pyVideoTrans

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Parakeet-API: High-Performance Local Speech Transcription Service ​

The parakeet-api project is a local speech transcription service based on the NVIDIA Parakeet-tdt-0.6b model. It provides an interface compatible with the OpenAI API and a clean Web UI, allowing you to easily and quickly convert any audio or video file into high-precision SRT subtitles. It is also compatible with pyVideoTrans v3.72+.

Project Open Source Address: https://github.com/jianchang512/parakeet-api

Windows All-in-One Package Download: ​

Download Link: https://pan.baidu.com/s/1cCUyLw93hrn40eFP_qV6Dw?pwd=1234

Usage: After extracting, double-click 启动.bat (Start.bat). Wait until the interface shown below appears and the browser opens automatically, indicating a successful launch. Successful Launch Interface

Usage with pyVideoTrans ​

Parakeet-API can be seamlessly integrated with the video translation tool pyVideoTrans (version v3.72 and above).

  1. Ensure your parakeet-api service is running locally.
  2. Open the pyVideoTrans software.
  3. In the menu bar, select Speech Recognition(R) -> Nvidia parakeet-tdt.
  4. In the pop-up configuration window, set the "http address" to: http://127.0.0.1:5092/v1
  5. Click "Save", and you can start using it.

Source Code Deployment ​

🛠️ Installation and Configuration Guide ​

This project supports Windows, macOS, and Linux. Please follow the steps below for installation and configuration.

Step 0: Set up Python 3.10 Environment ​

If you don't have Python 3 installed locally, please install it following this tutorial: https://pvt9.com/_posts/pythoninstall

Step 1: Prepare FFmpeg ​

This project uses ffmpeg for audio/video format preprocessing.

  • Windows (Recommended):

    1. Download from FFmpeg GitHub Repository. After extracting, you will get ffmpeg.exe.
    2. Place the downloaded ffmpeg.exe file directly in the root directory of this project (at the same level as the app.py file). The program will automatically detect and use it; no environment variable configuration is needed.

  • macOS (using Homebrew):

    bash
    brew install ffmpeg

  • Linux (Debian/Ubuntu):

    bash
    sudo apt update && sudo apt install ffmpeg

Step 2: Create Python Virtual Environment and Install Dependencies ​

  1. Download or clone this project's code to your local computer (recommended to place it in a folder with an English or numeric name on a non-system drive).

  2. Open a terminal or command-line tool and navigate to the project root directory (on Windows, simply type cmd in the folder address bar and press Enter).

  3. Create a virtual environment: python -m venv venv

  4. Activate the virtual environment:

    • Windows (CMD/PowerShell): .\venv\Scripts\activate
    • macOS / Linux (Bash/Zsh): source venv/bin/activate

  5. Install dependencies:

    • If you do NOT have an NVIDIA GPU (CPU only):

      bash
      pip install -r requirements.txt

    • If you have an NVIDIA GPU (using GPU acceleration): a. Ensure you have the latest NVIDIA Driver and the corresponding CUDA Toolkit installed. b. Uninstall any existing old PyTorch versions: pip uninstall -y torch c. Install PyTorch matching your CUDA version (using CUDA 12.6 as an example):

      bash
      pip install torch --index-url https://download.pytorch.org/whl/cu126

Step 3: Start the Service ​

In the terminal with the virtual environment activated, run the following command:

bash
python app.py

You will see prompts indicating the service is starting. The first run will download the model (approx. 1.2GB), please be patient.

If a bunch of warnings appear, you can ignore them.

Successful Launch Interface

🚀 How to Use ​

Method 1: Using the Web Interface ​

  1. Open in your browser: http://127.0.0.1:5092
  2. Drag and drop or click to upload your audio/video file.
  3. Click "Start Transcription", wait for processing to complete, and you can view and download the SRT subtitle below.

Method 2: API Call (Python Example) ​

You can easily call this service using the openai library.

python
from openai import OpenAI

client = OpenAI(
    base_url="http://127.0.0.1:5092/v1",
    api_key="any-key",
)

with open("your_audio.mp3", "rb") as audio_file:
    srt_result = client.audio.transcriptions.create(
        model="parakeet",
        file=audio_file,
        response_format="srt"
    )
print(srt_result)