Transparent remote GPU execution. Run `python train.py` on cloud GPUs.
Project description
specter-host
Remote GPUs, locally. Run python train.py on cloud GPUs as if they were local.
Install
# Recommended (isolated install)
pipx install specter-host
# Or with pip
pip install specter-host
Quick Start
# Create and activate a virtual environment
python -m venv .venv && source .venv/bin/activate
# Authenticate via browser
specter login
# Provision a GPU — patches your active venv
specter install h100
# Run Python as usual — it transparently executes on the remote GPU
python train.py
# pip install works locally AND syncs to the remote automatically
pip install transformers
# When done, tear down the pod and restore your venv
specter uninstall
How It Works
specter install h100provisions a cloud GPU pod via the Specter broker- Your active venv is patched —
bin/pythonbecomes a transparent proxy- The original binary is backed up as
python.specter-original - pip, pytest, and other entry points continue to run locally
- The original binary is backed up as
- When you run
python train.py, Specter:- Rsyncs your workspace to the remote machine
- Executes the command via SSH
- Streams stdout/stderr back in real-time
- Returns the remote exit code
- Dependencies stay in sync automatically:
- At install time:
pip freeze→ remotepip install - After every
pip install: auto-synced to the remote pod
- At install time:
specter uninstallrestores your venv to its original state
License
MIT
Project details
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