Skip to main content

llm-markdown-sanitizer (Python)

Fix broken markdown that LLMs generate. Zero dependencies, one function.

A Java binding with the same behavior is also available — see the repository root for both.

Install

Requires Python 3.9+. No other dependencies get pulled in.

pip install llm-markdown-sanitizer

Using a virtual environment (recommended for any real project):

python3 -m venv .venv
source .venv/bin/activate   # Windows: .venv\Scripts\activate
pip install llm-markdown-sanitizer

Pin a specific version if you want reproducible builds:

pip install "llm-markdown-sanitizer==0.1.0"

Verify it installed correctly:

python -c "from llm_markdown_sanitizer import clean_markdown; print(clean_markdown('**hi**there'))"
# **hi** there

Use

The whole API is one function:

from llm_markdown_sanitizer import clean_markdown

clean_markdown("**Note**this needs a space")
# "**Note** this needs a space"

clean_markdown("| A | B | | --- | --- | | 1 | 2 |")
# "| A | B |\n| --- | --- |\n| 1 | 2 |"

Default settings handle the common failure modes without additional configuration.

In a FastAPI endpoint

A typical place to call this is right before a stored or freshly-generated LLM response goes out to a client:

from fastapi import FastAPI
from llm_markdown_sanitizer import clean_markdown

app = FastAPI()

@app.get("/lectures/{lecture_id}/summary")
def get_summary(lecture_id: int):
    raw = db.get_ai_summary(lecture_id)  # however you fetch/generate it
    return {"summary": clean_markdown(raw)}

Streaming/multi-part LLM responses

Some SDKs return responses as a list of {"text": ...}-shaped chunks instead of one string. clean_markdown accepts that directly:

chunks = [{"text": "# Hello"}, {"text": "\n\nWorld"}]
clean_markdown(chunks)
# "# Hello\n\nWorld"

Why this exists

Ask an LLM to answer in markdown and eventually you'll get: the whole answer wrapped in a stray ```markdown fence, **bold**text glued directly onto the next word, list indentation that's inconsistent within the same response, and tables that are either collapsed onto one line or missing a separator row. Rendering that output as-is breaks the UI.

clean_markdown() fixes all of the above in a single left-to-right pass over the text — no whole-string regex backtracking, so it stays fast on long documents.

What it fixes

Problem Before After
Wrapping code fence ```markdown\n# Title\n``` # Title
<br> outside tables Line one<br>Line two Line one\nLine two (left untouched inside table cells, where it's usually intentional)
Bold glued to text **Note**this breaks **Note** this breaks
Inconsistent list indent mixed 2/3/tab indents normalized to 4 spaces per nesting level
Collapsed table | A | B | | --- | --- | | 1 | 2 | proper one-row-per-line table
Broken table (no separator / mismatched columns) renders as a wall of | dropped instead of rendering broken

Protecting your own syntax

If your prompts produce custom tokens — a [[wiki]]-style syntax, template placeholders, etc. — that the cleanup passes above might mangle, they can be excluded explicitly:

import re

clean_markdown(text, protect_patterns=[re.compile(r"\[\[.*?\]\]")])

Origin

Extracted from the markdown-cleanup layer of a production RAG service, after months of hardening against real LLM output. The domain-specific parts — a custom wiki syntax, a Korean-language note pattern — were removed in favor of the general protect_patterns mechanism above, so callers can supply their own domain syntax instead.

Contributing

Bug fixes and small improvements are welcome. No CLA/DCO required — see CONTRIBUTING.md for guidelines and how to run the test suite locally. AI coding agents should pick up AGENTS.md / CLAUDE.md automatically.

License

MIT

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

llm_markdown_sanitizer-0.1.0.tar.gz (10.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

llm_markdown_sanitizer-0.1.0-py3-none-any.whl (11.0 kB view details)

Uploaded Python 3

File details

Details for the file llm_markdown_sanitizer-0.1.0.tar.gz.

File metadata

  • Download URL: llm_markdown_sanitizer-0.1.0.tar.gz
  • Upload date:
  • Size: 10.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for llm_markdown_sanitizer-0.1.0.tar.gz
Algorithm Hash digest
SHA256 29828c4ba3e34d051af75853b2e0f09110eb85f80b2a72f2eb6710d0b42d318d
MD5 c507c2a6beddcfabb564ddafd88d3b7b
BLAKE2b-256 c0c6a95c2ce472bb71f3d4553c49d236d1d21bef44700129f15ac28419c1b4c4

See more details on using hashes here.

Provenance

The following attestation bundles were made for llm_markdown_sanitizer-0.1.0.tar.gz:

Publisher: python-publish.yml on stlahxm/llm-markdown-sanitizer

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file llm_markdown_sanitizer-0.1.0-py3-none-any.whl.

File metadata

File hashes

Hashes for llm_markdown_sanitizer-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 0d1df81ddd7bc2e0afbbef31bd02e782031a5140db75cfaaa3ef488da49d0256
MD5 8242c475870b9d89528ef91e01ee8304
BLAKE2b-256 c9d4d1851b5e56dd3d82a67cedf0a1a04d3569e84ab980bd6739463df2d58969

See more details on using hashes here.

Provenance

The following attestation bundles were made for llm_markdown_sanitizer-0.1.0-py3-none-any.whl:

Publisher: python-publish.yml on stlahxm/llm-markdown-sanitizer

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page