📚 Data-Augmentation Toolkit

A Streamlit-based UI that lets you:

• Upload single- or multi-turn SFT / Alignment datasets (.jsonl or .csv)
• Validate the file before launching the heavy pipeline
• Run the data-augmentation pipeline with live logs & progress bar
• Download the generated JSONL in one click
• Check your LLM endpoint instantly via a Health-Check button

---

✨ Features

Area	What it does
LLM Connection	Enter model_name, api_key, base_url & press Health-Check to verify connectivity.
Generation Mode	Choose between single/multi-turn SFT or Alignment pipelines.
Threading	Adjustable worker slider (1-16) controls concurrent requests.
File Validation	Early checks for broken JSONL, malformed CSV, or wrong extensions with descriptive errors.
Live Feedback	Real-time tqdm progress + log stream in the main pane.
Output	Final JSONL is offered for download; CSV deliberately omitted to keep training format consistent.

---

🛠 Quick Start

# 1. Clone & enter the repo
git clone https://github.com/your-org/data-augmentation-toolkit.git
cd data-augmentation-toolkit

# 2. Create env & install deps
python -m venv .venv
source .venv/bin/activate      # Windows: .venv\Scripts\activate
pip install -r requirements.txt

# 3. Run the Streamlit app
streamlit run app.py