hired.candidate.ingest#

Turn extracted atomic-fact records into persisted, provenance-bearing facts.

The intelligence of extraction (reading a CV/bio/publication and proposing atomic claims) is supplied externally — by the hired-profile-ingest subagent in interactive use, or an injected LLM in autonomous use. This module is the deterministic glue: it validates those proposals into Fact objects, enforces the provenance-quote invariant, and persists them.

A record is a lightweight dict:

{"statement": "...", "category": "skill", "tags": ["python"],
 "confidence": "high", "quote": "...", "locator": "experience[1]",
 "is_negation": false}

Functions

`fact_from_record`(record, *, source_kind[, ...])	Build a (not-yet-persisted) `Fact` from a record dict.
`ingest_facts`(kb, records, *, source_kind[, ...])	Validate, quote-check, and persist fact records; return persisted ids.
`verify_quote`(quote, source_text)	True if `quote` is a verbatim substring of `source_text`.

hired.candidate.ingest.fact_from_record(record, *, source_kind, source_id='', subject='me')[source]#

Build a (not-yet-persisted) Fact from a record dict.

Return type:: Fact

hired.candidate.ingest.ingest_facts(kb, records, *, source_kind, source_id='', source_text=None, drop_unverified_quotes=True)[source]#

Validate, quote-check, and persist fact records; return persisted ids.

When source_text is given, each record’s quote is checked to be a verbatim substring. Unverified quotes are dropped (the fact is still kept, but without the spurious quote) unless drop_unverified_quotes is False, in which case a ValueError is raised — useful for strict pipelines.

Return type:: list[str]

hired.candidate.ingest.verify_quote(quote, source_text)[source]#

True if quote is a verbatim substring of source_text.

A None quote (no quote claimed) always verifies. When no source text is available to check against, we cannot disprove it, so it verifies too — the invariant only bites when we can check.

Return type:: bool