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SDK for 100+ AI models — image, video, audio, and text generation with Picsart","maintainers":[{"name":"infosys-service","email":"infosys-service@picsart.com"},{"name":"tigran.shahverdyan","email":"tigran.shahverdyan@picsart.com"}],"readme":"# @picsart/ai-sdk\n\nGenerate images, video, audio, and text with 100+ AI models.\n\n## Documentation\n\nFull guides, the model catalog, and the API reference live on the Picsart API Platform:\n\n- [Documentation](https://picsart.com/api-platform/docs) -- overview and guides\n- [Quickstart](https://picsart.com/api-platform/docs/quickstart) -- install, authenticate, first generation\n- [SDK guide](https://picsart.com/api-platform/docs/sdk) -- client setup, `generate`/`generateText`, Drive, lifecycle\n- [Authentication](https://picsart.com/api-platform/docs/authentication) -- create an API key\n- [Model catalog](https://picsart.com/api-platform/models) -- browse every supported model\n- [API reference](https://picsart.com/api-platform/docs/api-reference)\n\nRepository: [github.com/PicsArt/ai-sdk](https://github.com/PicsArt/ai-sdk)\n\n## Quick Start\n\n```bash\nnpm install @picsart/ai-sdk\n```\n\n```typescript\nimport { createClient, Models, Model, catalog } from '@picsart/ai-sdk'\n\n// Create a client — pass your Picsart API key\nconst ai = createClient({\n  apiKey: process.env.PICSART_API_KEY,\n  apiUrl: 'https://api.picsart.com',\n})\n\n// Generate (Models.* are typed model-id constants)\nconst result = await ai.generate(Models.Flux2Pro, { prompt: 'a cat on mars' })\nconsole.log(result.url)\n\n// Browse models — the `catalog` accessor\ncatalog.all()                              // every model\ncatalog.find({ output: 'video' })          // video models only\ncatalog.search('kling')                    // search by name/id/provider\n\n// Model metadata & params — the `Model` accessor\nModel(Models.Flux2Pro).name                // 'Flux 2 Pro'\nModel(Models.Flux2Pro).meta()              // mode, provider, badges, …\nModel(Models.Flux2Pro).params()            // accepted parameters\nModel(Models.Flux2Pro).params().toSchema() // param schema\n\n// Validate input (never throws) → { valid, errors? }\nModel(Models.Flux2Pro).validate({ prompt: 'a cat' })\n```\n\n## Authentication\n\nPass `apiKey` and the SDK sends `Authorization: Bearer <apiKey>` on every request\n(a leading `Bearer ` is stripped if present). Create a key from the\n[Authentication guide](https://picsart.com/api-platform/docs/authentication).\n\n```typescript\nconst ai = createClient({\n  apiKey: process.env.PICSART_API_KEY,\n  apiUrl: 'https://api.picsart.com',\n})\n```\n\nKeep the key server-side — anything shipped to a browser is public.\n\nApps that already handle auth themselves (session cookies, token refresh, a\nbackend proxy) can pass their own `fetch` instead. It takes precedence over\n`apiKey` when both are set:\n\n```typescript\nconst ai = createClient({\n  fetch: myAuthenticatedFetch,\n  apiUrl: 'https://api.picsart.com',\n})\n```\n\n`createClient` throws if neither `apiKey` nor `fetch` is provided.\n\n## Custom Transport\n\n`fetch` swaps out how a request is authenticated; `transport` swaps out the\nrequests themselves. Pass one and the SDK stops talking to the workflows API\naltogether — every generation, poll, catalog load and credit estimate goes\nthrough your implementation instead:\n\n```typescript\nconst ai = createClient({ transport: myTransport })\n```\n\n`apiUrl` and the auth source are yours to bake into the transport, so neither is\nrequired alongside it. Two surfaces still speak the workflows protocol directly\nand keep needing `apiUrl` plus `fetch`/`apiKey` if you use them: `ai.drive` and\n`ai.apis`.\n\n| Method | Required | Serves |\n|--------|----------|--------|\n| `execute(request)` | yes | `syncExecute` models, catalog tasks, and every generation when `submit`/`poll` are absent |\n| `submit(request)` | no | `generate()`, `submit()` — returns the generation id |\n| `poll(handle, options)` | no | `generate()`, `result()`, `subscribe()` — resolves when the job is terminal, calls `options.onProgress` on the way |\n| `status(handle, signal?)` | no | the edit-route probe behind `result(model, id)` on models that have one |\n| `options(workflow, payload)` | no | `getCredits()` / `options()` — returns credits, an `OptionsResult`, or null |\n\nLeave `submit`/`poll` out and the client runs **every** generation through\n`execute()`; the async lifecycle (`submit()` / `result()` / `subscribe()`) then\nrejects with a 400 `unsupported_transport` rather than pretending. Leave\n`options` out and `getCredits()` / `options()` answer null.\n\n```typescript\nimport type { SdkTransport } from '@picsart/ai-sdk'\n\nconst myTransport: SdkTransport = {\n  async execute({ workflow, payload, signal }) {\n    const res = await callMyGateway(workflow, payload, signal)\n    return { result: res.output, usage: res.usage }\n  },\n  async submit({ workflow, payload }) {\n    return (await startMyJob(workflow, payload)).id\n  },\n  async poll(handle, options) {\n    const res = await waitForMyJob(handle.id, options)\n    return { result: res.output, usage: res.usage }\n  },\n}\n```\n\nThrow `ApiError` for failures — anything else reaches the caller as a 502\n`generation_failed`. A failed job may also resolve with the platform's\n`{ message, reason, statusCode }` payload as its `result`; the SDK turns that\ninto the matching `ApiError` itself.\n\n## Drive Integration\n\nAuto-save generations to Picsart Drive:\n\n```typescript\nconst ai = createClient({\n  apiKey: process.env.PICSART_API_KEY,\n  apiUrl: 'https://api.picsart.com',\n  drive: { folder: 'AI Playground' },\n})\n\n// Generates and auto-saves to the root folder\nconst result = await ai.generate(Models.Flux2Pro, { prompt: 'a cat' })\n// result.drive = { uid: '...', folder: { name: 'AI Playground', uid: '...' } }\n\n// Save to a subfolder\nconst board = await ai.drive.ensureFolder('Cats')\nconst result = await ai.generate(Models.Flux2Pro, { prompt: 'a cat' }, { folder: board })\n\n// Browse Drive\nconst folders = await ai.drive.folders()\nconst items = await ai.drive.list()\n```\n\nGenerated Drive assets carry `model` and JSON `aiSDKPayload` automatically. Both\n`generate()` and `submit()` record the original SDK inputs; custom Drive attributes\ncannot replace that provenance. These are requested inputs, not a claim that every\nprovider default or rewritten prompt has been recovered. The stored prompt is capped\nat 18,000 characters without changing the prompt sent to generation.\n\n`apis.run()` remains a direct vendor API pass-through. It does not apply the client’s\nDrive configuration or derive SDK metadata, even when a vendor payload explicitly\nrequests Drive saving. Vendor-shaped inputs must never be stored as `aiSDKPayload`;\nthat attribute is reserved for original SDK-shaped inputs.\n\nFor a separate or delayed save, pass the original generation context:\n\n```typescript\nawait ai.drive.save({\n  url: generatedUrl,\n  name: 'clip.mp4',\n  resourceType: 'VIDEO',\n  generation: { modelId, params: originalGenerationParams },\n})\n// The existing helper also accepts a full params object instead of just a prompt:\nconst saveParams = ai.drive.buildSaveParams(generatedUrl, modelId, modelName, 'video', originalGenerationParams)\n```\n\nWhen the request you submit is not the record you want kept (a render that sends\nonly a reference to an earlier job, say), pass the inputs to record as\n`drive.generation`. Custom `attributes` still cannot replace them:\n\n```typescript\nawait ai.submit(modelId, finalRequest, {\n  drive: { name: 'final.mp4', generation: { modelId, params: originalGenerationParams } },\n})\n```\n\nLegacy `model`/`prompt`/`textScript` saves are normalized at write time. URL-only\nuploads remain ordinary uploads: without generation context the SDK cannot infer\nmodel, prompt or settings. Existing Drive files are not backfilled. The backend preserves SDK-supplied metadata; it cannot reconstruct SDK input\nnames or catalog model IDs from an arbitrary vendor request.\n\n## Text Generation (LLMs)\n\nClaude, GPT, and Gemini text models are called with `generateText()`. Single-shot:\npass a prompt and optional image(s)/video, get text back. They surface in the catalog\nas `mode: 'text'`. Each vendor uses its own native workflow, so capabilities aren't lost\n— Gemini accepts video input, Claude uses the Anthropic-native messages API.\n\n```typescript\nimport { createClient, Models } from '@picsart/ai-sdk'\n\nconst ai = createClient({ apiKey: process.env.PICSART_API_KEY, apiUrl: 'https://api.picsart.com' })\n\n// Text in, text out\nconst { text } = await ai.generateText(Models.ClaudeOpus48, { prompt: 'Explain RAG in one line.' })\nconsole.log(text)\n\n// Optional vision input + reasoning level (OpenAI / Gemini)\nconst res = await ai.generateText(Models.Gpt55, {\n  prompt: 'What is in this image?',\n  imageUrls: ['https://cdn.example.com/photo.jpg'],\n  thinking: 'high',            // 'off' | 'low' | 'medium' | 'high'\n})\nconsole.log(res.text)\nconsole.log(res.raw)            // full backend response — usage, finish_reason, etc.\n\n// Gemini accepts video input\nawait ai.generateText(Models.Gemini3Pro, {\n  prompt: 'Summarize this clip',\n  videoUrl: 'https://cdn.example.com/clip.mp4',\n})\n\n// Browse text models\ncatalog.find({ output: 'text' })\n```\n\n> Thinking level maps per vendor: OpenAI → `reasoning_effort`, Gemini →\n> `thinkingConfig.thinkingLevel` (LOW/HIGH). Claude’s `claude/v1/messages`\n> workflow exposes no thinking knob, so Claude models omit `thinking`.\n\n`generateText()` is type-narrowed to text models (`TextModelId`); calling it with an\nimage/video model throws, and `generate()` throws on a text model — use the matching\nmethod for each.\n\n## Voice, Avatar & Template Catalogs\n\nModels with catalog-backed params (voices, avatars, effect / caption templates) serve their option lists\nfrom platform catalog tasks (`<vendor>/v1/catalog/<voices|avatars|templates|…>`) — nothing\nis bundled; the workers cache the lists and answer fast. Fetch them via\n`ai.catalogs`:\n\n```typescript\n// One page at a time — load more on scroll/pagination via nextCursor\nconst page = await ai.catalogs.voices('heygen-video-avatar')\n// page: { items: CatalogItem[], nextCursor: string | null }\nconst more = await ai.catalogs.voices('heygen-video-avatar', { cursor: page.nextCursor! })\n\n// Optional: preload the first page of every bound catalog at client creation\nconst ai = createClient({ apiKey, catalogs: { preload: true } })\n\n// Fetched pages accumulate into the model's options, so existing accessors\n// (and every picker built on them) see everything loaded so far:\nModel('heygen-video-avatar').params().catalog('videoId')?.catalogOptions\n```\n\n`CatalogItem` is the standard shape across all vendors:\n`{ id, name, description?, tags, preview? { imageUrl | videoUrl | audioUrl }, meta? }` —\n`id` is sent back verbatim on generate as the bound param's value. Validation\nnever requires hydration: catalog-bound params accept any id and the platform\nvalidates for real.\n\n## Advanced Lifecycle\n\nFor progress tracking and job recovery:\n\n```typescript\n// Submit without waiting — returns the generation id (a string)\nconst generationId = await ai.submit(Models.KlingV3, { prompt: 'a sunset' })\n\n// Subscribe to updates — the terminal generation.completed event carries the\n// parsed result, so no follow-up result() call is needed\nfor await (const e of ai.subscribe(Models.KlingV3, generationId)) {\n  if (e.type === 'generation.progress') console.log(e.progress?.percent)\n  if (e.type === 'generation.completed') console.log(e.result.url)\n  if (e.type === 'generation.failed') console.error(e.error.message)\n}\n\n// Or just wait for the parsed result (throws on failure/cancel)\nconst result = await ai.result(Models.KlingV3, generationId, { intervalMs: 2000 })\n\n// One-shot snapshot of a stored id (e.g. after a page reload)\nconst { value: snapshot } = await ai.subscribe(Models.KlingV3, generationId).next()\n```\n\nGeneration ids are plain strings — store them and recover jobs later with\n`result(model, id)` or `subscribe(model, id)`.\n\n## Error Handling\n\nEvery failure thrown by `generate()`, `generateText()`, `submit()`, and `result()`\nis an `ApiError` with the same four fields, so you can branch on the error\ninstead of pattern-matching its message:\n\n```typescript\nimport { createClient, Models, ApiError } from '@picsart/ai-sdk'\n\ntry {\n  const result = await ai.generate(Models.Flux2Pro, { prompt: 'a cat on mars' })\n} catch (err) {\n  if (err instanceof ApiError) {\n    err.status   // 402            — HTTP status, or its synthesized equivalent\n    err.code     // 'payment_required' — platform `reason`, else an SDK code\n    err.reason   // same value as `code`, named after the platform's own field\n    err.message  // 'Submit failed (402): Not enough credits'\n\n    if (err.status === 402) return topUpCredits()\n    if (err.status === 429 || err.status >= 500) return retry()\n    if (err.code === 'validation_error') return showFormError(err.message)\n  }\n  throw err\n}\n```\n\n`code` carries the platform's `reason` verbatim whenever the API supplies one\n(`content_moderation`, `unauthorized`, …). When it doesn't, the SDK fills in a\nconventional slug for the status — `payment_required` for 402, `rate_limited`\nfor 429, and so on.\n\nFailures that never reach the network get the status they semantically deserve,\nso one retry predicate covers every case:\n\n| Failure | `status` | `code` |\n|---------|----------|--------|\n| Unknown model id | 400 | `unknown_model` |\n| `generate()` on a text model (or the reverse) | 400 | `wrong_model_mode` |\n| Parameter validation | 400 | `validation_error` |\n| Async lifecycle on an execute-only transport | 400 | `unsupported_transport` |\n| HTTP error from the API | the response's status | platform `reason`, else the status slug |\n| Poll deadline exceeded | 408 | `timeout` |\n| Aborted via `options.signal`, or a canceled job | 499 | `aborted` / `canceled` |\n| Job finished `FAILED` | the task's `statusCode`, else 502 | platform `reason`, else `generation_failed` |\n| Response the SDK can't parse | 502 | `invalid_response` |\n\nAborts raised by `fetch` itself are deliberately **not** wrapped, so\n`err.name === 'AbortError'` keeps working on the `DOMException`.\n\n`message` is human-readable and may change between versions — branch on `status`\nand `code`, not on the message text.\n\n`ApiError` is the only error type the SDK throws: `ai.apis` and `ai.catalogs`\nreport failures the same way, and a custom transport's own error is mapped too\n(a 502 `generation_failed` when it isn't already an `ApiError`).\n\n## Public API\n\nKey exports (see `src/index.ts` for the full list):\n\n| Export | Type | Description |\n|--------|------|-------------|\n| `createClient` | function | Create an AI client from an API key (or a custom authenticated fetch) |\n| `Models` | object | Typed model-id constants (`Models.Flux2Pro` → `'flux-2-pro'`) |\n| `Model`, `catalog` | function / object | Model metadata, params, validation, discovery |\n| `GenerateResult` | type | `{ url, items: [{ url, metadata? }], generationId, usage?, drive? }` |\n| `GenerationEvent` | type | One `ai.subscribe()` update — `generation.progress` / `.completed` / `.failed` |\n| `GenerationEventType` | const | Named event-type constants (`GenerationEventType.Completed` === `'generation.completed'`) |\n| `ClientConfig` | type | `{ apiKey?, fetch?, apiUrl, drive?, transport? }` — one of `apiKey` / `fetch` required unless `transport` is set |\n| `AuthenticatedFetch` | type | `(url, init?) => Promise<Response>` — for the custom-`fetch` path |\n| `SdkTransport` | type | The transport contract — see [Custom Transport](#custom-transport) |\n| `GenerationOptions` | type | Poll controls for `result()`/`subscribe()` — `{ intervalMs?, maxAttempts?, signal? }` |\n| `ApiError` | class | Unified error: `{ status, code, reason, message }` — see [Error Handling](#error-handling) |\n\n## Package Structure\n\n```\npackages/ai-sdk/\n  package.json\n  tsconfig.json\n  tsup.config.ts\n  src/\n    index.ts                    # Public API entry\n    client/\n      types.ts                  # ClientConfig, GenerateResult, DriveConfig\n      transport.ts              # Default SdkTransport, over @picsart/workflows-client\n      prepare.ts                # Validate input, build payload, parse result\n      drive.ts                  # Drive folder management + file saving\n      index.ts                  # createClient() factory\n    core/\n      types.ts                  # ModelDefinition, ParamConfig, GenerationContext\n      workflow.ts               # Task envelope types + the SdkTransport contract\n      contracts.ts              # Runtime input validation\n      schema.ts                 # ParamConfig → JSON Schema\n      response.ts               # Vendor-agnostic result extraction\n      pricing.ts                # ToolId resolution\n      model-registry.ts         # Model lookup indexes\n      providers.ts              # Provider colors, labels, names\n      voices.ts                 # Voice catalogs (ElevenLabs, OpenAI, Gemini)\n      helpers.ts                # Vendor utilities\n    generated/\n      model-constants.ts        # AUTO-GENERATED: Models object + id constants\n      model-input-types.ts      # AUTO-GENERATED: per-model TypeScript input types\n    vendors/\n      define.ts                 # defineModels() framework + params.* helpers\n      presets.ts                # Reusable paramConfig factories\n      catalog/\n        index.ts                # Aggregation: ALL_MODELS, VENDOR_CATALOGS\n        kling.ts                # One file per vendor (31 total)\n        flux.ts\n        ...\n  __tests__/                    # SDK tests\n  scripts/                      # Build scripts\n```\n\n## Adding a New Model\n\n### Standard flow (pass-through payload)\n\nWhen the backend accepts param values as-is (no field renaming needed):\n\n1. Add config in `src/vendors/catalog/{vendor}.ts` via `defineModels()`:\n   - `buildPayload` is **optional** — omit it and param values pass through as-is\n2. Run `npm run build:model-constants` to regenerate constants\n3. Run `npm run build:model-input-types` to regenerate TypeScript types\n4. Model automatically appears in `catalog.all()` and as the `Models.NewModel` id constant\n\n### With payload transforms\n\nWhen the vendor API uses different field names or value formats:\n\n1. Define the model config as above (no `buildPayload`)\n2. Run `npm run build:model-input-types` — generates typed input for your model\n3. Create `src/vendors/catalog/{vendor}.payloads.ts`:\n   ```ts\n   import type { ModelInput } from '../../generated/model-input-types.ts';\n   import { registerPayloads } from '../define.ts';\n   import { SPECS, MODELS } from './{vendor}.ts';\n\n   registerPayloads({ SPECS, MODELS }, {\n     'model-id': (input: ModelInput<'model-id'>) => ({\n       prompt: input.prompt,\n       aspect_ratio: input.aspectRatio,  // rename for vendor API\n     }),\n   });\n   ```\n4. Import the `.payloads.ts` file in `src/vendors/catalog/index.ts` (after the vendor import)\n\nSee `src/vendors/catalog/luma.ts` + `src/vendors/catalog/luma.payloads.ts` for a working example.\n","readmeFilename":"README.md"}