What lands on a document-based reference system is DOCX, XLSX, PPTX, PDF, scans and recordings. loomcycle v1.122 to v1.124 reads them without the model ever holding the bytes: pure-Go extraction to Markdown with bounded zip and XML parsers, PDF text layers with CMaps and Cyrillic, and an import that builds a Document tagged untrusted with pictures as image chunks by page and slide. Pages with no text layer go through OCR by a vision model, opted into by both operator and agent, with page caps, a ledger purpose and a dry-run cost estimate. Recordings go through any OpenAI-audio-shaped whisper server, cut into overlapping pieces under minute budgets. Search filters by path, document, type, status, tag and as_of act inside every retrieval leg rather than after it, chunks carry validity periods, and documents_scope keeps notes and references apart.
From a scanned page and a recording to a searchable document
Loomcycle versions v1.122 through v1.124 add pure-Go extraction of DOCX, XLSX, PPTX, PDF, scanned pages and audio recordings into Markdown without the model ever holding the source bytes, the project announced. The release builds a Document tagged untrusted with pictures stored as image chunks by page and slide, routes text-layer-free pages through vision-model OCR that both operator and agent must opt into with page caps, a ledger purpose and a dry-run cost estimate, and sends recordings through any OpenAI-audio-shaped whisper server cut into overlapping pieces under minute budgets. Search now filters by path, document, type, status, tag and as_of act inside every retrieval leg rather than after it, with chunks carrying validity periods and documents_scope keeping notes and references apart.
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