Metadata-Version: 2.4
Name: blitz-cli
Version: 0.1.0
Summary: Developer CLI for Blitz: pull a workflow's training data + base-model recommendation and scaffold a runnable QLoRA training container.
Requires-Python: >=3.9
Description-Content-Type: text/markdown

# blitz-cli

Developer CLI for [Blitz](https://github.com/sparepartslabs/blitz-sdk-py). Pull a
workflow's captured traces as a fine-tuning dataset + the recommended open base
model, and scaffold a self-contained, runnable QLoRA training container — then
close the loop by grading the trained student against the held-out eval set.

```bash
pip install blitz-cli

export BLITZ_API_KEY=blz_...   # a read-scoped project key (mint one in the dashboard)
blitz scaffold -p proj_abc -w mechanic-assistant -o ./train

cd train
make build && make train && make eval
```

`blitz scaffold` writes `./train` with `data/dataset.jsonl`, `data/evalset.jsonl`,
`config.json` (derived from the base-model recommendation), and a `Dockerfile` +
`train.py` + `eval.py` + `Makefile`. Bring your own NVIDIA GPU.

This package is intentionally dependency-free (stdlib + the Blitz HTTP API). The
heavy ML stack (torch / transformers / trl / peft) is pinned only in the
*generated* project's `requirements.txt`, installed inside the training image.

The complementary tracing SDK (`pip install blitz-sdk`, `import blitz`) lives in
[`../blitz-sdk`](../blitz-sdk).
