
Query Documents in a Collection
query(
client,
collection_name,
query_embeddings,
n_results = 10L,
where = NULL,
where_document = NULL,
include = c("documents", "metadatas", "distances"),
tenant = "default_tenant",
database = "default_database"
)
A list containing the query results. Each element (documents, metadatas, distances) is a nested list, so use double brackets [[]] to access individual elements.
A ChromaDB client object
Name of the collection
List of query embeddings (must be a list of numeric vectors)
Number of results to return per query (default: 10)
Optional filtering conditions
Optional document-based filtering conditions
Optional vector of what to include in results. Possible values: "documents", "embeddings", "metadatas", "distances", "uris", "data" (default: c("documents", "metadatas", "distances"))
The tenant name (default: "default")
The database name (default: "default")
Note that ChromaDB's API only accepts embeddings for queries. If you want to query using text, you need to first convert your text to embeddings using an embedding model (e.g., using OpenAI's API, HuggingFace's API, or a local model).
Example:
# First convert text to embeddings using your preferred method
text_embedding <- your_embedding_function("your search text")
# Then query using the embedding
result <- query(client, "my_collection",
query_embeddings = list(text_embedding))