# CremyX Turbo ASR (`andrew_babo/cremyx-turbo-asr`) Actor

- **URL**: https://apify.com/andrew\_babo/cremyx-turbo-asr.md
- **Developed by:** [Andrew Babo](https://apify.com/andrew_babo) (community)
- **Stats:** 2,001 total users, 1,175 monthly users, 99.8% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## cremyx-turbo-asr

One-shot CPU Whisper ASR shard transcriber for the Super Clipping fan-out lane.

### Input

| field | type | default | meaning |
| --- | --- | --- | --- |
| `source` | string | — | public http(s) URL (preferred) or `kv:` ref |
| `start_sec` | number | 0 | shard start offset |
| `duration_sec` | number | 40 | shard length |
| `overlap_sec` | number | 1.5 | extra tail audio for boundary words |
| `language` | string | null | force language (null = auto) |
| `preset` | string | `fast` | fast / adaptive / balanced / accurate |
| `allow_empty` | boolean | false | silence-only shard still returns success |

### Output

One dataset item per run: `status`, `meta.words` (absolute timeline, overlap
tail flagged `_overlap`), `meta.segments`, `timings`, `errors`.

Model: `large-v3-turbo-q5_0` baked into the image (whisper.cpp, CPU).

# Actor input Schema

## `source` (type: `string`):

https:// URL (public artifact URL from a previous run, or any reachable media) or kv:<storeId>/<key>. Range-queried when the server allows it.

## `start_sec` (type: `number`):

Offset of this shard on the original timeline.

## `duration_sec` (type: `number`):

Shard length before the tail overlap. 240-300s is the measured sweet spot for faster-whisper on CPU (RTF ~4.7x); short 15-45s shards waste fixed overhead.

## `overlap_sec` (type: `number`):

Extra audio past duration\_sec; words there are flagged \_overlap so the engine can dedupe.

## `language` (type: `string`):

ISO code (en, vi, ...). Omit for auto-detect.

## `preset` (type: `string`):

fast | adaptive | balanced | accurate

## `allow_empty` (type: `boolean`):

Silent windows return 0 words instead of failing.

## `model` (type: `string`):

Baked models. large-v3-turbo = multilingual default (Vietnamese OK). distil-large-v3 is ENGLISH-ONLY and is auto-downgraded to large-v3-turbo for non-English audio. medium = smaller/faster, lower accuracy.

## `vad_filter` (type: `boolean`):

Skip silence before decoding. Cuts compute on sparse audio but can clip word boundaries.

## `cpu_threads` (type: `integer`):

faster-whisper cpu\_threads. 4 measured best on a 16 GB Apify run (~4 vCPU).

## `batch_size` (type: `integer`):

BatchedInferencePipeline batch size: VAD chunks decoded in parallel so every cpu\_thread stays busy. 0/1 = sequential decode.

## `mode` (type: `string`):

Để trống = 1 window/run. 'batch' = worker ấm chạy danh sách 'windows' (khuyến nghị). 'pool\_worker' = lấy window từ Apify request queue (cần cùng account + full permissions).

## `queue_id` (type: `string`):

Apify request queue holding the windows. fetch\_next\_request is atomic, so workers never take the same window twice.

## `dataset_id` (type: `string`):

Dataset every worker pushes its window rows into, so the engine reads one stream.

## `worker_label` (type: `string`):

Free-form label echoed back in each row for telemetry.

## `idle_sec` (type: `number`):

Exit after this many seconds with an empty queue. 2-120.

## `max_life_sec` (type: `number`):

Hard stop for one worker. 30-900.

## `max_jobs` (type: `integer`):

Hard stop after this many windows. 1-512.

## `windows` (type: `array`):

Danh sách window chia sẵn cho MỘT worker ấm: \[{job\_id,shard\_index,source,start\_sec,duration\_sec,overlap\_sec,preset,model,vad\_filter}]. Mô hình nạp một lần cho cả danh sách.

## Actor input object example

```json
{
  "start_sec": 0,
  "duration_sec": 240,
  "overlap_sec": 1.5,
  "preset": "fast",
  "allow_empty": true,
  "model": "large-v3-turbo",
  "vad_filter": false,
  "cpu_threads": 4,
  "batch_size": 8,
  "mode": "",
  "idle_sec": 25,
  "max_life_sec": 600,
  "max_jobs": 64
}
```

# Actor output Schema

## `results` (type: `string`):

Dataset row: status, shard, meta {words, segments, word\_count}, timings, errors.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("andrew_babo/cremyx-turbo-asr").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("andrew_babo/cremyx-turbo-asr").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call andrew_babo/cremyx-turbo-asr --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,andrew_babo/cremyx-turbo-asr"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/kW4vkYwCT6VylccZP/builds/PApaYdjfqiH598d7Z/openapi.json