Deploy the Python Llama wrote you.
Built a nightly export with Llama? Snapdock deploys and runs it in the cloud 24/7, watches every run, and explains failures in plain English. No servers, no Docker, no YAML.
No card to start. Works with any LLM.
How do I deploy a Python script Llama wrote?
You don't need a server, Docker, or DevOps. Upload the script to Snapdock; it auto-detects how the code runs and its dependencies, fixes the Windows-to-Linux gotchas, deploys it to a cloud machine, and runs it on a schedule 24/7 — then explains every run in plain English and alerts you the moment one fails.
What you need before you deploy.
The code Llama wrote
A .py file, a .zip, or a whole project folder. No cleanup required — bring it as-is.
Any API keys it uses
The keys for whatever it talks to (Stripe, a database, Google Sheets). You'll paste them into the encrypted Secrets vault, not the code.
A Snapdock account
No card to start. If you can attach a file to an email, you have everything you need.
Deploy it in four steps — about ninety seconds.
Drop in the code.
Upload the .py file, a .zip, or the whole project Llama gave you. Snapdock finds the entrypoint and reads your dependencies — no requirements.txt wrangling, no Dockerfile.
Snapdock checks and deploys it.
A plain-English pre-flight flags hardcoded keys or missing packages and auto-fixes the Windows-to-Linux gotchas, then deploys to the cloud, pre-warmed.
Pick a schedule.
Every morning, hourly, weekdays at 9 — a preset or your own cron. It runs on time on a cloud machine, independent of your laptop.
Read every run in plain English.
After each run you get a one-sentence summary of what it did; if it fails, a plain-English cause and a likely fix — by email, Slack, or Teams.
The gotchas in Llama-generated code — and how Snapdock handles them.
Hardcoded API keys
LLMs often paste your key straight into the script. Snapdock's pre-flight spots it and offers to move it to the encrypted Secrets vault before deploy.
Missing dependencies
The code imports a package that was never installed. Snapdock auto-detects imports and flags anything missing in plain English — no requirements.txt archaeology.
Windows-only paths & line endings
Code written on your machine assumes C:\ paths or CRLF line endings. Snapdock fixes the Windows-to-Linux gotchas automatically so it just runs in the cloud.
“It only runs while my laptop is on”
Llama writes the logic, not the scheduler. Snapdock runs it on a cloud machine on a schedule, so it keeps going 24/7 whether or not your computer is.
The DevOps you'd otherwise do by hand.
Detects how it runs
Entrypoint, Python version, and dependencies — auto-detected. No Dockerfile or requirements wrangling.
Fixes Windows → Linux
Paths and line endings that break in the cloud, fixed automatically.
Runs it on a schedule
Off a cloud machine, 24/7, independent of your laptop. Presets or your own cron.
Watches & explains
A plain-English summary of every run, and a likely fix the moment one fails.
Deploying Llama code — common questions.
Can Snapdock run Python that Llama generated?+
Yes. Snapdock is builder-agnostic — bring Python generated by Llama or any other LLM. Drop it in as-is; Snapdock detects how it runs, deploys it, schedules it, and explains every run. No rewrites.
Do I need Docker or a requirements.txt to deploy it?+
No. Snapdock auto-detects your dependencies and how the script runs — there is no Dockerfile, YAML, or build config to write. If a package is missing, the pre-flight tells you in plain English.
Where do the API keys Llama hardcoded go?+
Move them into Snapdock's encrypted Secrets vault and reference them the normal way (os.getenv). Keys are injected at runtime and never written to logs or bundled in your code.
What happens when the automation fails?+
Snapdock turns the error into a plain-English sentence, points at what broke, and hands you a likely fix — then notifies you by email, Slack, or Teams with a one-click re-run.
Related guides.
Deploy the Python Llama wrote you.
No card to start — deployed and running in minutes, no servers or Docker.