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.
Metadata
Release files for langchain-flatmark 1.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| langchain_flatmark-1.0.1.tar.gz | 5.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| langchain_flatmark-1.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.9 kB
Release files / langchain_flatmark-1.0.1.tar.gz
| Download URL | langchain_flatmark-1.0.1.tar.gz |
|---|---|
| Size | 5.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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Transparency logRelease files / langchain_flatmark-1.0.1-py3-none-any.whl
| Download URL | langchain_flatmark-1.0.1-py3-none-any.whl |
|---|---|
| Size | 5.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
498ae15143295ad4a41d9770705496cb1acccb5d5a9f2d1eaf268c4fc78722a3
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|
BLAKE2b-256 checksum How to use checksums |
040a2b87aa309d229a9c0d0abf43e00e04d810a071adc6c698403cfab2e4ab35
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
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