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Illustrative: Dots-style transcript → timestamped RAG chunks

Illustrative sample only. Shows how SRT cues become timestamped JSON chunks. Not an official OpenAI transcript and not a verified public file we host.

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SRT & WebVTT to JSON Subtitle Chunker for RAG
SRT & WebVTT to JSON Subtitle Chunker for RAGskilled_glee/subtitle-rag-chunker
sourceName
startTimestampMs
endTimestampMs
text
+1 field
Text
Number
Boolean
List
Object

Input

Subtitle inputs
Raw subtitle text:1 00:00:01,000 --> 00:00:06,000 Today we are introducing Dots, always-on AI agents powered by GPT-6 Astra. 2 00:00:06,000 --> 00:00:12,000 Each Dot gets its own cloud computer and connects to more than four thousand apps. 3 00:00:12,000 --> 00:00:18,000 Dots learn how you work and keep working in the background while you focus. 4 00:00:18,000 --> 00:00:24,000 Enterprise admins can enable organization-wide Dots with policy controls.
Source name:illustrative-dots-style-transcript
Chunk size:1500
Overlap:150

Output fields

sourceName
startTimestampMs
endTimestampMs
text
chunkId

How it works

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The SRT & WebVTT to JSON Subtitle Chunker for RAG Actor is ready to run with the inputs already set for "Illustrative: Dots-style transcript → timestamped RAG chunks". Sign up or log in and you'll land in Apify Console with a copy of this exact task.

Start the "Illustrative: Dots-style transcript → timestamped RAG chunks" task

The SRT & WebVTT to JSON Subtitle Chunker for RAG Actor will start running based on the input automatically. You can also change all the input fields, like subtitle inputs, to match your specific use case.

Receive the "Illustrative: Dots-style transcript → timestamped RAG chunks" 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 sourcename, starttimestampms, endtimestampms, and more.

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 "Illustrative: Dots-style transcript → timestamped RAG chunks" task via API.

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