API
Document Filtered Search
Performs a full text search on documents in a dataset, then uses those documents to perform an embedding search on the dataset. This is the same as calling /search-documents followed by /search, and using the documents from the first call as a metadata filter.
POST
/
api
/
datasets
/
{id}
/
document-filtered-search
Path Parameters
id
string
requiredDataset ID
Header
Authorization
string
Baseplate API key. Must be in the format โBearer $BASEPLATE_API_KEYโ
Body Parameters
query
string
requiredQuery string
top_k_documents
number
default: "3"Number of documents to use in embedding search filter.
top_k_rows
number
default: "3"Number of documents to use in embedding search filter.
Responses
{
"document_results": [
{
"document_id": "fc74e81e-05ac-4df6-936f-ce51cc69a868",
"dataset_id": "e2fa7f7b-d580-4ecf-8232-a1131938a3fc",
"content": "",
"filename": "doc1.pdf",
"url": "/5274962e-04c3-4a23-b3d5-1d7e1ea6a230/doc1.pdf",
"similarity": 0.0919062
},
{
"document_id": "e6afaf5b-e8f0-4af3-ba50-bbb2d0d1f1af",
"dataset_id": "e2fa7f7b-d580-4ecf-8232-a1131938a3fc",
"content": "",
"filename": "doc2.pdf",
"url": "/5274962e-04c3-4a23-b3d5-1d7e1ea6a230/doc2.pdf",
"similarity": 0.0919062
}
],
"results": [
{
"embedding": "Example text",
"data": {
"text": "Example text"
},
"confidence": 10.3084955,
"query": "text",
"metadata": {
"documentId": "fc74e81e-05ac-4df6-936f-ce51cc69a868",
"rowId": 567228,
"url": "/5274962e-04c3-4a23-b3d5-1d7e1ea6a230/doc1.pdf"
}
},
{
"embedding": "Example text 2",
"data": {
"text": "Example text 2"
},
"confidence": 10.3084955,
"query": "text",
"metadata": {
"documentId": "e6afaf5b-e8f0-4af3-ba50-bbb2d0d1f1af",
"rowId": 569813,
"url": "/5274962e-04c3-4a23-b3d5-1d7e1ea6a230/doc2.pdf"
}
}
]
}