leetvault
Mirror your LeetCode account (accepted submissions + source code + metadata) into a normalized SQLite database and a GitHub repository with an auto-generated README dashboard.
Sync is account-based, driven by your authenticated LeetCode session — not a browser extension. Your LeetCode account is the single source of truth. Free and open source; the only external services involved are LeetCode and GitHub.
Install
pip install leetvault
Requires Python 3.11+. See docs/DEVELOPER.md for an editable/dev install.
Quickstart
leetvault login # paste LEETCODE_SESSION + csrftoken
leetvault config repo_url https://github.com/you/repo.git # optional: enable GitHub push
leetvault import # one-time full history
leetvault sync # incremental, run anytime
leetvault watch # or: poll automatically
Commands
leetvault login [--leetcode|--github] [--force]— store yourLEETCODE_SESSION+csrftoken(and optionally a GitHub PAT) in the OS keyring. Only prompts for what's actually missing or expired — see below.leetvault import [--keep-all]— full history import of every accepted submission (resumable, one-time per site).leetvault sync [--keep-all]— incremental sync of new accepted submissions since the last run.leetvault watch— poll LeetCode and sync automatically (--interval, default 90s).leetvault status— show session validity/expiry and sync state.leetvault logout— remove stored credentials.leetvault config— get/set persistent configuration (repo URL, DB path, dedup window, ...).leetvault ai— set up optional AI-generated solution analysis (off by default).leetvault analyze [problem]— regenerate an existinganalysis.mdwith a different backend — see below.leetvault ask <problem> "<question>"— ask a question about one of your solutions and keep the answer — see below.leetvault bot [--install]— install a GitHub Actions workflow so you can ask from GitHub itself — see below.leetvault commands [--full]— list every command and what it does, generated from the CLI itself so it cannot fall behind.
Refreshing credentials
Your LeetCode session cookies expire roughly every 14 days; a GitHub PAT lasts until you revoke
it or it hits its own expiry. They fail independently, so login checks each one live and
only prompts for what actually needs replacing:
leetvault login # checks both, prompts only for what's expired/missing
leetvault login --leetcode # only refresh LeetCode cookies, never touch the stored PAT
leetvault login --github # only refresh the GitHub PAT, never re-ask for cookies
leetvault login --force # re-prompt for everything, even if still valid
If both are still good, login prompts for nothing and tells you so. leetvault status shows
the same live check without changing anything.
AI solution analysis (optional, off by default)
leetvault ai can generate an analysis.md next to each solution — explaining the approach,
walking through your actual code, and covering complexity and edge cases. It is disabled
until you turn it on, and your notes.md is never touched.
It works with whichever backend you already have; run leetvault ai and it detects them:
| Backend | Cost | Needs | Notes |
|---|---|---|---|
| Gemini | Free tier | Free API key | aistudio.google.com/apikey. No local hardware, no subscription. |
| Groq | Free tier | Free API key | console.groq.com/keys. Very fast; no local hardware. Meters 8000 tokens/min. |
| NVIDIA NIM | Free tier | Free API key | build.nvidia.com. Very large open models with reasoning; quota separate from Gemini and Groq. |
| Ollama (local) | Free, unlimited | ~5 GB disk + RAM | ollama pull qwen2.5-coder:7b. Fully offline, no account. Slow without a GPU. |
| Claude Code CLI | Free | An existing Claude subscription | npm i -g @anthropic-ai/claude-code, then claude once to sign in. |
| Anthropic API | Paid, per token | API key | pip install anthropic. Highest quality. |
Gemini, Groq and NVIDIA NIM are the fallback when you have neither spare RAM nor a Claude subscription — a free API key, and inference runs in the cloud. Their quotas are separate, so a backfill stopped by one provider's daily limit can be finished on another.
For Hard problems, prefer a reasoning-capable model. Tracing code and justifying complexity is multi-step arithmetic, and a mid-size instruct model will produce a confident, wrong dry run rather than admitting it cannot follow the code.
leetvault ai # detect backends and choose one
leetvault ai --set-key gemini # store a free key (or groq / nvidia / anthropic)
leetvault ai --show # print current settings
leetvault ai --disable # turn it back off
leetvault config ai_model openai/gpt-oss-120b # override the model
Generation is best-effort: a failing or slow model never breaks a sync. sync only fills
gaps — a problem that already has an analysis.md is skipped, which is what makes a backfill
resumable across a free tier's daily limit. To replace one you are not happy with, use
leetvault analyze.
Each file's footer records the model that wrote it, so a repo built across several providers stays traceable.
How an analysis is assembled
leetvault asks for the whole analysis in one call and keeps that when it comes back complete. If the reply is truncated or missing sections, it re-requests them in halves, then pairs, then one section at a time, pausing between calls so a per-minute token budget is not spent in one shot. A partial analysis is never written — a file that exists is a problem that never gets looked at again.
Redoing an analysis
leetvault analyze --list # which model wrote each analysis
leetvault analyze two-sum -p nvidia # redo one problem
leetvault analyze --from groq -p nvidia # redo everything Groq wrote
leetvault analyze --all -p gemini # redo the lot, one model throughout
Name a problem by slug, number, or part of its title. You are asked before anything is
overwritten (-y skips that), and if the new provider fails, the existing analysis is kept
rather than lost.
--keep-all
By default, import/sync keep only the newest accepted submission per problem within a
rolling 24-hour window (dedup_window_seconds in leetvault config, default 86400) — solving
the same problem twice in one sitting doesn't clutter history with near-duplicate attempts.
--keep-all disables that and stores every accepted submission individually:
leetvault sync --keep-all # one-off: keep everything from this run onward
leetvault import --keep-all # same, for the initial full-history import
To make this the permanent default instead of retyping the flag every time:
leetvault config dedup_window_seconds 0
--keep-all only changes how future submissions are processed — it can't retroactively
recover a submission an earlier (non---keep-all) run already deduped, since sync only walks
forward from the last submission it saw. See
docs/TROUBLESHOOTING.md
if you hit that.
What gets stored
A normalized SQLite database (problems, submissions, source code, topics, sync state) plus a disk layout per problem:
Problems/<slug>/
latest.<ext> the most recent accepted submission
history/submission_<id>.<ext> every kept accepted submission
question.md the problem statement, examples, constraints + collapsed hints
analysis.md optional AI explanation of your solution (off by default)
run.py runs your solution against the problem's example inputs
metadata.json difficulty, topics, runtime/memory percentiles, ...
notes.md yours - never overwritten once created
leetvault_runner.py shared runner that each run.py delegates to
.devcontainer/ so the repo opens ready-to-run in GitHub Codespaces
README.md auto-generated dashboard: progress, streaks, full solutions table,
and clickable topic tags that jump to a per-topic problem list
Running solutions in the browser
Open your solutions repo on GitHub and choose Code ▸ Codespaces ▸ Create codespace - you get full VS Code with a terminal, and the devcontainer means Python is already set up:
python Problems/two-sum/run.py
It prints your solution's output for each of LeetCode's example inputs. It intentionally does
not report pass/fail: the API exposes example inputs but not their expected outputs, so any
verdict would be guesswork - check the Output: lines in that problem's question.md.
Problems needing non-JSON inputs (linked lists, trees) or with no single entry point (design
problems) say so rather than running incorrectly.
question.md is fetched once per problem and never re-fetched, so it costs nothing on
subsequent syncs. Disable it entirely with leetvault config write_question_md false. Problem
statements remain the property of LeetCode; each file notes this.
Deduplicated by default within a 24h window — see --keep-all above to change
that.
Asking questions
analysis.md answers the questions leetvault thought to ask. For everything else:
leetvault ask two-sum "why a hash map and not sorting first?"
leetvault ask 3348 "is this actually greedy, or dynamic programming?" --push
The question and answer append to that problem's qa.md, so the thread accumulates and
earlier exchanges are carried into later ones as context. A problem can be named by slug,
number, or part of its title. --no-save prints the answer without keeping it.
Context comes from the repository — question.md, your solution, and any existing
analysis.md — not from the database. That is what lets the same command run in CI.
Asking from GitHub
leetvault bot --install
If the GitHub CLI is installed and signed in, that one command does everything: writes the workflow and issue template, uploads every stored API key as an encrypted repository secret, sets the provider (and model, if you have pinned one) as repository variables, grants the workflow permission to commit, and pushes. Then open an issue titled
[two-sum]: why a hash map?
and the bot replies as a comment and commits the exchange to Problems/two-sum/qa.md.
Replying in the thread asks a follow-up: the comment is the question, and the existing
qa.md is fed back in as context, so "why?" or "show me that trace" makes sense on its own.
It works from a phone, since it is just GitHub.
gh is used rather than the REST API for two reasons: uploading a secret means encrypting it
with the repository's public key, which would otherwise mean a new dependency, and gh's
token carries the workflow scope that a fine-grained PAT usually lacks — without it GitHub
refuses any push that touches .github/workflows/. If gh is missing or a step is not
permitted, the files are still written and the manual steps printed; --manual skips the
GitHub calls entirely.
To change which model the bot uses without reinstalling:
gh variable set LEETVAULT_AI_PROVIDER --repo <owner>/<repo> --body groq
gh variable set LEETVAULT_AI_MODEL --repo <owner>/<repo> --body openai/gpt-oss-120b
LEETVAULT_AI_MODEL is optional — leave it unset and each provider uses its own default.
Providers retire models without much notice, and a retired model is a 404 rather than a
warning - if a backend suddenly stops answering, check its model list before anything else.
Two things worth knowing:
- Your API key lives in GitHub's encrypted secrets, never in the repo.
leetvault botprints the exact settings page and secret name for the backend you have configured. - Only issues you open are answered. On a public repo anyone can file an issue, and without that check every stranger would be spending your quota. The workflow compares the issue author against the repository owner and does nothing otherwise.
GitHub renders Markdown but does not run it, so a chat box inside Problems/<slug>/ is not
possible. Issues are the closest real equivalent — and they give you threading, search,
notifications and history for free.
Discovering commands
leetvault commands # every command and what it does
leetvault commands --full # plus every argument and option
Generated from the CLI itself, so it cannot fall behind the commands that actually exist.
Command reference
Every command with every argument and option. Generated from the CLI itself, and a test fails if this section falls behind it.
leetvault ai
Set up optional AI-generated solution analysis (off by default).
| Flag / argument | Kind | Meaning |
|---|---|---|
--disable |
option | Turn AI analysis off. |
--set-key |
option | Store an API key for gemini, groq, nvidia, or anthropic. |
--show |
option | Print the current AI settings. |
leetvault analyze [problem]
Regenerate an existing analysis.md with a different AI backend.
| Flag / argument | Kind | Meaning |
|---|---|---|
problem |
argument | Problem slug, number, or part of its title. Omit with --all or --from. |
--provider, -p |
option | Backend to use instead of the configured one. |
--model |
option | Model override for this run. |
--all |
option | Re-analyse every problem. |
--from |
option | Re-analyse only what a given provider generated, e.g. groq. |
--list |
option | Show which model wrote each analysis and exit. |
--yes, -y |
option | Skip the overwrite confirmation. |
leetvault ask <problem> <question>
Ask a question about one of your solutions.
| Flag / argument | Kind | Meaning |
|---|---|---|
problem |
argument | Problem slug, number, or part of its title. |
question |
argument | What you want to know about it. |
--provider, -p |
option | Backend to use instead of the configured one. |
--model |
option | Model override for this run. |
--repo |
option | Repository to read from and write to (default: configured). |
--save |
option | Append to the problem's qa.md. |
--push |
option | Commit and push the qa.md. |
leetvault bot
Set up a GitHub bot that answers questions asked as issues.
| Flag / argument | Kind | Meaning |
|---|---|---|
--install |
option | Write the GitHub Actions workflow into your repo. |
--repo |
option | Repository to install into. |
--show |
option | Print the setup steps and exit. |
--manual |
option | Only write the files; do not touch GitHub settings. |
leetvault commands
List every leetvault command and what it does.
| Flag / argument | Kind | Meaning |
|---|---|---|
--full |
option | Include every argument and option for each command. |
leetvault config [key] [value]
Get or set persistent config (repo URL, DB path, dedup window, etc.).
| Flag / argument | Kind | Meaning |
|---|---|---|
key |
argument | Config key to get/set, e.g. repo.url. |
value |
argument | Value to set; omit to read. |
leetvault import
Full history import of all accepted submissions (resumable).
| Flag / argument | Kind | Meaning |
|---|---|---|
--site |
option | LeetCode site: com or cn. |
--keep-all |
option | Disable same-day dedup; keep every accepted submission. |
leetvault login
Store LEETCODE_SESSION + csrftoken (and optionally a GitHub PAT) in the OS keyring.
| Flag / argument | Kind | Meaning |
|---|---|---|
--leetcode |
option | Only refresh the LeetCode session; leave the GitHub PAT alone. |
--github |
option | Only refresh the GitHub PAT; leave the LeetCode session alone. |
--force |
option | Re-prompt even for credentials that are still valid. |
leetvault logout
Remove stored credentials from the OS keyring.
leetvault status
Show session validity/expiry, sync state, and repo config.
leetvault sync
Incremental sync: pick up new accepted submissions since the last sync.
| Flag / argument | Kind | Meaning |
|---|---|---|
--site |
option | LeetCode site: com or cn. |
--keep-all |
option | Disable same-day dedup; keep every accepted submission. |
leetvault watch
Poll for new accepted submissions and sync+push automatically.
| Flag / argument | Kind | Meaning |
|---|---|---|
--interval |
option | Polling interval in seconds (60-120). |
--site |
option | LeetCode site: com or cn. |
Global flags, usable with any command: --install-completion, --show-completion,
--help.
leetvault commands --full prints this same listing in the terminal.
Honest limits
watchis polling (default 90s, configurable), not a real-time push — LeetCode has no public webhook/streaming API.- LeetCode may Cloudflare-challenge automated HTTP clients; leetvault fails gracefully rather than faking success.
- Storing session cookies for automated access may be against LeetCode's Terms of Service. Use at your own risk, against your own account only.
- LeetCode has no official API — every endpoint leetvault uses is reverse-engineered and could change without notice.
- AI analysis is only as good as the model behind it. leetvault checks that a response is complete and rejects truncated or stub replies, but it cannot verify that a dry run or a complexity claim is correct — read generated analysis as a strong draft, not an authority, and prefer a reasoning-capable model for Hard problems.
Docs
- docs/ARCHITECTURE.md — data flow, module responsibilities, and every place live API behavior diverged from initial assumptions.
- docs/DEVELOPER.md — dev setup, project layout, running checks.
- docs/FAQ.md
- docs/TROUBLESHOOTING.md
- CONTRIBUTING.md
- CHANGELOG.md
License
MIT — see LICENSE.
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