Create an AI Podcast Generator with ElevenLabs

Podcasts have exploded in popularity, but producing a full episode still means spending hours on research, script‑writing, recording, and editing. What if you could automate the whole pipeline? By combining a large‑language model (LLM) for content generation with a state‑of‑the‑art text‑to‑speech (TTS) service, you can spin up a fully voiced episode in minutes.

In this guide we’ll build a simple AI Podcast Generator that:

Everything is done with plain Python and a few command‑line tools, so you can drop it into a CI job, a serverless function, or your local dev environment.

If you don’t have an ElevenLabs account yet, grab a free trial through this affiliate link: https://try.elevenlabs.io/kr07zfuqn1bp. It gives you 10 k characters of TTS credit and access to a handful of premium voices.

# Save your keys as environment variables (never hard‑code them!) export OPENAI_API_KEY = "sk-..." export ELEVENLABS_API_KEY = "your-elevenlabs-key" Enter fullscreen mode Exit fullscreen mode Both services use bearer tokens in the Authorization header, so keeping them in the environment is the safest approach.

Below is a minimal wrapper around the OpenAI chat completion endpoint. It accepts a topic and returns a concise script split into paragraphs.

import os import json import httpx OPENAI_API_KEY = os. getenv ( " OPENAI_API_KEY " ) HEADERS = { " Authorization ": f " Bearer { OPENAI_API_KEY } " } def generate_script ( topic: str, paragraphs: int = 5 ) -> list [ str ]: prompt = f """ You are a podcast host. Write a { paragraphs } -paragraph script about ** { topic } **. Each paragraph should be a self‑contained speaking segment (≈40‑60 words).

Use a conversational tone, include a brief intro and a wrap‑up. """ payload = { " model ": " gpt-4o ", " messages ": [{ " role ": " user ", " content ": prompt }], " temperature ": 0.7, } resp = httpx. post ( " https://api.openai.com/v1/chat/completions ", headers = HEADERS, json = payload ) resp. raise_for_status () content = resp. json ()[ " choices " ][ 0 ][ " message " ][ " content " ] # Split on double newlines to get separate paragraphs return [ p. strip () for p in content. split ( " \n\n " ) if p. strip ()] Enter fullscreen mode Exit fullscreen mode Tip: Adjust temperature for more creative vs. deterministic output. For a news‑style podcast you might set it lower (0.3).

ElevenLabs provides a clean REST API that accepts plain text and returns an MP3 buffer. The following function wraps that call.

import pathlib import uuid ELEVENLABS_API_KEY = os. getenv ( " ELEVENLABS_API_KEY " ) ELEVEN_HEADERS = { " xi-api-key ": ELEVENLABS_API_KEY, " Content-Type ": " application/json ", } VOICE_ID = " 21m00Tcm4TlvDq8ikWAM " # Example: "Rachel" voice – change to your favorite def synthesize_paragraph ( text: str, output_dir: pathlib. Path ) -> pathlib. Path: payload = { " text ": text, " voice_settings ": { " stability ": 0.75, " similarity_boost ": 0.85 } } url = f " https://api.elevenlabs.io/v1/text-to-speech/ { VOICE_ID } " resp = httpx. post ( url, headers = ELEVEN_HEADERS, json = payload ) resp. raise_for_status () # Save MP3 with a unique name out_path = output_dir / f " { uuid. uuid4 () }.mp3 " out_path. write_bytes ( resp. content ) return out_path Enter fullscreen mode Exit fullscreen mode You can experiment with different voice IDs or even upload a custom cloned voice through ElevenLabs’ dashboard.

For a truly branded podcast, clone the voice of your host and reference it here – the same API call works with the cloned voice’s ID.

ffmpeg makes concatenation painless. First, write a temporary file list, then run the command.

import subprocess def combine_audio ( files: list [ pathlib. Path ], output: pathlib. Path ): list_path = output. parent / " files.txt " with open ( list_path, " w ", encoding = " utf-8 " ) as f: for p in files: f. write ( f " file ' { p. as_posix () } ' \n " ) # -safe 0 allows absolute paths cmd = [ " ffmpeg ", " -y ", " -f ", " concat ", " -safe ", " 0 ", " -i ", str ( list_path ), " -c ", " copy ", str ( output ) ] subprocess. run ( cmd, check = True ) list_path. unlink () # clean up Enter fullscreen mode Exit fullscreen mode 5. The Full Pipeline Putting everything together:

import pathlib def create_podcast ( topic: str, out_file: pathlib. Path ): work_dir = pathlib. Path ( " temp_audio " ) work_dir. mkdir ( exist_ok = True ) # 1️⃣ Generate script paragraphs = generate_script ( topic ) # 2️⃣ Synthesize each paragraph audio_files = [ synthesize_paragraph ( p, work_dir ) for p in paragraphs ] # 3️⃣ Combine into one episode combine_audio ( audio_files, out_file ) # Optional clean‑up for f in work_dir. iterdir (): f. unlink () work_dir. rmdir () if __name__ == " __main__ ": import sys if len ( sys. argv )!= 3: print ( " Usage: python podcast.py <topic> <output.mp3> " ) sys. exit ( 1 ) create_podcast ( sys. argv [ 1 ], pathlib. Path ( sys. argv [ 2 ])) print ( " ✅ Podcast generated! " ) Enter fullscreen mode Exit fullscreen mode Run it like:

python podcast.py "The future of quantum computing" episode1.mp3 Enter fullscreen mode Exit fullscreen mode You’ll end up with an MP3 that sounds like a professional host, ready to upload to Spotify, Apple Podcasts, or any platform you prefer.

All of these extensions still rely on the same core building blocks: an LLM for content, ElevenLabs for realistic TTS, and a tiny amount of glue code.

If you’re looking for a plug‑and‑play solution that delivers studio‑grade audio without a massive learning curve, ElevenLabs is the go‑to service. Grab your free credits here: https://try.elevenlabs.io/kr07zfuqn1bp.

You now have a fully functional AI Podcast Generator that can:

The code is deliberately straightforward so you can adapt it to your own workflow—whether you want to add background music, integrate a transcription service, or schedule daily releases.

Ready to give your listeners a voice they’ll love? Try ElevenLabs today, spin up a few episodes, and watch how quickly you can go from idea to on‑air content. Happy coding!