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Build a seamless text-to-speech pipeline in Python by combining OpenAI’s Chat API with Google’s gTTS library. Generate natural language responses from an LLM and have them spoken aloud automatically.

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Prerequisites

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1. Install Dependencies

PackagePurposeInstall Command
gTTSGoogle Text-to-Speech Python clientpip install gTTS
OpenAI Python clientOfficial OpenAI API SDKpip install openai
Audio playback utilityPlay MP3 files (macOS: afplay; Linux: mpg123 or mpg321)brew install mpg123 or sudo apt install mpg123
This example is tested on Python 3.7+. If you use a different version, adjust commands as needed.

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2. Set Your OpenAI API Key

export OPENAI_API_KEY="your_openai_api_key"
Never commit your API key to public repositories. Use a secure vault or environment manager in production.

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Imports and Client Initialization

Begin by importing standard libraries, gTTS, and initializing the OpenAI client: 
import os
from gtts import gTTS
from openai import OpenAI

client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))

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1. Define the Prompt

Decide what you want the model to say. For example: 
prompt = "Tell me a story about a brave knight who loves basketball."

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2. Text-to-Speech Function

Convert text to speech and play the resulting MP3: 
def text_to_speech(text: str, lang: str = "en", slow: bool = False) -> None:
    """
    Generate speech from text using gTTS, save as MP3, and play it.
    """
    tts = gTTS(text=text, lang=lang, slow=slow)
    filename = "tts_output.mp3"
    tts.save(filename)
    # macOS uses 'afplay'; Linux users can install 'mpg123' or 'mpg321'
    os.system(f"afplay {filename}")
Adjust the playback command (afplay, mpg123, or mpg321) based on your operating system.

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3. Generate Text from OpenAI

Send the prompt to the Chat API and retrieve the response: 
def generate_text(
    prompt: str,
    model: str = "gpt-3.5-turbo",
    temperature: float = 0.8,
    max_tokens: int = 150
) -> str:
    """
    Generate a chat completion for the given prompt.
    """
    response = client.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": prompt}],
        temperature=temperature,
        max_tokens=max_tokens
    )
    return response.choices[0].message.content

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4. Combine Generation and Speech

Create a helper that prints the generated text, then speaks it: 
def gen_and_speak(prompt: str) -> None:
    """
    Generate text from the prompt, display it, and play the speech.
    """
    text = generate_text(prompt)
    print("Generated Text:\n")
    print(text, "\n")
    text_to_speech(text)

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5. Entry Point

Run the full pipeline with your defined prompt: 
if __name__ == "__main__":
    gen_and_speak(prompt)

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Example Console Output

$ python3 text_to_speech_pipeline.py
Generated Text:

Once upon a time in the kingdom of Eldoria, there lived a brave knight named Sir Cedric...
# (Audio will start playing automatically)

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Next Steps & Extensions

  • Support multiple languages by changing lang in text_to_speech().
  • Experiment with different voices and speech parameters.
  • Integrate other audio libraries like pydub or playsound for advanced playback.

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