Search

Search documents

search.execute() -> SearchExecuteResponse

POST/v3/search

Search documents

search.documents() -> SearchDocumentsResponse

POST/v3/search

Search memory entries

search.memories() -> SearchMemoriesResponse

POST/v4/search

ModelsExpand Collapse

class SearchExecuteResponse: …

results: List[Result]

chunks: List[ResultChunk]

Matching content chunks from the document

content: str

Content of the matching chunk

is_relevant: bool

Whether this chunk is relevant to the query

score: float

Similarity score for this chunk

maximum1

minimum0

created_at: str

Document creation date

formatdatetime

document_id: str

ID of the matching document

metadata: Optional[Dict[str, object]]

Document metadata

score: float

Relevance score of the match

maximum1

minimum0

title: Optional[str]

Document title

type: Optional[str]

Document type

updated_at: str

Document last update date

formatdatetime

content: Optional[str]

Full document content (only included when includeFullDocs=true)

summary: Optional[str]

Document summary

timing: float

total: float

class SearchDocumentsResponse: …

results: List[Result]

chunks: List[ResultChunk]

Matching content chunks from the document

content: str

Content of the matching chunk

is_relevant: bool

Whether this chunk is relevant to the query

score: float

Similarity score for this chunk

maximum1

minimum0

created_at: str

Document creation date

formatdatetime

document_id: str

ID of the matching document

metadata: Optional[Dict[str, object]]

Document metadata

score: float

Relevance score of the match

maximum1

minimum0

title: Optional[str]

Document title

type: Optional[str]

Document type

updated_at: str

Document last update date

formatdatetime

content: Optional[str]

Full document content (only included when includeFullDocs=true)

summary: Optional[str]

Document summary

timing: float

total: float

class SearchMemoriesResponse: …

results: List[Result]

Array of matching memory entries and chunks with similarity scores. Contains memory results when searchMode=‘memories’, both memory and chunk results when searchMode=‘hybrid’, or only chunk results when searchMode=‘documents’. Memory results have ‘memory’ field, chunk results have ‘chunk’ field. BACKWARD COMPATIBILITY: When using deprecated include.chunks=true, only memory results are returned with chunks embedded in them (old format).

id: str

Memory entry ID or chunk ID

metadata: Optional[Dict[str, object]]

Memory metadata

similarity: float

Similarity score between the query and memory entry

maximum1

minimum0

updated_at: str

Memory last update date

formatdatetime

chunk: Optional[str]

The chunk content (only present for chunk results from hybrid search)

chunks: Optional[List[ResultChunk]]

Relevant chunks from associated documents (only included when chunks=true)

content: str

Content of the chunk

document_id: str

ID of the document this chunk belongs to

position: float

Position of chunk in the document (0-indexed)

score: float

Similarity score between the query and chunk

maximum1

minimum0

context: Optional[ResultContext]

Object containing version history (parents/children via updates) and related memories (extends/derives)

children: Optional[List[ResultContextChild]]

memory: str

The contextual memory content

relation: Literal["updates", "extends", "derives"]

Relation type between this memory and its parent/child

One of the following:

"updates"

"extends"

"derives"

updated_at: str

Contextual memory last update date

formatdatetime

metadata: Optional[Dict[str, object]]

Contextual memory metadata

version: Optional[float]

Relative version distance from the primary memory (+1 for direct child, +2 for grand-child, etc.)

parents: Optional[List[ResultContextParent]]

memory: str

The contextual memory content

relation: Literal["updates", "extends", "derives"]

Relation type between this memory and its parent/child

One of the following:

"updates"

"extends"

"derives"

updated_at: str

Contextual memory last update date

formatdatetime

metadata: Optional[Dict[str, object]]

Contextual memory metadata

version: Optional[float]

Relative version distance from the primary memory (-1 for direct parent, -2 for grand-parent, etc.)

One of the following:

documents: Optional[List[ResultDocument]]

Associated documents for this memory entry

id: str

Document ID

created_at: str

Document creation date

formatdatetime

updated_at: str

Document last update date

formatdatetime

metadata: Optional[Dict[str, object]]

Document metadata (only included when documents=true)

summary: Optional[str]

Document summary (only included when summaries=true)

title: Optional[str]

Document title (only included when documents=true)

type: Optional[str]

Document type (only included when documents=true)

filepath: Optional[str]

Filepath of the source document this memory or chunk came from

is_aggregated: Optional[bool]

Indicates if this memory was created by aggregating multiple source memories

memory: Optional[str]

The memory content (only present for memory results)

version: Optional[float]

Version number of this memory entry

timing: float

Search execution time in milliseconds

total: float

Total number of results returned