convilyn

Convert files on your own machine, or run AI workflows on the Convilyn platform — one package, one CLI.

Convert a file with no account, no key, no network

pip install "convilyn[pdf]"
convilyn local convert report.pdf --to md

▶ Converting report.pdf → md
✓ Wrote report.md

convilyn.local runs entirely on your machine. Nothing is uploaded, no API key is read, no quota is touched — and it is the same code whether you call it from the shell or from Python:

from convilyn import local

local.convert("report.pdf", to="md")  # one file
local.convert_many(["a.docx", "b.pptx"], out_dir="out/")  # many, one call
local.convert("photo.png", to="webp")  # images too

local.convert("report.pdf", out="build/report.md")  # or name the path…
local.convert("report.pdf", to="md", overwrite=True)  # …and re-run over it

to= names the format and writes beside the input; out= names the path and reads the format from its suffix. Pass exactly one. Nothing replaces an existing file unless you say overwrite=True — guessing what you wanted is how a converter writes over the wrong one.

It tells you what it can do, and never guesses

convilyn local doctor

✓ pdfplumber: installed
✓ PIL: installed
! libreoffice: missing — Install LibreOffice from https://www.libreoffice.org/download/ (provides `soffice`).
! ffmpeg: missing — Install FFmpeg from https://ffmpeg.org/download.html (provides `ffmpeg`).
280 of 667 conversions available. Run `convilyn local formats` for the per-format detail.

Every route that is unavailable says why, and whether installing something fixes it — a missing extra, a Pillow plugin we do not ship, or a build that simply cannot write that format. Offline, that means no silent fallbacks and no partly-converted files: a route either runs or refuses.

The scope of that sentence is deliberate. It is a property of the engine in this package, which is why convilyn local doctor can enumerate it. The hosted conversion API is a different codebase with its own quality labels — it publishes a qualityMode per route at GET /api/v1/{document,image,media}/support, and a best_effort route is telling you in advance that something is dropped or flattened. Read that field before assuming a hosted conversion is lossless.

What runs offline

Legacy Office (.doc, .xls, .ppt), OpenDocument and ebook formats work too when LibreOffice or Calibre is on your PATH; doctor names the one you need.

Video and audio — .mov, .mp4, .webm, .avi, .mkv and .mp3, .wav, .ogg, .m4a, .flac — convert into one another, and a video converts into an audio file, when FFmpeg is on your PATH:

convilyn local convert clip.mov --to mp4
convilyn local convert talk.mp4 --to mp3        # just the audio

Like the two above it is a program rather than a package, so no extra installs it. Transcription is deliberately absent: it calls a paid service, and nothing under convilyn local does.

PDF page operations are a separate namespace, because a PDF goes in and a PDF comes out — rearranged, not converted:

from convilyn.local import pdf

pdf.merge(["a.pdf", "b.pdf"], "combined.pdf")
pdf.select("report.pdf", "summary.pdf", pages="1-3,10")
pdf.burst("scan.pdf", "pages/")  # one file per page — `split` on the CLI

Also on the CLI: convilyn local pdf {merge,select,split,rotate,compress,protect,unlock,info}. protect and unlock prompt for the password when you omit it, so it stays out of your shell history.

The platform half — AI workflows

With an API key, the same package reaches the hosted workflows: conversions that run on our infrastructure, and agentic workflows that ask you for what they are missing.

from convilyn import Convilyn

client = Convilyn()  # reads CONVILYN_API_KEY from env
file = client.files.upload("report.docx")
job = client.convert.create_and_wait(file=file, target_format="pdf")
client.convert.download_to(job, to="report.pdf")

• client.files · client.convert — upload, convert, download
• client.goals — agentic workflows, with human-in-the-loop slot filling
• client.workflows · client.user_workflows — the community library, and the ones you authored
• client.builder — build a workflow by chatting to it
• client.account — your tier, and what a run will cost before you start it

AsyncConvilyn is the same surface, awaitable. Both retry 5xx / 429 / 408 with exponential backoff and jitter, stamp Idempotency-Key on mutating verbs, and honour Retry-After.

Built for scripts and agents. Every command takes --json; the ones that upload or spend also take --dry-run. All of them exit with a pinned code (0 ok · 1 usage · 2 API error · 3 job failed · 130 interrupted), so a loop can branch on the result without parsing English:

convilyn account quota --tool pdf-mcp:extract_text --json | jq .estimated_usd
convilyn goals start "summarise these contracts" --dry-run

Free to install, metered to use

pip install convilyn is free, and everything under convilyn local stays free and unlimited — it runs on your hardware. Platform calls draw on your balance and your plan, and every refusal is a typed APIError subclass rather than an opaque failure: InsufficientCreditsError (your balance cannot fund this run — it carries shortfall_credits), QuotaExceededError (an allowance is spent), PlanRequiredError and FreeTierBlockedError (this needs a different plan). Check first with client.account.

Known limits

• Goal progress is polling-only. Follow a run with client.goals.wait(...) or retrieve(...). WebSocket streaming was removed in 3.0.0: the gateway authenticates no credential this SDK can hold, and the only way to change that would have put your API key in a URL query string — a WebSocket handshake carries no headers. See STABILITY.md.
• Beta. The public surface and its SemVer promise are written down in STABILITY.md; anything not listed there may move.

Authoring workflows? Different package

convilyn is the consumer SDK — you call the API with it. To build a tool server or author a workflow spec, install convilyn-author:

pip install convilyn-author
convilyn-author init my-server

They are deliberately separate so consumers never pay the FastAPI / uvicorn dependency cost.

Documentation

• Quickstart — 5 minutes, covering offline conversion, goals, workflows and quota
• What has been measured — full results, measured 2026-08-28 — conversion and extraction scored on three named corpora (685 documents), including where it falls short
• Full documentation
• Examples — runnable Python and shell scripts
• Changelog
• Contributing — DCO (git commit -s), no CLA; contributions land in the shipped package
• AGENT.md — for AI coding agents working on this SDK

Report a vulnerability privately via SECURITY.md — never in a public issue.

Licence

Apache-2.0. See LICENSE.