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deepgram-core-workflow-b Implement real-time streaming transcription with Deepgram WebSocket.
Use when building live transcription, voice interfaces,
real-time captioning, or voice AI applications.
Trigger: "deepgram streaming", "real-time transcription", "live transcription",
"websocket transcription", "voice streaming", "deepgram live".
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Use when building authentication UI, customizing sign-in experience,
or implementing OAuth social login.
Trigger with phrases like "clerk sign-in", "clerk sign-up",
"clerk login flow", "clerk OAuth", "clerk social login".
Implement session management and middleware with Clerk.
Use when managing user sessions, configuring route protection,
or implementing token refresh and custom JWT templates.
Trigger with phrases like "clerk session", "clerk middleware",
"clerk route protection", "clerk token", "clerk JWT".
Configure enterprise SSO, role-based access control, and organization management.
Use when implementing SSO integration, configuring role-based permissions,
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Trigger with phrases like "clerk SSO", "clerk RBAC",
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jeremylongshore
jeremylongshore/claude-code-plugins-plus-skills
GitHub 저장소 열기 name deepgram-core-workflow-b description Implement real-time streaming transcription with Deepgram WebSocket.
Use when building live transcription, voice interfaces,
real-time captioning, or voice AI applications.
Trigger: "deepgram streaming", "real-time transcription", "live transcription",
"websocket transcription", "voice streaming", "deepgram live".
allowed-tools Read, Write, Edit, Bash(npm:*), Bash(pip:*), Grep version 1.13.0 license MIT author Jeremy Longshore <jeremy@intentsolutions.io> tags ["saas","deepgram","voice-ai","transcription","streaming","websocket"] compatibility Designed for Claude Code, also compatible with Codex and OpenClaw
Deepgram Core Workflow B: Live Streaming Transcription
Overview
Real-time streaming transcription using Deepgram's WebSocket API. The SDK manages the WebSocket connection via listen.live(). Covers microphone capture, interim/final result handling, speaker diarization, UtteranceEnd detection, auto-reconnect, and building an SSE endpoint for browser clients.
Prerequisites
@deepgram/sdk installed, DEEPGRAM_API_KEY configured
Audio source: microphone (via Sox/rec), file stream, or WebSocket audio from browser
For mic capture: sox installed (apt install sox / brew install sox)
Instructions
Step 1: Basic Live Transcription
import { createClient, LiveTranscriptionEvents } from '@deepgram/sdk' ;
const deepgram = createClient (process.env .DEEPGRAM_API_KEY !);
const connection = deepgram.listen .live ({
model : 'nova-3' ,
language : 'en' ,
smart_format : true ,
punctuate : true ,
interim_results : true ,
utterance_end_ms : 1000 ,
vad_events : true ,
encoding : 'linear16' ,
sample_rate : 16000 ,
: ,
});
connection. ( . , {
. ( );
});
connection. ( . , {
. ( );
});
connection. ( . , {
. ( , err);
});
connection. ( . , {
transcript = data. . [ ]?. ;
(!transcript) ;
(data. ) {
. ( );
} {
process. . ( );
}
});
connection. ( . , {
. ( );
});
channels
1
on
LiveTranscriptionEvents
Open
() =>
console
log
'WebSocket connected to Deepgram'
on
LiveTranscriptionEvents
Close
() =>
console
log
'WebSocket closed'
on
LiveTranscriptionEvents
Error
(err ) =>
console
error
'Deepgram error:'
on
LiveTranscriptionEvents
Transcript
(data ) =>
const
channel
alternatives
0
transcript
if
return
if
is_final
console
log
`[FINAL] ${transcript} `
else
stdout
write
`\r[interim] ${transcript} `
on
LiveTranscriptionEvents
UtteranceEnd
() =>
console
log
'\n--- utterance end ---'
Step 2: Microphone Capture with Sox import { spawn } from 'child_process' ;
function startMicrophone (connection : any ) {
const mic = spawn ('rec' , [
'-q' ,
'-r' , '16000' ,
'-e' , 'signed' ,
'-b' , '16' ,
'-c' , '1' ,
'-t' , 'raw' ,
'-' ,
]);
mic.stdout .on ('data' , (chunk : Buffer ) => {
if (connection.getReadyState () === 1 ) {
connection.send (chunk);
}
});
mic.on ('error' , (err ) => {
console .error ('Microphone error:' , err.message );
console .log ('Install sox: apt install sox / brew install sox' );
});
return mic;
}
const mic = startMicrophone (connection);
process.on ('SIGINT' , () => {
mic.kill ();
connection.finish ();
setTimeout (() => process.exit (0 ), 2000 );
});
Step 3: Live Diarization const connection = deepgram.listen .live ({
model : 'nova-3' ,
smart_format : true ,
diarize : true ,
interim_results : false ,
utterance_end_ms : 1500 ,
encoding : 'linear16' ,
sample_rate : 16000 ,
channels : 1 ,
});
connection.on (LiveTranscriptionEvents .Transcript , (data ) => {
if (!data.is_final ) return ;
const words = data.channel .alternatives [0 ]?.words ?? [];
if (words.length === 0 ) return ;
let currentSpeaker = words[0 ].speaker ;
let segment = '' ;
for (const word of words) {
if (word.speaker !== currentSpeaker) {
console .log (`Speaker ${currentSpeaker} : ${segment.trim()} ` );
currentSpeaker = word.speaker ;
segment = '' ;
}
segment += ` ${word.punctuated_word ?? word.word} ` ;
}
console .log (`Speaker ${currentSpeaker} : ${segment.trim()} ` );
});
Step 4: Auto-Reconnect with Backoff class ReconnectingLiveTranscription {
private client : ReturnType <typeof createClient>;
private connection : any = null ;
private reconnectAttempts = 0 ;
private maxReconnectAttempts = 10 ;
private baseDelay = 1000 ;
constructor (apiKey : string , private options : Record <string , any > ) {
this .client = createClient (apiKey);
}
connect ( ) {
this .connection = this .client .listen .live (this .options );
this .connection .on (LiveTranscriptionEvents .Open , () => {
console .log ('Connected' );
this .reconnectAttempts = 0 ;
});
this .connection .on (LiveTranscriptionEvents .Close , () => {
this .scheduleReconnect ();
});
this .connection .on (LiveTranscriptionEvents .Error , (err : Error ) => {
console .error ('Connection error:' , err.message );
this .scheduleReconnect ();
});
return this .connection ;
}
private scheduleReconnect ( ) {
if (this .reconnectAttempts >= this .maxReconnectAttempts ) {
console .error ('Max reconnection attempts reached' );
return ;
}
const delay = this .baseDelay * Math .pow (2 , this .reconnectAttempts )
+ Math .random () * 1000 ;
this .reconnectAttempts ++;
console .log (`Reconnecting in ${Math .round(delay)} ms (attempt ${this .reconnectAttempts} )` );
setTimeout (() => this .connect (), delay);
}
send (chunk : Buffer ) {
if (this .connection ?.getReadyState () === 1 ) {
this .connection .send (chunk);
}
}
close ( ) {
this .maxReconnectAttempts = 0 ;
this .connection ?.finish ();
}
}
Step 5: SSE Endpoint for Browser Clients import express from 'express' ;
import { createClient, LiveTranscriptionEvents } from '@deepgram/sdk' ;
const app = express ();
app.get ('/api/transcribe/stream' , (req, res ) => {
res.setHeader ('Content-Type' , 'text/event-stream' );
res.setHeader ('Cache-Control' , 'no-cache' );
res.setHeader ('Connection' , 'keep-alive' );
const deepgram = createClient (process.env .DEEPGRAM_API_KEY !);
const connection = deepgram.listen .live ({
model : 'nova-3' ,
smart_format : true ,
interim_results : true ,
encoding : 'linear16' ,
sample_rate : 16000 ,
channels : 1 ,
});
connection.on (LiveTranscriptionEvents .Transcript , (data ) => {
const transcript = data.channel .alternatives [0 ]?.transcript ;
if (transcript) {
res.write (`data: ${JSON .stringify({
transcript,
is_final: data.is_final,
speech_final: data.speech_final,
})} \n\n` );
}
});
req.on ('close' , () => {
connection.finish ();
});
});
Step 6: KeepAlive for Long Sessions
connection.on (LiveTranscriptionEvents .Open , () => {
const keepAliveInterval = setInterval (() => {
if (connection.getReadyState () === 1 ) {
connection.keepAlive ();
}
}, 8000 );
connection.on (LiveTranscriptionEvents .Close , () => {
clearInterval (keepAliveInterval);
});
});
Output
Live WebSocket transcription with interim/final results
Microphone capture pipeline (Sox -> Deepgram)
Speaker diarization in streaming mode
Auto-reconnect with exponential backoff and jitter
SSE endpoint for browser integration
KeepAlive handling for long sessions
Error Handling Issue Cause Solution WebSocket closes immediately Invalid API key or bad encoding params Check key, verify encoding/sample_rate match audio No transcripts received Audio not being sent or wrong format Verify connection.send(chunk) is called with raw PCM High latency Network congestion Use interim_results: true for perceived speed rec command not foundSox not installed apt install sox or brew install soxConnection drops after 10s No audio + no KeepAlive Send connection.keepAlive() every 8s Garbled output Sample rate mismatch Ensure audio sample rate matches sample_rate option
Resources
Next Steps Proceed to deepgram-data-handling for transcript processing and storage patterns.