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Podcast transcriptions include best-effort speaker diarization: each segment may carry a `speaker` integer (0, 1, …) identifying who is talking. The ids are hints from voice separation, not named identification, and non-podcast sources never carry them.
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Batch works the same way by default (`mode="auto"`): entries with no caption track are transcribed from audio, come back with `outcome == "processing"` and a `job_id`, cost nothing on that call, and are charged on delivery at the audio rate. Re-send the same batch once the jobs have had time to finish and the text comes back normally — or poll each `job_id` with `tf.transcripts.job()`. Pass `mode="captions"` to read existing caption tracks only, in which case a captionless video fails as `no_transcript` (the old behaviour):
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Batch works the same way by default (`mode="auto"`): entries with no caption track are transcribed from audio, come back with `outcome == "processing"` and a `job_id`, cost nothing on that call, and are charged on delivery at the audio rate. Re-send the same batch once the jobs have had time to finish and the text comes back normally — or poll each `job_id` with `tf.transcripts.job()`. Pass `mode="captions"` to read existing caption tracks only, in which case a captionless video fails as `outcome == "error"` with `error.code == "no_captions"` (and `error.retry_with` naming the audio mode):
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```python
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res = tf.transcripts.batch(ids) # captionless entries -> "processing" + job_id
@@ -104,7 +104,7 @@ asyncio.run(main())
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## Errors
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All errors subclass `TranscriptFetchError`. API errors carry `.status`, `.code`, `.message`, and`.request_id`:
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All errors subclass `TranscriptFetchError`. API errors carry `.status`, `.code`, `.number` (the thousands digit is the family; 5xxx means retry), `.message`, `.docs`,`.retry_with` (the request change that would succeed, when there is one), `.details`, `.request_id`, and a `.retryable` property:
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