# Podcast Episode to RAG Chunks with Time Citations

**Use case:** 

Paste a podcast, lecture or meeting recording URL (MP3, MP4, M4A, WAV and more) and get the transcript as JSON: timestamped segments, RAG chunks with time citations like 00:12:03-00:12:48, SRT and VTT subtitles. Runs open-source Whisper on CPU, no speech API key needed. The preset uses a short public-domain sample so you can see the output before pointing it at your own file.

## Input

```json
{
  "audioUrls": [
    "https://archive.org/download/gettysburg_shurtagal_librivox/Gettysburg_Address_Lincoln_64kb.mp3"
  ],
  "model": "standard",
  "language": "auto",
  "translateToEnglish": false,
  "outputMode": "documents",
  "chunkSize": 1200,
  "chunkOverlap": 150,
  "includeWordTimestamps": false,
  "subtitles": true,
  "maxDurationMinutes": 180,
  "maxFileSizeMb": 200
}
```

## Output

```json
{
  "sourceUrl": {
    "label": "Source URL",
    "format": "string"
  },
  "fileName": {
    "label": "File",
    "format": "string"
  },
  "durationMs": {
    "label": "Duration (ms)",
    "format": "integer"
  },
  "language": {
    "label": "Language",
    "format": "string"
  },
  "model": {
    "label": "Tier",
    "format": "string"
  },
  "chunks": {
    "label": "Chunks",
    "format": "array"
  },
  "error": {
    "label": "Error",
    "format": "string"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Audio & Video Transcription to JSON: RAG Chunks + Timestamps Actor is ready to run with the inputs already set for "Podcast Episode to RAG Chunks with Time Citations". [Sign up or log in](https://console.apify.com/create-task-from-example/xz1YLvqsaKpjeWoy8) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Podcast Episode to RAG Chunks with Time Citations" task

The Audio & Video Transcription to JSON: RAG Chunks + Timestamps Actor will start running based on the input automatically. You can also change all the input fields, like audio or video urls, accuracy tier, and more, to match your specific use case.

### 3. Receive the "Podcast Episode to RAG Chunks with Time Citations" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as source url, file, duration (ms), and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Podcast Episode to RAG Chunks with Time Citations" task via API](https://apify.com/landoz/transcribe-to-json-chunks.md).

## About this Actor

This example demonstrates how to use [Audio & Video Transcription to JSON: RAG Chunks + Timestamps](https://apify.com/landoz/transcribe-to-json-chunks.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/landoz/transcribe-to-json-chunks.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/landoz/transcribe-to-json-chunks.md

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`).