This is a snapshot release of the final gradio PoC build.
This version was the first iteration of the application, and is no longer supported.
If you are looking for a replacement for a local-first/open-source solution similar, please see either tldw_chatbook: https://github.com/rmusser01/tldw_chatbook or the Web Front-end for tldw_server:

Install instructions:

tldw_server – Installation Guide (Win/Mac/Linux)

Requirements

• Python 3.9+
• ffmpeg (media processing)
• 8GB+ RAM (3–4GB for server, rest for models)
• 10GB+ disk space

1. Install System Dependencies

Linux

# Debian/Ubuntu
sudo apt install ffmpeg portaudio19-dev gcc build-essential python3-dev
# Fedora
sudo dnf install ffmpeg portaudio-devel gcc gcc-c++ python3-devel

macOS

brew install ffmpeg portaudio

Windows

• Install Python and ffmpeg from official sources.
• For CUDA transcription without full CUDA install:
  Download [Faster-Whisper-XXL](https://github.com/Purfview/whisper-standalone-win/releases/download/Faster-Whisper-XXL/Faster-Whisper-XXL_r192.3.4_windows.7z)
  Extract cudnn_ops_infer64_8.dll and cudnn_cnn_infer64_8.dll into the tldw_server directory.
  Download/install ffmpeg from https://www.gyan.dev/ffmpeg/builds/ - Move the ffmpeg/ffmprobe binaries into the ./bin folder if you don't install them system-wide. This will let tldw use ffmpeg for transcription/file conversion.

2. Download Software & Create Virtual Environment

# Download this package via your choice, and then extract the folder to a location of your choosing, and then navigate to that folder via the terminal.

cd tldw_server

python3 -m venv .venv
# Activate:
# Linux/macOS:
source .venv/bin/activate
# Windows:
.venv\Scripts\activate

3. Install Python Dependencies

pip install -r requirements.txt

4. Configure API Keys

cp config.txt.example config.txt
# Edit config.txt with your keys & settings

Alternatively, use environment variables (OPENAI_API_KEY, ANTHROPIC_API_KEY, etc.).

5. Run the Server

python summarize.py -gui

Optional – Docker Install

CPU

docker build -f Helper_Scripts/Dockerfiles/tldw_cpu_Dockerfile -t tldw-cpu .
docker run -p 8000:8000 tldw-cpu

GPU

docker build -f Helper_Scripts/Dockerfiles/tldw_nvidia_Dockerfile -t tldw-gpu .
docker run --gpus all -p 8000:8000 tldw-gpu