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[BizRouter](https://bizrouter.ai/) provider for the [Vercel AI SDK](https://sdk.vercel.ai/docs) provides access to multiple large language models (OpenAI, Anthropic, Google Gemini, xAI Grok) through the BizRouter API gateway, optimized for the Korean ","maintainers":[{"name":"xrath","email":"rath@xrath.com"},{"name":"ai3inc","email":"contact@ai3.kr"}],"readme":"# BizRouter Provider for Vercel AI SDK\n\nThe [BizRouter](https://bizrouter.ai/) provider for the [Vercel AI SDK](https://sdk.vercel.ai/docs) provides access to multiple large language models (OpenAI, Anthropic, Google Gemini, xAI Grok) through the BizRouter API gateway, optimized for the Korean market.\n\n## Requirements\n\n| Provider version | AI SDK (`ai`) | Node.js | Module format |\n|---|---|---|---|\n| **2.x** (current) | `^7.0.0` | >= 22 | ESM only |\n| 1.x (maintenance) | `^5.0.0` | >= 18 | ESM + CJS |\n\n### Breaking changes in 2.0.0\n\n- Implements the AI SDK **LanguageModelV4** provider specification; requires `ai@^7`.\n- **ESM only** — `require()` is no longer supported.\n- Node.js **22 or later** is required.\n- The deprecated `BizRouter` facade class was removed — use `createBizRouter()`.\n- Token usage follows the V4 nested shape (`usage.inputTokens.total`, `usage.outputTokens.reasoning`, ...).\n- `providerMetadata.bizrouter.usage` (KRW cost tracking) is **unchanged**.\n\n### Fixes up to 2.1.3\n\nUpgrade to the latest 2.1.x; each fix names the release that shipped it.\n\n- **Response validation.** Shapes that some models send no longer fail with\n  `AI_TypeValidationError`:\n  - a `completion_tokens_details` / `prompt_tokens_details` object without its\n    counter (e.g. `\"completion_tokens_details\": {}` on\n    `bizrouter/glm-5.3-flash`). Missing counters are `undefined` in `usage` and\n    `0` in `providerMetadata.bizrouter.usage` (2.1.1);\n  - an explicit `\"delta\": { \"role\": null }` after the first stream chunk (tool\n    calls of `bizrouter/deepseek-v4.1-flash`). Those chunks used to become\n    error parts, so `streamText()` finished with `finishReason: 'tool-calls'`\n    but no tool calls (2.1.2);\n  - a `null` top-level `id` / `model` / `provider`, or a tool call without a\n    `type`, matching `@ai-sdk/openai-compatible` (2.1.3).\n- **Reasoning.** `message.reasoning_content` (DeepSeek / GLM spelling, e.g.\n  `bizrouter/glm-5.3`) is mapped to `result.reasoning` / `result.reasoningText`\n  alongside `reasoning` and `reasoning_details`, and a top-level\n  `usage.reasoning_tokens` fills `usage.outputTokens.reasoning` (2.1.1).\n- **Completion model.** `bizrouter.completion()` works with `generateText()` /\n  `streamText()` again. AI SDK 7 sends `toolChoice: { type: 'auto' }` on every\n  call, and since 2.0.0 the model rejected it with\n  `AI_UnsupportedFunctionalityError`. Passing `tools` is still rejected (2.1.3).\n\n## Setup\n\n```bash\n# For bun\nbun add @bizrouter/ai-sdk-provider\n\n# For pnpm\npnpm add @bizrouter/ai-sdk-provider\n\n# For npm\nnpm install @bizrouter/ai-sdk-provider\n```\n\n## Provider Instance\n\nYou can import the default provider instance `bizrouter` from `@bizrouter/ai-sdk-provider`:\n\n```ts\nimport { bizrouter } from '@bizrouter/ai-sdk-provider';\n```\n\n## Example\n\n```ts\nimport { bizrouter } from '@bizrouter/ai-sdk-provider';\nimport { generateText } from 'ai';\n\nconst { text } = await generateText({\n  model: bizrouter('anthropic/claude-sonnet-5'),\n  prompt: 'Write a vegetarian lasagna recipe for 4 people.',\n});\n```\n\n## Configuration\n\nSet your BizRouter API key:\n\n```bash\nexport BIZROUTER_API_KEY=\"sk-br-v1-your-api-key\"\n```\n\nOr pass it directly:\n\n```ts\nimport { createBizRouter } from '@bizrouter/ai-sdk-provider';\n\nconst bizrouter = createBizRouter({\n  apiKey: 'sk-br-v1-your-api-key',\n  // Optional: Override the base URL\n  baseURL: 'https://api.bizrouter.ai/ai-sdk',\n});\n```\n\n### Authentication\n\nThe AI SDK Provider uses standard Bearer token authentication:\n- Endpoint: `https://api.bizrouter.ai/ai-sdk/*`\n- Header: `Authorization: Bearer sk-br-v1-your-api-key`\n\n## Features\n\n- **Streaming Support**: Real-time text generation with SSE\n- **Function Calling**: Tool use and parallel function calling\n- **Multimodal**: Image analysis and generation\n- **Video Generation**: Google Veo 3.1 and Gemini Omni Flash via `/video` helpers\n- **Usage Tracking**: Token usage and cost tracking (in KRW)\n- **Reasoning Support**: Access to model reasoning process (`reasoning`, `reasoning_content`, and `reasoning_details` response shapes)\n- **Provider Routing**: Automatic failover and load balancing\n\n## Supported Models\n\nBizRouter provides access to models from multiple providers. Visit [BizRouter Models](https://bizrouter.ai/models) for the complete and up-to-date list.\n\n### Popular Models\n- **OpenAI**: `openai/gpt-5.5`, `openai/gpt-5.5-pro`, `openai/gpt-5.4-mini`\n- **Anthropic**: `anthropic/claude-fable-5`, `anthropic/claude-opus-4.8`, `anthropic/claude-sonnet-5`, `anthropic/claude-haiku-4.5`\n- **Google**: `google/gemini-3.5-flash`, `google/gemini-3.1-pro-preview`, `google/gemini-3.1-flash-lite`\n- **xAI**: `x-ai/grok-4.3`, `x-ai/grok-4.20`\n- **Perplexity**: `perplexity/sonar-pro`, `perplexity/sonar-deep-research`\n\n## Streaming with Usage Tracking\n\n```typescript\nimport { bizrouter } from '@bizrouter/ai-sdk-provider';\nimport { streamText } from 'ai';\n\nconst { textStream, usage } = await streamText({\n  model: bizrouter('anthropic/claude-sonnet-5'),\n  prompt: 'Tell me about Seoul.',\n});\n\nfor await (const chunk of textStream) {\n  console.log(chunk);\n}\n\n// Get usage after streaming completes\nconst finalUsage = await usage;\nconsole.log('Input tokens:', finalUsage.inputTokens);\nconsole.log('Output tokens:', finalUsage.outputTokens);\nconsole.log('Total tokens:', finalUsage.totalTokens);\n```\n\n## Advanced Streaming Features\n\nGet detailed metadata and performance metrics from streaming responses:\n\n```typescript\nimport { bizrouter } from '@bizrouter/ai-sdk-provider';\nimport { streamText } from 'ai';\n\nconst { textStream, usage, finishReason, response } = await streamText({\n  model: bizrouter('openai/gpt-5.5'),\n  messages: [\n    {\n      role: 'system',\n      content: 'You are a helpful assistant.',\n    },\n    {\n      role: 'user',\n      content: 'What are the top 3 attractions in Seoul?',\n    },\n  ],\n  maxOutputTokens: 1000,\n});\n\n// Track streaming progress\nlet chunkCount = 0;\nlet fullText = '';\nconst startTime = Date.now();\n\nfor await (const chunk of textStream) {\n  process.stdout.write(chunk);\n  fullText += chunk;\n  chunkCount++;\n}\n\nconst duration = (Date.now() - startTime) / 1000;\n\n// Get response metadata\nconst metadata = await response;\nconsole.log(`Request ID: ${metadata.id}`);\nconsole.log(`Model used: ${metadata.modelId}`);\nconsole.log(`Timestamp: ${metadata.timestamp}`);\n\n// Get streaming statistics\nconsole.log(`Total chunks: ${chunkCount}`);\nconsole.log(`Streaming duration: ${duration.toFixed(2)}s`);\nconsole.log(`Characters per second: ${(fullText.length / duration).toFixed(0)}`);\n\n// Get finish reason\nconst reason = await finishReason;\nconsole.log(`Finish reason: ${reason}`);\n```\n\n## Tool Calling\n\n```typescript\nimport { bizrouter } from '@bizrouter/ai-sdk-provider';\nimport { generateText, jsonSchema } from 'ai';\n\nconst result = await generateText({\n  model: bizrouter('openai/gpt-5.5'),\n  prompt: '서울과 부산의 현재 날씨가 어떤지 알려줘.',\n  tools: {\n    getWeather: {\n      description: 'Get the current weather in a location',\n      inputSchema: jsonSchema({\n        type: 'object',\n        properties: {\n          location: {\n            type: 'string',\n            description: 'The city name, e.g. Seoul',\n          },\n        },\n        required: ['location'],\n      }),\n      execute: async ({ location }) => {\n        console.log(`getWeather tool executed with location: ${location}`);\n        // Your implementation here\n        return {\n          location,\n          temperature: 20,\n          condition: 'sunny',\n          unit: 'celsius',\n        };\n      },\n    },\n  },\n});\n\n// Extract text response from the last step\nconst lastStep = result.steps[result.steps.length - 1];\nconst textContent = lastStep.content.find(c => c.type === 'text');\nconsole.log(textContent?.text);\n\n// Extract tool calls from steps\nfor (const step of result.steps) {\n  const toolCalls = step.content.filter(c => c.type === 'tool-call');\n  for (const call of toolCalls) {\n    console.log(`Tool called: ${call.toolName}(${JSON.stringify(call.input)})`);\n  }\n}\n```\n\n## Image Generation\n\nBizRouter supports image generation through multimodal models like Google Gemini's image generation models.\n\n### Basic Image Generation\n\n```typescript\nimport { bizrouter } from '@bizrouter/ai-sdk-provider';\nimport { generateText } from 'ai';\nimport { extractImages } from '@bizrouter/ai-sdk-provider/image';\n\nconst result = await generateText({\n  model: bizrouter('google/gemini-3.1-flash-image'),\n  prompt: 'Draw a cute cat wearing a party hat',\n});\n\n// Extract images from the result\nconst { images, text } = extractImages(result);\n\nconsole.log('Description:', text);\n\nfor (const image of images) {\n  console.log(`Image type: ${image.mediaType}`);\n  console.log(`Image size: ${image.uint8Array.length} bytes`);\n\n  // Save to file (Node.js)\n  const fs = await import('fs/promises');\n  await fs.writeFile('cat.png', image.uint8Array);\n}\n```\n\n### Supported Image Generation Models\n\n| Model | Description | Max Resolution |\n|-------|-------------|----------------|\n| `google/gemini-2.5-flash-image` | Fast image generation | 1K |\n| `google/gemini-3.1-flash-image` | Fast image generation | 2K |\n| `google/gemini-3-pro-image` | High-quality image generation | 4K |\n\n### Image Generation Options\n\nGemini image models support optional configuration for aspect ratio and resolution.\n\n**Aspect Ratios** (all models):\n- `1:1`, `2:3`, `3:2`, `3:4`, `4:3`, `4:5`, `5:4`, `9:16`, `16:9`, `21:9`\n\n**Image Sizes** (Gemini 3 Pro only):\n- `1K` (default), `2K`, `4K`\n\n> **Note**: Use uppercase 'K' only (e.g., `2K` not `2k`).\n\n```typescript\nconst result = await generateText({\n  model: bizrouter('google/gemini-3-pro-image'),\n  prompt: 'A beautiful landscape',\n  providerOptions: {\n    bizrouter: {\n      aspect_ratio: '16:9',\n      image_size: '2K',\n    },\n  },\n});\n```\n\n### Image Data Formats\n\nThe `extractImages` function returns images in multiple formats:\n\n```typescript\ninterface GeneratedImage {\n  // Base64-encoded image data (without data URI prefix)\n  base64: string;\n\n  // Binary data for direct file operations\n  uint8Array: Uint8Array;\n\n  // MIME type (e.g., 'image/png', 'image/jpeg')\n  mediaType: string;\n}\n```\n\n### Image-to-Image Generation\n\nUse a reference image along with a text prompt to transform images or generate new styles.\n\n```typescript\nimport { bizrouter } from '@bizrouter/ai-sdk-provider';\nimport { generateText } from 'ai';\nimport { extractImages } from '@bizrouter/ai-sdk-provider/image';\nimport fs from 'fs/promises';\n\n// Load reference image as Base64 Data URL\nasync function loadImageAsDataUrl(filePath: string): Promise<string> {\n  const buffer = await fs.readFile(filePath);\n  const base64 = buffer.toString('base64');\n  return `data:image/jpeg;base64,${base64}`;\n}\n\n// Transform image to Van Gogh style\nconst refImage = await loadImageAsDataUrl('./my-photo.jpg');\n\nconst result = await generateText({\n  model: bizrouter('google/gemini-3.1-flash-image'),\n  messages: [\n    {\n      role: 'user',\n      content: [\n        {\n          type: 'text',\n          text: `Recreate this image in the style of Van Gogh's \"Starry Night\".\nApply swirling skies and bold brushstrokes,\nemphasizing blue and yellow tones.`,\n        },\n        {\n          // AI SDK v7: use 'file' parts ('image' parts are deprecated)\n          type: 'file',\n          mediaType: 'image/jpeg',\n          data: refImage, // plain data-URL string is accepted\n        },\n      ],\n    },\n  ],\n  providerOptions: {\n    bizrouter: {\n      aspect_ratio: '16:9',\n    },\n  },\n});\n\nconst { images } = extractImages(result);\n\nfor (const image of images) {\n  await fs.writeFile('styled-output.png', image.uint8Array);\n  console.log(`Generated: styled-output.png (${image.uint8Array.length} bytes)`);\n}\n```\n\n## Video Generation\n\nVideo generation is exposed as standalone helpers under the\n`@bizrouter/ai-sdk-provider/video` subpath rather than through the AI SDK model\ninterface, because generation is asynchronous (start → poll → download).\n\n> **Authentication differs from the rest of this package.** The video helpers\n> call the standard public API (`https://api.bizrouter.ai/v1/video/generation`)\n> with the `X-API-Key` header, not the `/ai-sdk` Bearer endpoints. The API key\n> is read from `BIZROUTER_API_KEY` unless you pass `apiKey` in the config\n> argument.\n\n```typescript\nimport {\n  generateVideo,\n  waitForVideo,\n  downloadVideo,\n} from '@bizrouter/ai-sdk-provider/video';\nimport fs from 'fs/promises';\n\n// 1. Start generation — returns immediately with an operation ID\nconst { operationId } = await generateVideo({\n  model: 'google/veo-3.1-fast',\n  prompt: 'A cat playing with a ball of yarn',\n  duration_seconds: 4,\n  resolution: '720p',\n});\n\n// 2. Poll until the operation settles (default: every 5s, 5 minute timeout)\nconst result = await waitForVideo(operationId, {\n  onStatusChange: (status) => console.log(`Status: ${status.status}`),\n});\n\n// 3. Download through the BizRouter proxy (link expires ~30 minutes after completion)\nif (result.status === 'completed') {\n  const video = await downloadVideo(operationId);\n  await fs.writeFile('output.mp4', video.data);\n}\n```\n\n### Supported Video Models\n\n| Model | Billing | Duration | Resolution |\n|-------|---------|----------|------------|\n| `google/veo-3.1` | Per second of video | 4 / 6 / 8s | 720p, 1080p, 4k |\n| `google/veo-3.1-fast` | Per second of video | 4 / 6 / 8s | 720p, 1080p, 4k |\n| `google/veo-3.1-lite` | Per second of video | 4 / 6 / 8s | 720p, 1080p |\n| `google/gemini-omni-flash-preview` | Per token of actual usage | 3–10s | 720p |\n\nAudio is always generated natively; there is no toggle.\n\n### Veo 3.1\n\n```typescript\nconst { operationId } = await generateVideo({\n  model: 'google/veo-3.1',\n  prompt: 'The cat slowly turns its head toward the camera',\n  duration_seconds: 8,\n  resolution: '1080p',\n  aspect_ratio: '16:9',\n  negative_prompt: 'text, watermark',\n  image: { mime_type: 'image/jpeg', data_base64: firstFrameBase64 },\n  last_frame: { mime_type: 'image/jpeg', data_base64: lastFrameBase64 },\n});\n```\n\n- `1080p` and `4k` require `duration_seconds: 8` — 4 and 6 second videos are 720p only.\n- `last_frame` (first/last frame interpolation) must be combined with `image`.\n- `reference_images` accepts up to 3 subject/asset references, requires\n  `duration_seconds: 8`, and cannot be combined with `image` / `last_frame`.\n- `google/veo-3.1-lite` does not support `4k`.\n\n### Gemini Omni Flash Preview\n\n`google/gemini-omni-flash-preview` is a separate arm of the\n`VideoGenerationOptions` discriminated union, so TypeScript enforces its\nnarrower contract at compile time:\n\n```typescript\nconst { operationId } = await generateVideo({\n  model: 'google/gemini-omni-flash-preview',\n  prompt: 'A neon-lit Seoul alley in the rain, camera pushing forward',\n  duration_seconds: 10, // 3–10 seconds\n  aspect_ratio: '16:9',\n  reference_images: [\n    { mime_type: 'image/png', data_base64: referenceBase64 },\n  ],\n});\n```\n\n- `duration_seconds` accepts any integer from 3 to 10; `resolution` accepts `720p` only.\n- `negative_prompt` and `last_frame` are not supported (typed as `never`).\n- `reference_images` accepts 1–6 images and cannot be combined with `image`.\n- **Cost timing differs**: this model is billed from the provider's actual token\n  usage, which is only known after generation finishes. `generateVideo()` omits\n  `costKrw` from its initial response, and `costKrw` appears on the status\n  result once usage has been settled. Veo models, billed per second, can report\n  the cost up front.\n\n### Image Inputs\n\nAll video image inputs use inline base64 — no data URL prefix:\n\n```typescript\ninterface VideoImageInput {\n  mime_type: string;     // 'image/jpeg' | 'image/png' | 'image/webp'\n  data_base64: string;   // base64 bytes, without the `data:` prefix\n}\n```\n\nThe complete request body is capped at 20MB, including base64 expansion.\n\n### Error Handling\n\nEvery helper throws `VideoGenerationError` (carrying `code` and `operationId`\nwhen available) on API failure, and `waitForVideo()` also throws it on timeout:\n\n```typescript\nimport { VideoGenerationError } from '@bizrouter/ai-sdk-provider/video';\n\ntry {\n  const result = await waitForVideo(operationId, { timeout: 600_000 });\n} catch (error) {\n  if (error instanceof VideoGenerationError) {\n    console.error(error.message, error.code, error.operationId);\n  }\n}\n```\n\nA `failed` operation does not throw — check `result.status` and `result.error`.\n\n## Multimodal Support\n\n> **AI SDK v7 file parts and data URL rules**\n>\n> In v7 the `image` part is deprecated; use `file` parts instead. The `data`\n> field accepts a raw base64 string, a `Uint8Array`, an http(s) `URL`, or a\n> **data URL as a plain string** (the SDK splits data URLs automatically).\n> However, putting a data URL inside the tagged form\n> `{ type: 'data', data: 'data:image/...' }` is **rejected** and throws an\n> error — when using the tagged form, pass data URLs as\n> `{ type: 'url', url: new URL(dataUrl) }`.\n\n### Basic Image Analysis\n\n```typescript\nimport { bizrouter } from '@bizrouter/ai-sdk-provider';\nimport { generateText } from 'ai';\n\n// OpenAI와 Google 모델은 URL 직접 지원\nconst { text } = await generateText({\n  model: bizrouter('openai/gpt-5.5'),\n  messages: [{\n    role: 'user',\n    content: [\n      { type: 'text', text: '이 이미지에 무엇이 있나요?' },\n      {\n        type: 'file',\n        mediaType: 'image/jpeg',\n        data: new URL('https://example.com/image.jpg'),\n      },\n    ],\n  }],\n});\n```\n\n### Anthropic Models (Base64 Required)\n\n```typescript\n// 이미지 URL을 base64로 변환하는 헬퍼 함수\nasync function imageUrlToBase64(url: string): Promise<string> {\n  const response = await fetch(url);\n  const buffer = await response.arrayBuffer();\n  const base64 = Buffer.from(buffer).toString('base64');\n  const contentType = response.headers.get('content-type') || 'image/jpeg';\n  return `data:${contentType};base64,${base64}`;\n}\n\n// Anthropic 모델 사용\nconst imageBase64 = await imageUrlToBase64('https://example.com/image.jpg');\n\nconst { text } = await generateText({\n  model: bizrouter('anthropic/claude-haiku-4.5'),\n  messages: [{\n    role: 'user',\n    content: [\n      { type: 'text', text: '이 이미지를 분석해주세요.' },\n      { type: 'file', mediaType: 'image/jpeg', data: imageBase64 },\n    ],\n  }],\n  maxOutputTokens: 500,\n});\n```\n\n### Multiple Images Comparison\n\n여러 이미지를 동시에 분석하고 비교:\n\n```typescript\nconst { text } = await generateText({\n  model: bizrouter('anthropic/claude-haiku-4.5'),\n  messages: [{\n    role: 'user',\n    content: [\n      { type: 'text', text: '이 두 이미지의 차이점을 비교해주세요.' },\n      {\n        type: 'file',\n        mediaType: 'image/jpeg',\n        data: await imageUrlToBase64('https://example.com/image1.jpg'),\n      },\n      {\n        type: 'file',\n        mediaType: 'image/jpeg',\n        data: await imageUrlToBase64('https://example.com/image2.jpg'),\n      },\n    ],\n  }],\n  maxOutputTokens: 1000,\n});\n```\n","readmeFilename":"README.md"}