Deepgram Hello World

Overview

Minimal working examples for Deepgram speech-to-text. Transcribe an audio URL in 5 lines with createClient + listen.prerecorded.transcribeUrl. Includes local file transcription, Python equivalent, and Nova-3 model selection.

Prerequisites

• npm install @deepgram/sdk completed
• DEEPGRAMAPIKEY environment variable set
• Audio source: URL or local file (WAV, MP3, FLAC, OGG, M4A)

Instructions

Step 1: Transcribe Audio from URL (TypeScript)

import { createClient } from '@deepgram/sdk';

const deepgram = createClient(process.env.DEEPGRAM_API_KEY!);

async function main() {
  const { result, error } = await deepgram.listen.prerecorded.transcribeUrl(
    { url: 'https://static.deepgram.com/examples/Bueller-Life-moves-702702706.wav' },
    {
      model: 'nova-3',        // Latest model — best accuracy
      smart_format: true,     // Auto-punctuation, paragraphs, numerals
      language: 'en',
    }
  );

  if (error) throw error;

  const transcript = result.results.channels[0].alternatives[0].transcript;
  console.log('Transcript:', transcript);
  console.log('Confidence:', result.results.channels[0].alternatives[0].confidence);
}

main();

Step 2: Transcribe a Local File

import { createClient } from '@deepgram/sdk';
import { readFileSync } from 'fs';

const deepgram = createClient(process.env.DEEPGRAM_API_KEY!);

async function transcribeFile(filePath: string) {
  const audio = readFileSync(filePath);

  const { result, error } = await deepgram.listen.prerecorded.transcribeFile(
    audio,
    {
      model: 'nova-3',
      smart_format: true,
      // Deepgram auto-detects format, but you can specify:
      mimetype: 'audio/wav',
    }
  );

  if (error) throw error;

  console.log(result.results.channels[0].alternatives[0].transcript);
}

transcribeFile('./meeting-recording.wav');

Step 3: Python Equivalent

import os
from deepgram import DeepgramClient, PrerecordedOptions

client = DeepgramClient(os.environ["DEEPGRAM_API_KEY"])

# URL transcription
url = {"url": "https://static.deepgram.com/examples/Bueller-Life-moves-702702706.wav"}
options = PrerecordedOptions(model="nova-3", smart_format=True, language="en")

response = client.listen.rest.v("1").transcribe_url(url, options)
transcript = response.results.channels[0].alternatives[0].transcript
print(f"Transcript: {transcript}")
print(f"Confidence: {response.results.channels[0].alternatives[0].confidence}")

# Local file transcription
with open("meeting.wav", "rb") as audio:
    source = {"buffer": audio.read(), "mimetype": "audio/wav"}
    response = client.listen.rest.v("1").transcribe_file(source, options)
    print(response.results.channels[0].alternatives[0].transcript)

Step 4: Add Features

// Enable diarization (speaker identification)
const { result } = await deepgram.listen.prerecorded.transcribeUrl(
  { url: audioUrl },
  {
    model: 'nova-3',
    smart_format: true,
    diarize: true,         // Speaker labels
    utterances: true,      // Turn-by-turn segments
    paragraphs: true,      // Paragraph formatting
  }
);

// Print speaker-labeled output
if (result.results.utterances) {
  for (const utterance of result.results.utterances) {
    console.log(`Speaker ${utterance.speaker}: ${utterance.transcript}`);
  }
}

Step 5: Explore Model Options

Step 6: Run It

# TypeScript
npx tsx hello-deepgram.ts

# Python
python hello_deepgram.py

Output

• Working transcription from URL or local file
• Printed transcript text with confidence score
• Optional: speaker-labeled utterances

Error Handling

Resources

• Pre-recorded Audio Guide
• Model Options
• Smart Formatting
• Sample Audio Files

Next Steps

Proceed to deepgram-core-workflow-a for production transcription patterns or deepgram-core-workflow-b for live streaming.