Let your AI read your documents.

Tag, rename, and enrich any PDF or image. Free tier, no credit card.

• files_create_uploadReserve a pre-signed PUT slot for a file the agent holds locally, then follow the returned next_tool_call recipe — tag_file by default, extract_document when purpose='extract'. One slot type: any slot works with either tool. Bytes go straight from the agent host to storage and never traverse the LLM context. The host needs access to attachment bytes and an HTTP PUT capability. If it cannot transfer attachments, use a supplied sample URL or the private upload in the Gemina setup guide.
• tag_fileRun the FileTag pipeline against a previously uploaded slot. Returns extracted metadata, a suggested filename, six filename patterns, and a short-lived signed URL to an enriched copy with the metadata embedded in document properties or EXIF.
• tag_urlFetch a public HTTPS URL server-side under strict SSRF guards and run the FileTag pipeline on it. Same result shape as tag_file; the bytes never traverse the LLM context.
• get_filetag_resultRead a completed FileTag result and renew its download link. Uses saved fields and consumes no extraction or FileTag credits. The document must belong to your connection and still be retained.

Typed extraction over invoices, Hebrew documents, line items, raw OCR, and custom templates.

• extract_documentRun typed extraction on an uploaded slot from files_create_upload. Choose extraction_types: invoice_headers, invoice_line_items, custom_template, ocr (runs only on the praetorian model), or the legacy document_details_hebrew / document_line_items_hebrew (praetorian only, not recommended). Model choice is a recommendation, not a rule: velox for headers, invictus with thinking for line items. Asynchronous — returns the result directly or a correlationId to poll. Thinking, evaluation, correction, and coordinate toggles mirror the REST API.
• get_extraction_resultPoll for the result of an asynchronous extract_document call using its correlationId. Returns the completed extraction, or an in-process status to poll again.
• list_extractionsList past extractions, newest first. Filter by external_id, end_user_id, or an ISO date window, and paginate with skip and limit.
• get_extractionFetch one extraction by id, including the full extracted data.
• get_documentFetch one document by id, including all of its extractions.
• add_document_extractionsRun more extraction types on a document Gemina already stores — no re-upload. Pass the document id (from tag_file, extract_document, or get_document) and the extraction_types; paid per extraction like an upload. Two modes: leave wait at its default to hold the call and read the values in the same turn (poll pollCorrelationId with get_extraction_result), or pass wait=false to return at once when you only need the document filed for later search — the extraction still runs to completion and its outcome stays visible in get_document / list_extractions. Both modes cost the same. Every structured type (not plain OCR) is also submitted for indexing, so the document becomes answerable by query_documents and aggregate_documents; indexing is opt-in, plan-gated and best-effort. A pending upload slot (gfile_…) is not a document id.
• submit_extraction_feedbackSubmit verified or corrected field values for a completed extraction and get back a per-field comparison summary. Each extraction accepts feedback once.
• extract_urlRead a PDF or image at a public URL through the normal extraction pipeline. Uses extraction credits; does not run FileTag first. For a guided sample URL, Gemina supplies its prepared fields and collection. For another URL, provide extraction_types and template_id when using custom_template. If still in_process, poll get_extraction_result with the returned correlation id. Never claim a search result until extraction and indexing are ready.
• resume_tutorial_requestExplicitly recover an interrupted guided request with its original connection and original file. Reuses saved work; never dispatches from a progress read.

Ask questions and run spend analytics across the tenant's indexed documents — search and compute exact totals, no re-upload.

• query_documentsAsk across your whole indexed collection, no re-upload. Search in structured mode (exact field filters), semantic mode (natural-language similarity over extracted fields and FileTag metadata, not raw body text), or hybrid mode (keyword and semantic fused with Reciprocal Rank Fusion, the best default). Returns matched documents with their extracted fields; semantic and hybrid modes also return relevance scores.
• aggregate_documentsSpend analytics with no export: compute sums, averages, minimums, maximums, and counts over your indexed documents, grouped by vendor, currency, document type, expense type, payment method, end user, month, or year — e.g. total spent per vendor last quarter. Counts are per document (re-uploads collapse on a full identity match). Money metrics are always split per currency unless a currency filter is given, so totals are never mixed.
• index_documentManually (re)index one document into the searchable index — after corrections, or to backfill a document processed before indexing was enabled. Documents are otherwise submitted for indexing automatically for FileTag and structured extractions once the tenant enables it — plain OCR is not indexed, and a document can be skipped (e.g. no extractable fields or no indexing credits).