__query_collection() — langchain Function Reference
Architecture documentation for the __query_collection() function in vectorstores.py from the langchain codebase.
Entity Profile
Dependency Diagram
graph TD 180f6c1b_bb48_bf57_69cd_8e866f8993df["__query_collection()"] d25f9e94_3ec0_b9ca_7d2f_eb7ef487ccab["Chroma"] 180f6c1b_bb48_bf57_69cd_8e866f8993df -->|defined in| d25f9e94_3ec0_b9ca_7d2f_eb7ef487ccab style 180f6c1b_bb48_bf57_69cd_8e866f8993df fill:#6366f1,stroke:#818cf8,color:#fff
Relationship Graph
Source Code
libs/partners/chroma/langchain_chroma/vectorstores.py lines 450–484
def __query_collection(
self,
query_texts: list[str] | None = None,
query_embeddings: list[list[float]] | None = None,
n_results: int = 4,
where: dict[str, str] | None = None,
where_document: dict[str, str] | None = None,
**kwargs: Any,
) -> list[Document] | chromadb.QueryResult:
"""Query the chroma collection.
Args:
query_texts: List of query texts.
query_embeddings: List of query embeddings.
n_results: Number of results to return.
where: dict used to filter results by metadata.
E.g. {"color" : "red"}.
where_document: dict used to filter by the document contents.
E.g. {"$contains": "hello"}.
kwargs: Additional keyword arguments to pass to Chroma collection query.
Returns:
List of `n_results` nearest neighbor embeddings for provided
query_embeddings or query_texts.
See more: https://docs.trychroma.com/reference/py-collection#query
"""
return self._collection.query(
query_texts=query_texts,
query_embeddings=query_embeddings, # type: ignore[arg-type]
n_results=n_results,
where=where, # type: ignore[arg-type]
where_document=where_document, # type: ignore[arg-type]
**kwargs,
)
Domain
Subdomains
Source
Frequently Asked Questions
What does __query_collection() do?
__query_collection() is a function in the langchain codebase, defined in libs/partners/chroma/langchain_chroma/vectorstores.py.
Where is __query_collection() defined?
__query_collection() is defined in libs/partners/chroma/langchain_chroma/vectorstores.py at line 450.
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