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POMA AI SDK ​

PrimeCut is the recommended client in the poma package. Use it to ingest documents, collect typed results, store .poma archives, and feed structure-aware chunksets into your retrieval stack.

The package also exports AsyncPrimeCut, PomaArchive, unpack, and generate_cheatsheets for async workflows, archive handling, and retrieval post-processing.

The legacy Poma client still ships for compatibility. It is deprecated. New code should start with PrimeCut or AsyncPrimeCut.

Looking for an older SDK snapshot? Use the version switch above this page.

python
from poma import PrimeCut

client = PrimeCut()
result = client.ingest("example.pdf", show_progress=True)

print(len(result.chunksets))
print(result.chunksets[0].to_embed)

Getting started ​

  • Installation Install poma and the integration extras you need.
  • Authentication Create a POMA_API_KEY and configure your environment.
  • Quickstart Process your first document with PrimeCut.

Core workflow ​

  • Ingest a file with PrimeCut.ingest(...)
  • Collect a previously submitted job with PrimeCut.collect(...)
  • Work with PomaResult, PomaChunk, and PomaChunkSet
  • Save or reopen .poma archives with PomaArchive or unpack(...)
  • Generate structure-preserving cheatsheets with generate_cheatsheets(...)
  • Connect the result to Qdrant, LangChain, or LlamaIndex

Concepts ​

CLI ​

Prefer the terminal? The poma CLI uses the same public API (v2) for ingest, job status, downloads, and basic account flows.

Integrations and reference ​