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langchain-flatmark

Document to Markdown API and MCP server for PDF, Word, PowerPoint, Excel and HTML. OCR queue for large files. Hosted in Germany.

A LangChain document loader for the flatmark API: FlatmarkLoader turns local files and URLs into Markdown Documents.

pip install langchain-flatmark
from langchain_flatmark import FlatmarkLoader

docs = FlatmarkLoader("report.pdf").load()
print(docs[0].page_content)

Direct conversion (POST /v1/convert) works without a key at a lower rate limit. Get an API key and pass it as api_key= or set FLATMARK_API_KEY.

For large or scanned files, convert through the queue (an API key is required):

loader = FlatmarkLoader(["scan.pdf", "https://example.com/deck.pptx"], use_queue=True)
for doc in loader.lazy_load():
    print(doc.metadata, len(doc.page_content))

The loader submits POST /v1/convert/jobs, polls GET /v1/jobs/{job_id} until the job's status is succeeded or failed, then downloads GET /v1/convert/jobs/{job_id}/result.

Documents

One Document per source; page_content is the Markdown. metadata carries source (the path or URL as given) plus the meta fields of the answer — and job_id for a queued conversion.

A URL is downloaded by the loader without your key, then uploaded. Other options: base_url, poll_interval, timeout, and client (an httpx.Client for proxies or retries).

API reference: https://flatmark.dev/docs · Support: https://flatmark.dev/support · Generated from openapi.json.

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Release files for langchain-flatmark 1.0.6

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