deepgram-reference-architecture

Implement Deepgram reference architecture for scalable transcription systems. Use when designing transcription pipelines, building production architectures, or planning Deepgram integration at scale. Trigger: "deepgram architecture", "transcription pipeline", "deepgram system design", "deepgram at scale", "enterprise deepgram", "deepgram queue".

1,868 stars

Best use case

deepgram-reference-architecture is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Implement Deepgram reference architecture for scalable transcription systems. Use when designing transcription pipelines, building production architectures, or planning Deepgram integration at scale. Trigger: "deepgram architecture", "transcription pipeline", "deepgram system design", "deepgram at scale", "enterprise deepgram", "deepgram queue".

Teams using deepgram-reference-architecture should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/deepgram-reference-architecture/SKILL.md --create-dirs "https://raw.githubusercontent.com/jeremylongshore/claude-code-plugins-plus-skills/main/plugins/saas-packs/deepgram-pack/skills/deepgram-reference-architecture/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/deepgram-reference-architecture/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How deepgram-reference-architecture Compares

Feature / Agentdeepgram-reference-architectureStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Implement Deepgram reference architecture for scalable transcription systems. Use when designing transcription pipelines, building production architectures, or planning Deepgram integration at scale. Trigger: "deepgram architecture", "transcription pipeline", "deepgram system design", "deepgram at scale", "enterprise deepgram", "deepgram queue".

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Deepgram Reference Architecture

## Overview
Four reference architectures for Deepgram transcription at scale: synchronous REST for short files, async queue (BullMQ) for batch processing, WebSocket proxy for real-time streaming, and a hybrid router that auto-selects the best pattern based on audio duration.

## Architecture Selection Guide

| Pattern | Best For | Latency | Throughput | Complexity |
|---------|----------|---------|------------|------------|
| Sync REST | Files <60s, low volume | Low | Low | Simple |
| Async Queue | Batch, files >60s | Medium | High | Medium |
| WebSocket Proxy | Live audio, real-time | Real-time | Medium | Medium |
| Hybrid Router | Mixed workloads | Varies | High | High |
| Callback | Files >5min, fire-and-forget | N/A | Very High | Low |

## Instructions

### Step 1: Synchronous REST Pattern

```typescript
import express from 'express';
import { createClient } from '@deepgram/sdk';

const app = express();
app.use(express.json());

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

// Direct API call — best for short files (<60s)
app.post('/api/transcribe', async (req, res) => {
  const { url, model = 'nova-3', diarize = false } = req.body;

  try {
    const { result, error } = await deepgram.listen.prerecorded.transcribeUrl(
      { url },
      { model, smart_format: true, diarize, utterances: diarize }
    );
    if (error) return res.status(502).json({ error: error.message });

    res.json({
      transcript: result.results.channels[0].alternatives[0].transcript,
      confidence: result.results.channels[0].alternatives[0].confidence,
      duration: result.metadata.duration,
      request_id: result.metadata.request_id,
      utterances: diarize ? result.results.utterances : undefined,
    });
  } catch (err: any) {
    res.status(500).json({ error: err.message });
  }
});
```

### Step 2: Async Queue Pattern (BullMQ)

```typescript
import { Queue, Worker, Job } from 'bullmq';
import { createClient } from '@deepgram/sdk';
import Redis from 'ioredis';

const connection = new Redis(process.env.REDIS_URL ?? 'redis://localhost:6379');

// Producer: submit transcription jobs
const transcriptionQueue = new Queue('transcription', { connection });

async function submitJob(audioUrl: string, options: Record<string, any> = {}) {
  const job = await transcriptionQueue.add('transcribe', {
    audioUrl,
    model: options.model ?? 'nova-3',
    diarize: options.diarize ?? false,
    submittedAt: new Date().toISOString(),
  }, {
    attempts: 3,
    backoff: { type: 'exponential', delay: 5000 },
    removeOnComplete: { age: 86400 },  // Keep for 24h
  });

  console.log(`Job submitted: ${job.id}`);
  return job.id;
}

// Consumer: process transcription jobs
const deepgram = createClient(process.env.DEEPGRAM_API_KEY!);

const worker = new Worker('transcription', async (job: Job) => {
  const { audioUrl, model, diarize } = job.data;
  console.log(`Processing job ${job.id}: ${audioUrl}`);

  const { result, error } = await deepgram.listen.prerecorded.transcribeUrl(
    { url: audioUrl },
    { model, smart_format: true, diarize, utterances: diarize }
  );

  if (error) throw new Error(`Deepgram error: ${error.message}`);

  const output = {
    transcript: result.results.channels[0].alternatives[0].transcript,
    confidence: result.results.channels[0].alternatives[0].confidence,
    duration: result.metadata.duration,
    request_id: result.metadata.request_id,
  };

  // Store result (database, S3, etc.)
  console.log(`Job ${job.id} complete: ${output.duration}s audio`);
  return output;
}, {
  connection,
  concurrency: 10,     // Process 10 jobs simultaneously
  limiter: {
    max: 50,           // Max 50 per time window
    duration: 60000,   // Per minute
  },
});

worker.on('completed', (job) => console.log(`Completed: ${job.id}`));
worker.on('failed', (job, err) => console.error(`Failed: ${job?.id}`, err.message));
```

### Step 3: WebSocket Proxy for Real-Time

```typescript
import { WebSocketServer, WebSocket } from 'ws';
import { createClient, LiveTranscriptionEvents } from '@deepgram/sdk';

const wss = new WebSocketServer({ port: 8080 });

wss.on('connection', (clientWs: WebSocket) => {
  console.log('Client connected');

  const deepgram = createClient(process.env.DEEPGRAM_API_KEY!);
  const dgConnection = deepgram.listen.live({
    model: 'nova-3',
    smart_format: true,
    interim_results: true,
    utterance_end_ms: 1000,
    encoding: 'linear16',
    sample_rate: 16000,
    channels: 1,
  });

  // Forward Deepgram transcripts to client
  dgConnection.on(LiveTranscriptionEvents.Transcript, (data) => {
    const transcript = data.channel.alternatives[0]?.transcript;
    if (transcript && clientWs.readyState === WebSocket.OPEN) {
      clientWs.send(JSON.stringify({
        type: 'transcript',
        text: transcript,
        is_final: data.is_final,
        speech_final: data.speech_final,
      }));
    }
  });

  dgConnection.on(LiveTranscriptionEvents.UtteranceEnd, () => {
    if (clientWs.readyState === WebSocket.OPEN) {
      clientWs.send(JSON.stringify({ type: 'utterance_end' }));
    }
  });

  // Forward client audio to Deepgram
  clientWs.on('message', (data: Buffer) => {
    if (dgConnection.getReadyState() === 1) {
      dgConnection.send(data);
    }
  });

  // Cleanup on disconnect
  clientWs.on('close', () => {
    dgConnection.finish();
    console.log('Client disconnected');
  });

  dgConnection.on(LiveTranscriptionEvents.Error, (err) => {
    console.error('Deepgram error:', err.message);
    clientWs.close();
  });
});

console.log('WebSocket proxy on ws://localhost:8080');
```

### Step 4: Hybrid Router

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

class TranscriptionRouter {
  private client: ReturnType<typeof createClient>;
  private queue: typeof transcriptionQueue;

  constructor(apiKey: string, queue: any) {
    this.client = createClient(apiKey);
    this.queue = queue;
  }

  async route(audioUrl: string, options: {
    mode?: 'sync' | 'async' | 'callback' | 'auto';
    estimatedDuration?: number;  // seconds
    callbackUrl?: string;
    model?: string;
    diarize?: boolean;
  } = {}) {
    const mode = options.mode ?? 'auto';
    const duration = options.estimatedDuration ?? 0;

    // Auto-select based on duration
    const selectedMode = mode === 'auto'
      ? duration > 300 ? 'callback'   // >5 min: use callback
        : duration > 60 ? 'async'     // >60s: use queue
        : 'sync'                       // <60s: direct API
      : mode;

    console.log(`Routing: ${selectedMode} (est. ${duration}s)`);

    switch (selectedMode) {
      case 'sync':
        return this.syncTranscribe(audioUrl, options);
      case 'async':
        return this.asyncTranscribe(audioUrl, options);
      case 'callback':
        return this.callbackTranscribe(audioUrl, options);
    }
  }

  private async syncTranscribe(url: string, opts: any) {
    const { result, error } = await this.client.listen.prerecorded.transcribeUrl(
      { url },
      { model: opts.model ?? 'nova-3', smart_format: true, diarize: opts.diarize }
    );
    if (error) throw error;
    return { mode: 'sync', result };
  }

  private async asyncTranscribe(url: string, opts: any) {
    const jobId = await submitJob(url, opts);
    return { mode: 'async', jobId };
  }

  private async callbackTranscribe(url: string, opts: any) {
    const { result } = await this.client.listen.prerecorded.transcribeUrl(
      { url },
      { model: opts.model ?? 'nova-3', smart_format: true, callback: opts.callbackUrl }
    );
    return { mode: 'callback', requestId: result.metadata.request_id };
  }
}
```

### Step 5: Architecture Diagram

```
                    ┌──────────────┐
                    │   Client     │
                    └──────┬───────┘
                           │
                    ┌──────▼───────┐
                    │   API Gateway │
                    │  /transcribe  │
                    └──────┬───────┘
                           │
                    ┌──────▼───────┐
                    │ Hybrid Router │
                    └──┬───┬───┬───┘
                       │   │   │
           ┌───────────┘   │   └───────────┐
           ▼               ▼               ▼
    ┌──────────┐   ┌──────────┐   ┌──────────┐
    │   Sync   │   │  Queue   │   │ Callback │
    │  (<60s)  │   │ (BullMQ) │   │  (>5min) │
    └────┬─────┘   └────┬─────┘   └────┬─────┘
         │              │              │
         └──────────┬───┘──────────────┘
                    │
            ┌───────▼──────┐
            │  Deepgram    │
            │  API         │
            └───────┬──────┘
                    │
            ┌───────▼──────┐
            │   Results    │
            │   Store      │
            └──────────────┘
```

## Output
- Sync REST endpoint for short files
- BullMQ queue with workers for batch processing
- WebSocket proxy for real-time streaming
- Hybrid router with auto-mode selection
- Architecture diagram

## Error Handling
| Issue | Cause | Solution |
|-------|-------|----------|
| Sync timeout on large file | Wrong pattern selected | Use async queue or callback |
| Queue backlog growing | Workers overloaded | Scale workers, increase concurrency |
| WebSocket disconnects | Network instability | Auto-reconnect with backoff |
| Callback not received | Endpoint unreachable | Check HTTPS, verify callback URL |

## Resources
- [Deepgram Architecture Guide](https://developers.deepgram.com/docs/architecture)
- [BullMQ Documentation](https://docs.bullmq.io/)
- [WebSocket API](https://developer.mozilla.org/en-US/docs/Web/API/WebSockets_API)

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