Deepgram

Purpose

Transcribe prerecorded audio files to text (with optional diarization, summaries, topics, sentiment) and synthesize speech with Deepgram's Aura voices. Reach for this when the user has an audio file to transcribe or wants spoken audio generated from text.

Tooling

All commands go through bin/deepgram.py. Auth uses exactly Authorization: Token <api_key> (not Bearer); the CLI wires it through the credential surrogate.

bin/deepgram.py auth
# {"ok": true, "projects": 2} on success

bin/deepgram.py projects
# list Deepgram projects (id, name)

bin/deepgram.py transcribe --file meeting.wav
# upload a local audio file, print the transcript JSON

bin/deepgram.py transcribe --file call.mp3 --model nova-3 --diarize --summarize --topics --sentiment
# transcript with speaker labels plus summary, topics and sentiment

bin/deepgram.py tts --text "Thanks for listening." --out thanks.mp3
# synthesize with an Aura voice to a local MP3 file; prints the saved path

Notes:

• transcribe reads a local audio file, posts the bytes to POST /v1/listen, and prints the full transcript JSON. Content type is guessed from the file extension (wav, mp3, m4a, flac, ogg supported).
• tts posts {"text": "..."} to POST /v1/speak?model=<model>&encoding=mp3 (default model aura-2-thalia-en, 2,000-char limit) and saves the audio to --out (default deepgram-output.mp3).
• Live WebSocket STT (/v1/listen streaming) is real-time and outside CLI scope.

Auth

• Provider id: deepgram (credential is collected as custom.deepgram)
• Collection: Deepgram API key via the secure credential flow (credentials.request_api_access); create one in the Deepgram console
• Allowed hosts: api.deepgram.com
• Connect placement: custom_header:Authorization (the stored credential value must be exactly Token <api_key>, with the Token prefix; Bearer is not accepted)
• Status check: bin/deepgram.py auth