Week4 exercise bootcamp feb2026 ibrahim sheriff

[Sheriff10]

Week 4: Code gen and unit-test AI

What it is

A Gradio app (launched from the notebook) that uses a frontier LLM via OpenRouter to:

• Convert Python → TypeScript — Generate idiomatic, typed TypeScript from Python with equivalent behavior.
• Run code — Run the Python or TypeScript in the app and compare outputs.
• Generate unit tests — Choose Python (pytest) or TypeScript (Jest) and generate tests for the code in the corresponding box.

Notebook: week4/python_to_typescript.ipynb.

Setup

1. API key: Put your OpenRouter API key in a .env file in the repo root:

   OPENROUTER_API_KEY=sk-or-v1-...
   

   Get a key at openrouter.ai.

2. Dependencies: From the repo root run:

   uv sync

   Or install: python-dotenv, openai, gradio.

How to run

1. Open and run week4/python_to_typescript.ipynb.
2. Run all cells to load the client and start the Gradio app.
3. Use the local URL (e.g. http://127.0.0.1:7860) in your browser.
4. Convert: Paste Python, pick a model, click Convert to get TypeScript.
5. Run: Use Run Python and Run TypeScript to see outputs.
6. Unit tests: Choose Python or TypeScript in the dropdown and click Generate unit tests to get pytest or Jest tests.

Optional: Run TypeScript in the app

The Run TypeScript button uses npx tsx (or npx ts-node). You need:

• Node.js installed.
• tsx or ts-node, e.g.:
  • npx tsx (recommended, no global install),
  • or npm i -g ts-node.

If neither is available, the app will show an install message.

[hopeogbons]

Suggested change

	"outputs": [
	{
	"name": "stdout",
	"output_type": "stream",
	"text": [
	"OpenRouter API Key exists and begins sk-or-v1\n"
	]
	}
	],
	"outputs": [],

[hopeogbons]

Suggested change

	"outputs": [
	{
	"name": "stdout",
	"output_type": "stream",
	"text": [
	"* Running on local URL: http://127.0.0.1:7864\n",
	"* To create a public link, set `share=True` in `launch()`.\n"
	]
	},
	{
	"data": {
	"text/html": [
	"<div><iframe src=\"http://127.0.0.1:7864/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
	],
	"text/plain": [
	"<IPython.core.display.HTML object>"
	]
	},
	"metadata": {},
	"output_type": "display_data"
	},
	{
	"data": {
	"text/plain": []
	},
	"execution_count": 42,
	"metadata": {},
	"output_type": "execute_result"
	}
	],
	"outputs": [],

[hopeogbons]

Hey @Sheriff10 kindly resolve the suggestions above.

#LGTM 👍