst client = createClient();\n```\n\n必要なら API キーや接続先を明示できます。\n\n```ts\nimport { createClient } from \"@super_studio/ecforce-ai-agent-server\";\n\nconst client = createClient({\n  apiKey: process.env.AI_AGENT_API_KEY,\n  baseUrl: process.env.AI_AGENT_API_ENDPOINT,\n});\n```\n\n### AI Agent セッションを発行する\n\nReact パッケージの `ChatbotSheet` / `ChatbotFrame` に渡すセッションは、通常この SDK で発行します。\n\n```ts\nimport { NextResponse } from \"next/server\";\nimport { createClient } from \"@super_studio/ecforce-ai-agent-server\";\n\nconst client = createClient();\n\nexport async function POST() {\n  const currentUser = {\n    email: \"user@example.com\",\n    projectId: \"project_123\",\n  };\n\n  const session = await client.internalChat.createSession({\n    email: currentUser.email,\n    projectId: currentUser.projectId,\n  });\n\n  return NextResponse.json(session);\n}\n```\n\n返り値は次の形です。\n\n```ts\ntype AgentSession = {\n  token: string;\n  expiresAt: string;\n};\n```\n\n### 外部アプリで利用規約の同意を管理する\n\n利用規約は `https://agent.ec-force.com/terms` で公開されています。外部アプリでは、このページへのリンクを表示してから同意を記録してください。\n\n`status` は未登録ユーザーでも `accepted: false` を返します。Accounts API を呼ばずに同意状況だけ確認できます。\n\n```ts\nconst terms = await client.internalTerms.status({\n  email: \"user@example.com\",\n  projectId: \"project_123\",\n});\n\nif (!terms.accepted) {\n  // 利用規約へのリンクと同意チェックボックスを表示\n}\n```\n\nユーザーが同意したら、次の API で記録します。未登録ユーザーも同時に作成する場合だけ `createIfMissing: true` を指定してください。\n\n```ts\nawait client.internalTerms.accept({\n  email: \"user@example.com\",\n  projectId: \"project_123\",\n  createIfMissing: true,\n});\n```\n\nユーザー情報も必要な場合は `resolve` を使います。`createIfMissing` の既定値は `false` です。\n\n```ts\nconst user = await client.internalUser.resolve({\n  email: \"user@example.com\",\n  projectId: \"project_123\",\n  createIfMissing: true,\n});\n\nconsole.log(user.role, user.plan, user.termsAcceptedAt);\n```\n\n`accept` / `resolve` で存在しないユーザーに `createIfMissing: false` を指定すると、`NOT_FOUND` エラーになります。ユーザー作成時は既存のルールに従い、有料プロジェクトでは Accounts に登録済みのメールアドレスだけ作成できます。\n\n### 内部 usage summary を取得する\n\n内部 API の利用例として、`/v1/internal/usage/summary` に対応する usage summary 取得は次のように呼べます。\n\n```ts\nimport { createClient } from \"@super_studio/ecforce-ai-agent-server\";\n\nconst client = createClient();\n\nconst summary = await client.internalUsage.getUsageSummary({\n  projectId: \"project_123\",\n  period: \"2026-04\",\n});\n\nconsole.log(summary);\n/*\n{\n  plan: \"pro\",\n  totalUsedCredits: 12345,\n  creditLimit: 50000,\n  remainingCredits: 37655,\n  billingPeriod: \"2026-04\"\n}\n*/\n```\n\n`period` を省略すると、サーバー側の現在 billing period が使われます。\n\n想定用途:\n\n- 自社管理画面で利用量サマリーを表示する\n- `spst()` 経由の利用量を含めた残クレジットを確認する\n- 定期ジョブや監視でプロジェクトごとの消費量を取る\n\n## Proxy Provider\n\nProxy Provider を利用するアプリは、対応する AI SDK を直接インストールしてください。\n\n```bash\npnpm add @ai-sdk/anthropic @ai-sdk/google-vertex @ai-sdk/openai @ai-sdk/provider\n```\n\n`spst()` は `@super_studio/ecforce-ai-agent-server/provider` から import します。\n\n```ts\nimport { spst } from \"@super_studio/ecforce-ai-agent-server/provider\";\n```\n\n### 最小例\n\n```ts\nimport { generateText } from \"ai\";\nimport { spst } from \"@super_studio/ecforce-ai-agent-server/provider\";\n\nconst result = await generateText({\n  model: spst(\"openai/gpt-5.4\"),\n  prompt: \"売上の改善案を3つ提案して\",\n  providerOptions: {\n    spst: {\n      projectId: \"project_123\",\n      email: \"user@example.com\",\n      callerApp: \"admin-dashboard\",\n    },\n  },\n});\n\nconsole.log(result.text);\nconsole.log(result.usage);\n```\n\n`providerOptions.spst` は内部利用時の識別情報です。\n\n- `projectId`: どのプロジェクトの利用か\n- `email`: 誰の利用か\n- `callerApp`: どのアプリからの利用か\n\n通常の内部利用では、この 3 つを毎回渡してください。\n\n### モデル ID の形式\n\n`spst()` は provider 付きの model id を受け取ります。\n\n```ts\nspst(\"openai/gpt-5.4\");\nspst(\"google/gemini-2.5-flash\");\nspst(\"anthropic/claude-sonnet-4-6\");\n```\n\n現状サポートしている prefix は次です。\n\n- `openai/`\n- `google/`\n- `anthropic/`\n\n### `callerApp` を固定した provider を作る\n\n同じアプリから何度も呼ぶなら `createSpstProvider()` が便利です。\n\n```ts\nimport { generateText } from \"ai\";\nimport { createSpstProvider } from \"@super_studio/ecforce-ai-agent-server/provider\";\n\nconst provider = createSpstProvider({\n  callerApp: \"admin-dashboard\",\n});\n\nconst result = await generateText({\n  model: provider(\"google/gemini-2.5-flash\"),\n  prompt: \"今月の広告成果を要約して\",\n  providerOptions: {\n    spst: {\n      projectId: \"project_123\",\n      email: \"user@example.com\",\n    },\n  },\n});\n```\n\nこの場合、`callerApp` は `createSpstProvider()` 側の値が使われます。\n\n必要なら API キーや接続先もここで上書きできます。\n\n```ts\nimport { createSpstProvider } from \"@super_studio/ecforce-ai-agent-server/provider\";\n\nconst provider = createSpstProvider({\n  apiKey: process.env.AI_AGENT_API_KEY,\n  baseUrl: process.env.AI_AGENT_API_ENDPOINT,\n  callerApp: \"admin-dashboard\",\n});\n```\n\n### ストリーミング\n\n`streamText()` でも同じです。\n\n```ts\nimport { streamText } from \"ai\";\nimport { spst } from \"@super_studio/ecforce-ai-agent-server/provider\";\n\nconst result = streamText({\n  model: spst(\"openai/gpt-5.4-mini\"),\n  prompt: \"FAQ の草案を作成して\",\n  providerOptions: {\n    spst: {\n      projectId: \"project_123\",\n      email: \"user@example.com\",\n      callerApp: \"admin-dashboard\",\n    },\n  },\n});\n```\n\n### エラーハンドリング\n\nユーザーが未登録、または利用規約に未同意の場合、プロキシは判別可能なエラーコードを返します。\n\n| HTTP | `error.code` | 意味 |\n| --- | --- | --- |\n| 404 | `user_not_found` | 指定したプロジェクトにユーザーが存在しない |\n| 403 | `terms_not_accepted` | ユーザーが利用規約に同意していない |\n\n```ts\nimport { APICallError } from \"ai\";\n\nfunction isTermsNotAcceptedError(error: unknown) {\n  return (\n    APICallError.isInstance(error) &&\n    error.statusCode === 403 &&\n    error.responseBody?.includes(\"terms_not_accepted\") === true\n  );\n}\n```\n\nクレジット上限に達すると、プロキシは **429** を返します。\n\n```json\n{\n  \"error\": {\n    \"message\": \"Credit limit exceeded.\",\n    \"type\": \"rate_limit_error\",\n    \"code\": \"credit_limit_exceeded\"\n  }\n}\n```\n\nVercel AI SDK では、このエラーは `APICallError` として扱われます。`generateText` と `streamText` で受け取り方が異なる点に注意してください。\n\n#### `generateText`\n\n`generateText()` 自体が throw します。\n\n```ts\nimport { APICallError, generateText } from \"ai\";\nimport { createSpstProvider } from \"@super_studio/ecforce-ai-agent-server/provider\";\n\nconst provider = createSpstProvider({ callerApp: \"admin-dashboard\" });\n\ntry {\n  await generateText({\n    model: provider(\"openai/gpt-5.4\"),\n    prompt: \"売上の改善案を3つ提案して\",\n    maxRetries: 0,\n    providerOptions: {\n      spst: {\n        projectId: \"project_123\",\n        email: \"user@example.com\",\n      },\n    },\n  });\n} catch (error) {\n  if (isCreditLimitError(error)) {\n    // 例: UI に「クレジット上限に達しました」を表示\n    return;\n  }\n\n  throw error;\n}\n\nfunction isCreditLimitError(error: unknown) {\n  return (\n    APICallError.isInstance(error) &&\n    error.statusCode === 429 &&\n    error.responseBody?.includes(\"credit_limit_exceeded\") === true\n  );\n}\n```\n\n#### `streamText`\n\n`streamText()` の HTTP エラーは `onError` で受け取ります。`await result.text` 側で credit limit を判定する必要はありません。\n\n```ts\nimport { APICallError, streamText } from \"ai\";\nimport { createSpstProvider } from \"@super_studio/ecforce-ai-agent-server/provider\";\n\nconst provider = createSpstProvider({ callerApp: \"admin-dashboard\" });\n\nconst result = streamText({\n  model: provider(\"openai/gpt-5.4-mini\"),\n  prompt: \"FAQ の草案を作成して\",\n  maxRetries: 0,\n  providerOptions: {\n    spst: {\n      projectId: \"project_123\",\n      email: \"user@example.com\",\n    },\n  },\n  onError: ({ error }) => {\n    if (isCreditLimitError(error)) {\n      // 例: UI に「クレジット上限に達しました」を表示\n      return;\n    }\n\n    console.error(error);\n  },\n});\n\nreturn result.toUIMessageStreamResponse();\n```\n\n### Google Search tool を併用する\n\nGoogle 系モデルでは、AI SDK 側のツールを組み合わせて使えます。\n\n```ts\nimport { vertex } from \"@ai-sdk/google-vertex\";\nimport { generateText } from \"ai\";\nimport { spst } from \"@super_studio/ecforce-ai-agent-server/provider\";\n\nconst result = await generateText({\n  model: spst(\"google/gemini-3.5-flash\"),\n  prompt: \"今日の生成AI関連ニュースを3件まとめて\",\n  tools: {\n    google_search: vertex.tools.googleSearch({}),\n  },\n  providerOptions: {\n    spst: {\n      projectId: \"project_123\",\n      email: \"user@example.com\",\n      callerApp: \"admin-dashboard\",\n    },\n  },\n});\n```\n","readmeFilename":"README.md"}