YouTube transcripts for RAG and LLM pipelines
Turn a YouTube channel into a text corpus for retrieval-augmented generation (RAG), embeddings or LLM fine-tuning. Each row holds the full transcript plus timed segments (start time, duration, text), so every chunk can cite the exact moment in the video. Output as JSON, CSV or Excel. Example input: the Lex Fridman Podcast, 20 latest videos.
Input
Output fields
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The YouTube Transcript API: Any Video, Channel or Playlist Actor is ready to run with the inputs already set for "YouTube transcripts for RAG and LLM pipelines". Sign up or log in and you'll land in Apify Console with a copy of this exact task.
Start the "YouTube transcripts for RAG and LLM pipelines" task
The YouTube Transcript API: Any Video, Channel or Playlist Actor will start running based on the input automatically. You can also change all the input fields, like channels, playlists, videos or search terms, max videos per channel, playlist or search, and more, to match your specific use case.
Receive the "YouTube transcripts for RAG and LLM pipelines" 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 title, video type, views (exact), 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 "YouTube transcripts for RAG and LLM pipelines" task via API.
Integrate "YouTube transcripts for RAG and LLM pipelines" into your workflow
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