# Phase 2.1A uv environment

This directory is the deployable Python environment definition for
`Robometer-Low-LoRA` and `Robometer-Low`. Do not copy a local `.venv` between
machines.

## Host requirements

- Linux x86_64
- NVIDIA GPU with BF16 support
- NVIDIA driver compatible with CUDA 12.8
- `uv` 0.11.3 or a compatible newer release
- A CUDA development toolkit is needed only if no compatible prebuilt
  FlashAttention wheel can be selected and a source build is required.

## Rebuild

From the experiment root:

```bash
uv python install 3.10.12
uv sync --project environment/phase21a_robometer --frozen
uv run --project environment/phase21a_robometer python environment/phase21a_robometer/doctor.py
```

The second `uv sync --frozen --dry-run` must report no changes. Run the formal
training smoke test before starting a seed.

The formal trainer sets `PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True` before
initializing CUDA. Keep this setting for the validated micro-batch of 32 pairs;
removing it can cause allocator-fragmentation OOM near the RTX 5090 capacity
limit even when several GiB are reserved but unused.

The base model, public-proxy dataset, and run output are external artifacts and
must not be placed inside this environment directory. Pin their Hugging Face
revisions in the run manifest.