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Podcast generation

Skill ComeOnOliver/skillshub/skills/aiskillstore/marketplace/sickn33/podcast-generation

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Install
npx -y skills add ComeOnOliver/skillshub --skill podcast-generation

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What its author says it does

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Generate AI-powered podcast-style audio narratives using Azure OpenAI's GPT Realtime Mini model via WebSocket. Use when building text-to-speech features, audio narrative generation, podcast creation from content, or integrating with Azure OpenAI Realtime API for real audio output. Covers full-stack implementation from React frontend to Python FastAPI backend with WebSocket streaming.

SKILL.md

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Podcast Generation with GPT Realtime Mini

Generate real audio narratives from text content using Azure OpenAI's Realtime API.

Quick Start

  1. Configure environment variables for Realtime API
  2. Connect via WebSocket to Azure OpenAI Realtime endpoint
  3. Send text prompt, collect PCM audio chunks + transcript
  4. Convert PCM to WAV format
  5. Return base64-encoded audio to frontend for playback

Environment Configuration

AZURE_OPENAI_AUDIO_API_KEY=your_realtime_api_key
AZURE_OPENAI_AUDIO_ENDPOINT=https://your-resource.cognitiveservices.azure.com
AZURE_OPENAI_AUDIO_DEPLOYMENT=gpt-realtime-mini

Note: Endpoint should NOT include /openai/v1/ - just the base URL.

Core Workflow

Backend Audio Generation

from openai import AsyncOpenAI
import base64

# Convert HTTPS endpoint to WebSocket URL
ws_url = endpoint.replace("https://", "wss://") + "/openai/v1"

client = AsyncOpenAI(
    websocket_base_url=ws_url,
    api_key=api_key
)

audio_chunks = []
transcript_parts = []

async with client.realtime.connect(model="gpt-realtime-mini") as conn:
    # Configure for audio-only output
    await conn.session.update(session={
        "output_modalities": ["audio"],
        "instructions": "You are a narrator. Speak naturally."
    })
    
    # Send text to narrate
    await conn.conversation.item.create(item={
        "type": "message",
        "role": "user",
        "content": [{"type": "input_text", "text": prompt}]
    })
    
    await conn.response.create()
    
    # Collect streaming events
    async for event in conn:
        if event.type == "response.output_audio.delta":
            audio_chunks.append(base64.b64decode(event.delta))
        elif event.type == "response.output_audio_transcript.delta":
            transcript_parts.append(event.delta)
        elif event.type == "response.done":
            break

# Convert PCM to WAV (see scripts/pcm_to_wav.py)
pcm_audio = b''.join(audio_chunks)
wav_audio = pcm_to_wav(pcm_audio, sample_rate=24000)

Frontend Audio Playback

// Convert base64 WAV to playable blob
const base64ToBlob = (base64, mimeType) => {
  const bytes = atob(base64);
  const arr = new Uint8Array(bytes.length);
  for (let i = 0; i < bytes.length; i++) arr[i] = bytes.charCodeAt(i);
  return new Blob([arr], { type: mimeType });
};

const audioBlob = base64ToBlob(response.audio_data, 'audio/wav');
const audioUrl = URL.createObjectURL(audioBlob);
new Audio(audioUrl).play();

Voice Options

VoiceCharacter
alloyNeutral
echoWarm
fableExpressive
onyxDeep
novaFriendly
shimmerClear

Realtime API Events

  • response.output_audio.delta - Base64 audio chunk
  • response.output_audio_transcript.delta - Transcript text
  • response.done - Generation complete
  • error - Handle with event.error.message

Audio Format

  • Input: Text prompt
  • Output: PCM audio (24kHz, 16-bit, mono)
  • Storage: Base64-encoded WAV

References

Gives 1 of the 12 instructions most video audio skills give

Counted across 621 of the 795 authors here whose files we hold, read 2026-08-06

  • read individual rule files for detailed explanationsin 21 of 621, across 9 files
  • Use WAV PCM 16kHz mono audio formathere, and in 13 of 621, across 4 files
  • render final videoin 13 of 621, across 6 files
  • use this skill when dealing with Remotion codein 11 of 621, across 4 files
  • save generated audio to a WAV filein 11 of 621, across 4 files
  • handle conversion errors gracefullyin 10 of 621, across 6 files
  • add captions to videos alwaysin 10 of 621, across 4 files
  • generate music from text descriptions using MusicGenin 9 of 621, across 2 files
  • do not skip pipeline layersin 9 of 621, across 3 files
  • do not make one tool do everythingin 9 of 621, across 3 files
  • never ask the user to paste their full API keyin 9 of 621, across 3 files
  • use azure document intelligence for complex pdfsin 9 of 621, across 4 files

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.

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