Skip to content

220-django-channels-live-stt-python

Directory actions

More options

Directory actions

More options

Latest commit

 

History

History

220-django-channels-live-stt-python

Folders and files

NameName
Last commit message
Last commit date

parent directory

..
src
src
 
 
tests
tests
 
 
.env.example
.env.example
 
 
README.md
README.md
 
 
requirements.txt
requirements.txt
 
 

README.md

Django Channels Real-Time Transcription with Deepgram Live STT

Build a Django 5 application that captures browser microphone audio and streams it through Django Channels WebSockets to Deepgram's Live STT API, displaying transcription results on the page in real-time. The Deepgram API key stays server-side — the browser never sees it.

What you'll build

A Django web application that uses Django Channels to handle WebSocket connections from the browser. When a user clicks "Start Listening", the page captures microphone audio, streams it over a WebSocket to a Django Channels consumer, which forwards it to Deepgram's Live STT API (Nova-3). Transcription results flow back through the same WebSocket and appear on the page instantly.

Prerequisites

Environment variables

Variable Where to find it
DEEPGRAM_API_KEY Deepgram console

Copy .env.example to .env and fill in your values.

Install and run

cd examples/220-django-channels-live-stt-python

pip install -r requirements.txt

cp .env.example .env
# Edit .env and add your DEEPGRAM_API_KEY

python src/manage.py runserver

Then open http://127.0.0.1:8000 in your browser and click Start Listening.

Key parameters

Parameter Value Description
model nova-3 Deepgram's latest and most accurate speech recognition model
smart_format True Adds punctuation, capitalization, and number formatting
interim_results True Returns partial transcripts while you're still speaking
encoding linear16 Raw 16-bit PCM audio format from the browser
sample_rate 16000 16 kHz sample rate — good balance of quality and bandwidth

How it works

  1. Browser — the HTML page uses getUserMedia to capture microphone audio, resamples it to 16 kHz linear16 PCM via a ScriptProcessorNode, and sends binary frames over a WebSocket to /ws/transcribe/
  2. Django Channels consumer (consumer.py) — an AsyncWebsocketConsumer that on connect opens a Deepgram live STT WebSocket using the official Python SDK (client.listen.v1.connect())
  3. Audio forwarding — each binary WebSocket frame from the browser is forwarded to Deepgram via connection.send_media()
  4. Transcript delivery — Deepgram fires EventType.MESSAGE callbacks with ListenV1Results; the consumer sends each transcript back to the browser as JSON with is_final indicating whether the result is finalized
  5. Browser display — interim results appear greyed out and get replaced; final results are appended permanently

Architecture

Browser Microphone
       |
       | WebSocket (binary PCM audio)
       v
Django Channels Consumer
       |
       | Deepgram Python SDK (WebSocket)
       v
Deepgram Live STT (nova-3)
       |
       | transcript JSON
       v
Django Channels Consumer
       |
       | WebSocket (JSON)
       v
Browser Display

Related

Starter templates

If you want a ready-to-run base for your own project, check the deepgram-starters org — there are starter repos for every language and every Deepgram product.