Add docker and requirements

.github/workflows/ci.yml

@@ -0,0 +1,41 @@
+name: CI
+
+on:
+  push:
+    branches: [main]
+  pull_request:
+    branches: [main]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.11'
+
+      - name: Install uv
+        run: pip install uv
+
+      - name: Create venv
+        run: uv venv .venv
+
+      - name: Activate venv and install dependencies
+        run: |
+          source .venv/bin/activate
+          uv pip install -e .[test]
+
+      - name: Run tests with coverage
+        run: |
+          source .venv/bin/activate
+          pytest --cov=data-gen --cov-report=xml --cov-fail-under=0
+
+      - name: Upload coverage report
+        uses: actions/upload-artifact@v4
+        with:
+          name: coverage-xml
+          path: coverage.xml 

Dockerfile

@@ -0,0 +1,14 @@
+FROM python:3.11-slim
+
+# Install uv
+RUN pip install uv
+
+# Set workdir and copy project
+WORKDIR /app
+COPY . .
+
+RUN uv pip install --system -r requirements.txt || true
+RUN uv pip install --system .
+
+# Default command (for development)
+CMD ["bash"] 

README.md

@@ -1,2 +1,57 @@
-# data-gen
-The one-stop shop to generate synthetic data for GenAI post-training.
+# Data-Gen
+
+## Project Overview
+Data-Gen is a modular toolkit for generating synthetic data tailored for LLM post-training and evaluation. The project is structured as a monorepo to support multiple components, including a core data generation module, a backend API, and a web client.
+
+## Monorepo Structure
+```
+core/      # Core synthetic data generation logic (Python, uv-managed)
+web/       # (future) Web client
+backend/   # (future) Backend API
+```
+
+## Getting Started
+- See `core/README.md` for details on the core module.
+- Each component is managed independently.
+
+## Local Development (Core Module)
+
+1. Install [uv](https://github.com/astral-sh/uv):
+   ```sh
+   pip install uv
+   ```
+2. Create a virtual environment (recommended):
+   ```sh
+   uv venv .venv
+   source .venv/bin/activate
+   ```
+3. Install dependencies:
+   ```sh
+   uv pip install -e .
+   ```
+4. Run tests:
+   ```sh
+   uv pip install pytest  # if not already installed
+   pytest
+   ```
+
+## Docker Usage
+
+1. Build the Docker image:
+   ```sh
+   docker build -t data-gen .
+   ```
+2. Run the container:
+   ```sh
+   docker run -it data-gen
+   ```
+
+> **Note:** If you see an error about "No virtual environment found" when building Docker, ensure the Dockerfile uses `uv pip install --system ...` for global installs (already set up in this repo).
+
+## Component Descriptions
+- **core/**: Implements the main logic for generating synthetic data for LLM post-training. (First component to be implemented)
+- **web/**: (Planned) Web-based user interface for data generation and management.
+- **backend/**: (Planned) API backend for orchestration and integration.
+
+## Contributing
+- Contributions are welcome! Please see the contributing guidelines in each component folder.

data-gen/core/README.md

@@ -0,0 +1,13 @@
+# Core Module: Synthetic Data Generation
+
+This module implements the core logic for generating synthetic data for LLM post-training and evaluation.
+
+## Structure
+- `core/` — Python package with core logic
+- `tests/` — Unit tests for the core module
+
+## Setup
+- Managed with [uv](https://github.com/astral-sh/uv) and PEP 621 (`pyproject.toml`)
+
+## Usage
+- (Coming soon) Example usage and API documentation. 

data-gen/core/__init__.py

@@ -0,0 +1 @@
+

data-gen/core/tests/__init__.py

@@ -0,0 +1 @@
+

data-gen/core/tests/test_smoke.py

@@ -0,0 +1,3 @@
+def test_smoke() -> None:
+    """Dummy test to ensure CI and coverage run successfully."""
+    assert True 

pyproject.toml

@@ -0,0 +1,19 @@
+[project]
+name = "core"
+version = "0.1.0"
+description = "Core synthetic data generation logic for LLM post-training."
+authors = [
+  { name = "Your Name", email = "your@email.com" }
+]
+requires-python = ">=3.9"
+readme = "README.md"
+
+[project.optional-dependencies]
+test = [
+  "pytest",
+  "pytest-cov"
+]
+
+[build-system]
+requires = ["setuptools", "wheel"]
+build-backend = "setuptools.build_meta"