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.
1 maintainer
Metadata
1 maintainer
Release files for langchain-flatmark 1.0.10
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| File | Size | Uploaded | Provenance | |
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| langchain_flatmark-1.0.10-py3-none-any.whl | Python 3 | none | any | Details |
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