# Subtitle RAG Chunker (`skilled_glee/subtitle-rag-chunker`) Actor

Convert SRT and WebVTT subtitles into timestamped JSON chunks for video transcript RAG, semantic search and vector databases. Preserve cue timestamps, source provenance, stable chunk IDs and SHA-256 hashes.

- **URL**: https://apify.com/skilled\_glee/subtitle-rag-chunker.md
- **Developed by:** [Dakota Myers](https://apify.com/skilled_glee) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$5.00 / 1,000 document with useful outputs

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Subtitle RAG Chunker

Give me valid SRT or WebVTT subtitle text, or a public HTTP(S) text URL, and I reliably return deterministic timestamp-aware RAG chunks without splitting a cue. Records carry source and document identity, cue numbers where supplied, first/last cue timestamps, hashes, chunk order, and chunking configuration.

Submit one or more subtitle sources through the `items` array. `rawText` takes precedence over `sourceUrl` or `fileUrl`. `chunkSize` and `overlap` are deterministic parameters that materially affect output.

### Output and repeatability

The default dataset contains cue-preserving chunks with stable `documentId`, `chunkId`, SHA-256 hashes, timestamps, cue metadata, source provenance, and chunking parameters. Identical subtitle text and semantic parameters produce the same useful records and stable IDs.

The default key-value store record `SUMMARY` contains aggregate run status, submitted-document count, total chunk count, per-document outcomes, and a UTC `processedAt` timestamp. `processedAt` is volatile metadata and does not participate in stable chunk identity.

A failed input is isolated from successful siblings rather than discarding useful batch output.

Limitations: tested for ordinary SRT and WebVTT timing syntax, multiline cues, simple tags, duplicates, gaps, and malformed timestamps. It does not support TTML, ASS/SSA, subtitle OCR, translations, speaker diarization, or live streams.

### Billing and limits

One `document-converted` event is charged only after a document produces supported output saved to the dataset. Empty or failed documents are not charged. Platform costs are included; no start or automatic dataset-item charge. Up to 25 documents, 2 MB UTF-8 text per document, and a 120-second run timeout. The Actor stops at the spending limit. Public text downloads must be accessible without credentials.

# Actor input Schema

## `items` (type: `array`):

One to 100 independently processed subtitle inputs.

## Actor input object example

```json
{
  "items": [
    {
      "rawText": "1\n00:00:00,000 --> 00:00:02,000\nDeterministic subtitle health fixture.\n\n2\n00:00:02,000 --> 00:00:04,000\nThe same input produces the same stable chunk identifiers.",
      "sourceName": "apify-health-fixture"
    }
  ]
}
```

# Actor output Schema

## `chunks` (type: `string`):

No description

## `summary` (type: `string`):

No description

# 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 = {
    "items": [
        {
            "rawText": "1\n00:00:00,000 --> 00:00:02,000\nDeterministic subtitle health fixture.\n\n2\n00:00:02,000 --> 00:00:04,000\nThe same input produces the same stable chunk identifiers.",
            "sourceName": "apify-health-fixture"
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("skilled_glee/subtitle-rag-chunker").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 = { "items": [{
            "rawText": """1
00:00:00,000 --> 00:00:02,000
Deterministic subtitle health fixture.

2
00:00:02,000 --> 00:00:04,000
The same input produces the same stable chunk identifiers.""",
            "sourceName": "apify-health-fixture",
        }] }

# Run the Actor and wait for it to finish
run = client.actor("skilled_glee/subtitle-rag-chunker").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 '{
  "items": [
    {
      "rawText": "1\\n00:00:00,000 --> 00:00:02,000\\nDeterministic subtitle health fixture.\\n\\n2\\n00:00:02,000 --> 00:00:04,000\\nThe same input produces the same stable chunk identifiers.",
      "sourceName": "apify-health-fixture"
    }
  ]
}' |
apify call skilled_glee/subtitle-rag-chunker --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,skilled_glee/subtitle-rag-chunker"
        }
    }
}
```

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/NzbvKBTYMFZTdWM36/builds/wKqdyiTBlk7PLAkg2/openapi.json