Knowledge

from definable.knowledge import Knowledge

Constructor

Parameter	Type	Default	Description
`vector_db`	`VectorDB`	`InMemoryVectorDB()`	Vector database backend.
`embedder`	`Embedder`	`OpenAIEmbedder()`	Embedding provider.
`reranker`	`Reranker`	`None`	Optional reranker.
`chunker`	`Chunker`	`None`	Text chunker for `add()`.
`readers`	`List[Reader]`	auto	Document readers.
`auto_detect_reader`	`bool`	`True`	Auto-detect reader from source.
`top_k`	`int`	`5`	Number of results per search.
`trigger`	`str`	`"always"`	When to search: `"always"`, `"auto"`, `"never"`.
`context_format`	`str`	`"xml"`	`"xml"` or `"markdown"`.
`fts_index`	`FTSIndex`	`None`	Full-text search index for hybrid search.
`hybrid_config`	`HybridSearchConfig`	`None`	Vector + text merge config.
`temporal_decay`	`TemporalDecay`	`None`	Score decay by document age.
`mmr`	`MMRConfig`	`None`	Diversity reranking.

Method	Returns	Description
`add(source)`	`List[str]`	Add content (string, file path, or URL).
`aadd(source)`	`List[str]`	Async add.
`search(query, top_k=)`	`List[Document]`	Search by similarity.
`asearch(query, top_k=)`	`List[Document]`	Async search.
`remove(doc_ids)`	—	Remove documents by ID.
`clear()`	—	Remove all documents.
`__len__()`	`int`	Document count.

from definable.knowledge import Document

Parameter	Type	Default	Description
`merge_strategy`	`str`	`"rrf"`	`"rrf"` (reciprocal rank fusion) or `"weighted"`.
`vector_weight`	`float`	`0.7`	Weight for vector results.
`text_weight`	`float`	`0.3`	Weight for text results.

Parameter	Type	Default	Description
`half_life_days`	`float`	`30.0`	Days until score halves.
`evergreen_meta_key`	`str`	`None`	Meta key that exempts from decay.

Parameter	Type	Default	Description
`lambda_param`	`float`	`0.7`	Relevance vs diversity tradeoff.
`top_n`	`int`	`None`	Results after MMR.