wispr-hello-world

Wispr Flow hello world for voice-to-text API integration. Use when integrating Wispr Flow dictation, WebSocket streaming, or building voice-powered applications. Trigger: "wispr hello world".

1,868 stars

Best use case

wispr-hello-world is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Wispr Flow hello world for voice-to-text API integration. Use when integrating Wispr Flow dictation, WebSocket streaming, or building voice-powered applications. Trigger: "wispr hello world".

Teams using wispr-hello-world 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/wispr-hello-world/SKILL.md --create-dirs "https://raw.githubusercontent.com/jeremylongshore/claude-code-plugins-plus-skills/main/plugins/saas-packs/wispr-pack/skills/wispr-hello-world/SKILL.md"

Manual Installation

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

How wispr-hello-world Compares

Feature / Agentwispr-hello-worldStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Wispr Flow hello world for voice-to-text API integration. Use when integrating Wispr Flow dictation, WebSocket streaming, or building voice-powered applications. Trigger: "wispr hello world".

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

# Wispr Flow Hello World

## Overview

Stream audio to Wispr Flow and receive real-time transcription. Wispr specializes in developer-context-aware dictation -- it understands code terms, CLI commands, and technical jargon.

## Instructions

### Step 1: Record and Transcribe (REST)

```python
import requests, os

# Transcribe an audio file
with open("voice-memo.wav", "rb") as audio:
    response = requests.post(
        "https://api.wisprflow.ai/api/v1/transcribe",
        headers={"Authorization": f"Bearer {os.environ['WISPR_API_KEY']}"},
        files={"audio": audio},
        data={"language": "en", "context": "programming"},
    )

result = response.json()
print(f"Text: {result['text']}")
print(f"Confidence: {result.get('confidence', 'N/A')}")
```

### Step 2: Real-Time Streaming (WebSocket)

```typescript
// Stream microphone audio to Wispr Flow
const ws = new WebSocket('wss://api.wisprflow.ai/api/v1/ws');

// Browser audio capture
const stream = await navigator.mediaDevices.getUserMedia({ audio: true });
const context = new AudioContext({ sampleRate: 16000 });
const source = context.createMediaStreamSource(stream);

const processor = context.createScriptProcessor(4096, 1, 1);
source.connect(processor);
processor.connect(context.destination);

processor.onaudioprocess = (event) => {
  const audioData = event.inputBuffer.getChannelData(0);
  // Convert Float32Array to Int16Array for transmission
  const int16 = new Int16Array(audioData.length);
  for (let i = 0; i < audioData.length; i++) {
    int16[i] = Math.max(-32768, Math.min(32767, audioData[i] * 32768));
  }
  ws.send(int16.buffer);
};

ws.onmessage = (event) => {
  const data = JSON.parse(event.data);
  if (data.type === 'partial') {
    console.log(`Partial: ${data.text}`);
  } else if (data.type === 'final') {
    console.log(`Final: ${data.text}`);
  }
};
```

## Output

```
Partial: implement a function that
Final: Implement a function that calculates the Fibonacci sequence using dynamic programming.
```

## Error Handling

| Error | Cause | Solution |
|-------|-------|----------|
| Garbled text | Wrong sample rate | Use 16kHz mono PCM |
| No results | Silence or noise | Check microphone input |
| High latency | REST endpoint | Use WebSocket for streaming |

## Resources

- [WebSocket Quickstart](https://api-docs.wisprflow.ai/websocket_quickstart)
- [Wispr Flow for Developers](https://wisprflow.ai/developers)

## Next Steps

Proceed to `wispr-local-dev-loop` for development workflow.

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