# Topaz Video Upscale

> Video upscaling and enhancement with Topaz AI — Proteus, Artemis, Nyx, Gaia and Starlight models.

## Overview

- **Model ID**: `topaz-upscale-video`
- **Workflow**: `topaz/upscale/video`
- **Provider**: Topaz
- **Origin**: Partner Model
- **Category**: Video → Video (video)
- **Output**: A video URL.
- **Tags**: upscale, video required
- **Unified endpoint**: `POST https://api.picsart.com/workflows/v1/models/execute` (model id in the body)
- **Compatibility endpoint**: `POST https://api.picsart.com/workflows/topaz/upscale/video/execute` (vendor's own parameters)
- **Execution**: long-running — use the async submit/poll pair or the SDK, which polls for you
- **Model page**: https://picsart.com/api-platform/models/topaz-upscale-video

## Pricing

Live pricing for this model is not published yet. See https://picsart.com/pricing/ or the Pricing tab of the model page (https://picsart.com/api-platform/models/topaz-upscale-video#pricing).

## Authentication

The SDK and the REST API authenticate with a Picsart API key sent as a bearer token. Create a key in the console at https://picsart.com/api-platform/dashboard/api-keys, keep it in a server-side environment variable, and never ship it in browser code or commit it.

```bash
export PICSART_API_KEY="YOUR_KEY"
```

```http
Authorization: Bearer $PICSART_API_KEY
```

The CLI and the MCP server do not use an API key: `gen-ai login` signs in through the browser once per machine and stores a token locally.

## Interfaces

- **SDK (TypeScript)** — `@picsart/ai-sdk` (Node 20+, ESM). Type-safe `ai.generate()` / `ai.generateText()` with per-model parameter types; polls long jobs for you.
- **SDK (Python)** — `picsart-ai-sdk` (Python 3.10+, async). The same surface in snake_case: `await ai.generate()` / `await ai.generate_text()`, with a typed input per model.
- **REST** — the API gateway at `https://api.picsart.com`. Sync `/execute`, or async `/submit` + `/{taskId}/result`.
- **CLI** — `@picsart/gen-ai` (`gen-ai`). Generate from a terminal, quote cost before spending, emit JSON for pipelines.
- **MCP** — the same models inside Claude Code, Cursor, Windsurf and other MCP hosts. Setup: https://picsart.com/gen-ai-mcp/

```bash
npm install @picsart/ai-sdk      # SDK (TypeScript)
pip install picsart-ai-sdk       # SDK (Python)
npm install -g @picsart/gen-ai   # CLI (also drives the MCP server)
```

## Unified API (recommended)

One parameter set, used by the SDK and by REST alike: the names below are what `ai.generate('topaz-upscale-video', …)` takes, and what goes inside the inner `params` of a REST call. Over REST the model id travels in the body, not the path — one workflow, `v1/models`, fronts the whole catalogue.

### Execution modes

- **Sync** — `POST /workflows/v1/models/execute` returns the result in one call. Only for jobs that finish within ~20 seconds; otherwise it times out.
- **Async** — `POST /workflows/v1/models/submit` returns a task id; poll `GET /workflows/v1/models/{taskId}/result` until `response.status` is `COMPLETED` or `FAILED`. Task statuses: `ACCEPTED` · `IN_PROGRESS` · `COMPLETED` · `FAILED`.
- **SDK** — `ai.generate()` always awaits the finished result; polling is hidden.

Video jobs routinely outrun the sync limit: use async over REST, or the SDK, which polls for you.

### Input parameters

- **`videoUrl`** (`string`, _required_): The video to work on, as a URL.
  - Accepts: video URL
- **`model`** (`string`, _optional_): Model
  - Default: `"Proteus"`
  - Options: `Proteus`, `Artemis HQ`, `Artemis MQ`, `Artemis LQ`, `Nyx`, `Nyx Fast`, `Nyx XL`, `Nyx HF`, `Gaia HQ`, `Gaia CG`, `Gaia 2`, `Starlight Precise 2.5`, `Starlight HQ`, `Starlight Mini`, `Starlight Sharp`, `Starlight Fast 2`

### Input JSON Schema

The inner `params` object. Over REST it is wrapped as `{ "params": { "model": "<id>", "params": <this> } }`; the SDK takes it directly.

```json
{
  "type": "object",
  "required": [
    "videoUrl"
  ],
  "properties": {
    "videoUrl": {
      "type": "string",
      "format": "uri",
      "description": "The video to work on, as a URL."
    },
    "model": {
      "type": "string",
      "enum": [
        "Proteus",
        "Artemis HQ",
        "Artemis MQ",
        "Artemis LQ",
        "Nyx",
        "Nyx Fast",
        "Nyx XL",
        "Nyx HF",
        "Gaia HQ",
        "Gaia CG",
        "Gaia 2",
        "Starlight Precise 2.5",
        "Starlight HQ",
        "Starlight Mini",
        "Starlight Sharp",
        "Starlight Fast 2"
      ],
      "default": "Proteus",
      "description": "Model"
    }
  },
  "additionalProperties": false
}
```

### Required parameters example

The required parameters plus the defaults that shape the output, as a REST body:

```json
{
  "params": {
    "model": "topaz-upscale-video",
    "params": {
      "videoUrl": "https://cdn.example.com/input.mp4"
    }
  }
}
```

### Response

The body is the gateway's status envelope: the output is at `response.result`, next to the task id, its status and the credits charged. Asset models return `url` plus an `items` array of results.

```json
{
  "status": "success",
  "response": {
    "id": "task_abc123",
    "status": "COMPLETED",
    "result": {
      "url": "https://cdn.picsart.com/…/result",
      "items": [
        {
          "url": "https://cdn.picsart.com/…/result"
        }
      ],
      "model": "topaz-upscale-video"
    }
  }
}
```

What `ai.generate()` / `ai.generateText()` resolve to (the envelope already unwrapped):

```json
{
  "items": [
    {
      "url": "https://cdn.picsart.com/…/result"
    }
  ],
  "model": "topaz-upscale-video"
}
```

### Usage examples

#### TypeScript (SDK)

```typescript
import { createClient } from '@picsart/ai-sdk';

const ai = createClient({
  apiKey: process.env.PICSART_API_KEY,
  apiUrl: 'https://api.picsart.com',
});

const result = await ai.generate('topaz-upscale-video', {
  videoUrl: "https://cdn.example.com/input.mp4"
});

console.log(result.url); // video URL
```

#### Python (SDK)

```python
import asyncio
import os

from picsart_ai_sdk import create_client


async def main() -> None:
    async with create_client(
        api_key=os.environ["PICSART_API_KEY"],
        api_url="https://api.picsart.com",
    ) as ai:
        result = await ai.generate("topaz-upscale-video", {
            "videoUrl": "https://cdn.example.com/input.mp4",
        })

        print(result.url)  # video URL


asyncio.run(main())
```

#### cURL (sync)

```bash
curl -X POST 'https://api.picsart.com/workflows/v1/models/execute' \
  -H 'Authorization: Bearer $PICSART_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
  "params": {
    "model": "topaz-upscale-video",
    "params": {
      "videoUrl": "https://cdn.example.com/input.mp4"
    }
  }
}'
```

#### cURL (async: submit, then poll)

```bash
# 1. Submit the job
curl -X POST 'https://api.picsart.com/workflows/v1/models/submit' \
  -H 'Authorization: Bearer $PICSART_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
  "params": {
    "model": "topaz-upscale-video",
    "params": {
      "videoUrl": "https://cdn.example.com/input.mp4"
    }
  }
}'
# → { "status": "success", "response": { "id": "task_abc123" } }

# 2. Poll until response.status is COMPLETED
curl 'https://api.picsart.com/workflows/v1/models/task_abc123/result' \
  -H 'Authorization: Bearer $PICSART_API_KEY'
```

#### CLI

```bash
gen-ai login  # once per machine
gen-ai models info topaz-upscale-video  # this model's parameters
gen-ai pricing topaz-upscale-video  # quote before spending credits
gen-ai generate -m topaz-upscale-video
```

## Compatibility API (vendor parameters)

Alongside the unified API, the `topaz/upscale/video` workflow takes Topaz's own parameters exactly as the vendor defines them — nothing renamed or reshaped. It is the shortest path onto Picsart for request bodies already written against the vendor; the trade is that a request is written for one vendor, and the result comes back in the vendor's own shape. Same authentication.

- **Endpoint**: `POST https://api.picsart.com/workflows/topaz/upscale/video/execute` (sync) · `POST …/submit` + `GET …/{taskId}/result` (async)
- **SDK**: `ai.apis.run('topaz/upscale/video', params, { mode })` in TypeScript, `ai.apis.run("topaz/upscale/video", params, mode=…)` in Python — params forwarded verbatim

### Vendor parameters

| Parameter | Type | Required | Default | Details |
| --- | --- | --- | --- | --- |
| `target_fps` | `integer` | no | — | Target FPS for frame interpolation. If set, frame interpolation will be enabled. · 16–60 |
| `upscale_factor` | `number` | no | `2` | Factor to upscale the video by (e.g. 2.0 doubles width and height) · 1–4 |
| `enable_safety_checker` | `boolean` | no | `true` | — |
| `H264_output` | `boolean` | no | `false` | Whether to use H264 codec for output video. Default is H265. |
| `video_url` | `string` | yes | — | URL of the video to upscale · e.g. `https://v3.fal.media/files/kangaroo/y5-1YTGpun17eSeggZMzX_video-1733468228.mp4` |
| `compression` | `number` | no | — | Compression artifact removal level (0.0-1.0). Default varies by model. · 0–1 |
| `halo` | `number` | no | — | Halo reduction level (0.0-1.0). Default varies by model. · 0–1 |
| `recover_detail` | `number` | no | — | Recover original detail level (0.0-1.0). Higher values preserve more original detail. · 0–1 |
| `noise` | `number` | no | — | Noise reduction level (0.0-1.0). Default varies by model. · 0–1 |
| `grain` | `number` | no | — | Film grain amount (0.0-0.1). Default varies by model. · 0–0.1 · multiple of 0.01 |
| `model` | `string` | no | `Proteus` | Video enhancement model, grouped by family. Precision — Proteus fits most footage, Artemis denoises and sharpens degraded sources, Gaia HQ/CG refine rendered content, Gaia 2 handles animation and motion graphics at 2x. Denoise — Nyx models are dedicated noise reduction. Generative — Starlight models use diffusion for restoration and upscaling. Starlight Precise 1, Starlight Precise 2 and Starlight Fast 1 are deprecated by Topaz; prefer Starlight Precise 2.5 or Starlight Fast 2. · Options: `Proteus`, `Artemis HQ`, `Artemis MQ`, `Artemis LQ`, `Gaia HQ`, `Gaia CG`, `Gaia 2`, `Nyx`, `Nyx Fast`, `Nyx XL`, `Nyx HF`, `Starlight Precise 2.5`, `Starlight HQ`, `Starlight Mini`, `Starlight Sharp`, `Starlight Fast 2`, `Starlight Precise 1`, `Starlight Precise 2`, `Starlight Fast 1` |
| `options` | `object` | no | — | Platform-specific options for safety checks and Picsart Drive integration. |
| └ `safety_checks` | `object` | no | — | Safety check configuration. |
| └   `enabled` | `boolean` | no | `true` | Enable or disable text safety checks. Defaults to true. |
| └ `drive` | `object` | no | — | Picsart Drive storage options. When provided, the result will be saved to the user's Drive. |
| └   `name` | `string` | yes | — | Filename to save the result as in Picsart Drive. |
| └   `attributes` | `object` | no | — | Additional file metadata attributes. |
| └   `folder` | `object` | no | — | Destination folder in Picsart Drive. |

### Example request body

```json
{
  "params": {
    "video_url": "https://v3.fal.media/files/kangaroo/y5-1YTGpun17eSeggZMzX_video-1733468228.mp4"
  }
}
```

### Usage examples

#### TypeScript (`ai.apis.run`)

```typescript
import { createClient, ApiRunMode } from '@picsart/ai-sdk';

const ai = createClient({
  apiKey: process.env.PICSART_API_KEY,
  apiUrl: 'https://api.picsart.com',
});

// Calls the 'topaz/upscale/video' workflow directly — params are sent as-is.
const { result, usage } = await ai.apis.run('topaz/upscale/video', {
  video_url: "https://v3.fal.media/files/kangaroo/y5-1YTGpun17eSeggZMzX_video-1733468228.mp4"
}, {
  mode: ApiRunMode.SYNC,
});

console.log(result); // workflow-specific output
console.log(usage?.credits); // amount charged, in $
```

#### Python (`ai.apis.run`)

```python
import asyncio
import os

from picsart_ai_sdk import ApiRunMode, create_client


async def main() -> None:
    async with create_client(
        api_key=os.environ["PICSART_API_KEY"],
        api_url="https://api.picsart.com",
    ) as ai:
        # Calls the 'topaz/upscale/video' workflow directly — params are sent as-is.
        response = await ai.apis.run("topaz/upscale/video", {
            "video_url": "https://v3.fal.media/files/kangaroo/y5-1YTGpun17eSeggZMzX_video-1733468228.mp4",
        }, mode=ApiRunMode.SYNC)

        print(response["result"])  # workflow-specific output
        print((response.get("usage") or {}).get("credits"))  # amount charged, in $


asyncio.run(main())
```

#### cURL (sync)

```bash
curl -X POST 'https://api.picsart.com/workflows/topaz/upscale/video/execute' \
  -H 'Authorization: Bearer $PICSART_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
  "params": {
    "video_url": "https://v3.fal.media/files/kangaroo/y5-1YTGpun17eSeggZMzX_video-1733468228.mp4"
  }
}'
```

#### cURL (async: submit, then poll)

```bash
# 1. Submit the job
curl -X POST 'https://api.picsart.com/workflows/topaz/upscale/video/submit' \
  -H 'Authorization: Bearer $PICSART_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
  "params": {
    "video_url": "https://v3.fal.media/files/kangaroo/y5-1YTGpun17eSeggZMzX_video-1733468228.mp4"
  }
}'
# → { "status": "success", "response": { "id": "wf_abc123" } }

# 2. Poll until response.status is COMPLETED
curl 'https://api.picsart.com/workflows/topaz/upscale/video/wf_abc123/result' \
  -H 'Authorization: Bearer $PICSART_API_KEY'
```

### Response

Over HTTP the vendor-shaped result arrives inside the gateway envelope at `response.result`:

```json
{
  "status": "success",
  "response": {
    "id": "wf_abc123",
    "status": "COMPLETED",
    "result": {
      "video": {
        "file_size": 4404019,
        "file_name": "z9RV14K95DvU.png",
        "url": "https://cdn.picsart.com/…/result.mp4",
        "content_type": "image/png"
      }
    }
  }
}
```

`ai.apis.run()` unwraps that envelope and resolves to `{ result, usage }`:

```json
{
  "result": {
    "video": {
      "file_size": 4404019,
      "file_name": "z9RV14K95DvU.png",
      "url": "https://cdn.picsart.com/…/result.mp4",
      "content_type": "image/png"
    }
  }
}
```

## Additional resources

- Model page (playground): https://picsart.com/api-platform/models/topaz-upscale-video
- SDK and REST API (unified): https://picsart.com/api-platform/models/topaz-upscale-video#api
- Compatibility API (vendor parameters): https://picsart.com/api-platform/models/topaz-upscale-video#advanced
- Pricing: https://picsart.com/api-platform/models/topaz-upscale-video#pricing
- This document: https://picsart.com/api-platform/models/topaz-upscale-video/llms.txt
- All models: https://picsart.com/api-platform/models
- Docs — quickstart https://picsart.com/api-platform/docs/quickstart, authentication https://picsart.com/api-platform/docs/authentication, SDK https://picsart.com/api-platform/docs/sdk, REST https://picsart.com/api-platform/docs/api-reference, CLI https://picsart.com/api-platform/docs/cli, MCP https://picsart.com/api-platform/docs/mcp
- CLI reference: https://picsart.github.io/picsart-mcp-cli-docs/guide/introduction