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Retrievers

Create Retriever

client.retrievers.create(RetrieverCreateParams { name, organization_id, project_id, pipelines } params, RequestOptionsoptions?): Retriever { id, name, project_id, 3 more }

POST/api/v1/retrievers

Upsert Retriever

client.retrievers.upsert(RetrieverUpsertParams { name, organization_id, project_id, pipelines } params, RequestOptionsoptions?): Retriever { id, name, project_id, 3 more }

PUT/api/v1/retrievers

List Retrievers

client.retrievers.list(RetrieverListParams { name, organization_id, project_id } query?, RequestOptionsoptions?): RetrieverListResponse { id, name, project_id, 3 more }

GET/api/v1/retrievers

Get Retriever

client.retrievers.get(stringretrieverID, RetrieverGetParams { organization_id, project_id } query?, RequestOptionsoptions?): Retriever { id, name, project_id, 3 more }

GET/api/v1/retrievers/{retriever_id}

Update Retriever

client.retrievers.update(stringretrieverID, RetrieverUpdateParams { pipelines, organization_id, project_id, name } params, RequestOptionsoptions?): Retriever { id, name, project_id, 3 more }

PUT/api/v1/retrievers/{retriever_id}

Delete Retriever

client.retrievers.delete(stringretrieverID, RetrieverDeleteParams { organization_id, project_id } params?, RequestOptionsoptions?): void

DELETE/api/v1/retrievers/{retriever_id}

Direct Retrieve

client.retrievers.search(RetrieverSearchParams { query, organization_id, project_id, 4 more } params, RequestOptionsoptions?): CompositeRetrievalResult { image_nodes, nodes, page_figure_nodes }

POST/api/v1/retrievers/retrieve

ModelsExpand Collapse

CompositeRetrievalMode = "routing" | "full"

Enum for the mode of composite retrieval.

One of the following:

"routing"

"full"

CompositeRetrievalResult { image_nodes, nodes, page_figure_nodes }

Deprecatedimage_nodes?: Array<PageScreenshotNodeWithScore { node, score, class_name } >

The image nodes retrieved by the pipeline for the given query. Deprecated - will soon be replaced with ‘page_screenshot_nodes’.

node: Node { file_id, image_size, page_index, metadata }

file_id: string

The ID of the file that the page screenshot was taken from

formatuuid

image_size: number

The size of the image in bytes

minimum0

page_index: number

The index of the page for which the screenshot is taken (0-indexed)

minimum0

metadata?: Record<string, unknown> | null

Metadata for the screenshot

score: number

The score of the screenshot node

class_name?: string

nodes?: Array<Node>

The retrieved nodes from the composite retrieval.

node: Node { id, end_char_idx, pipeline_id, 5 more }

id: string

The ID of the retrieved node.

formatuuid

end_char_idx: number | null

The end character index of the retrieved node in the document

pipeline_id: string

The ID of the pipeline this node was retrieved from.

formatuuid

retriever_id: string

The ID of the retriever this node was retrieved from.

formatuuid

retriever_pipeline_name: string

The name of the retrieval pipeline this node was retrieved from.

start_char_idx: number | null

The start character index of the retrieved node in the document

text: string

The text of the retrieved node.

metadata?: Record<string, unknown>

Metadata associated with the retrieved node.

class_name?: string

score?: number | null

page_figure_nodes?: Array<PageFigureNodeWithScore { node, score, class_name } >

The page figure nodes retrieved by the pipeline for the given query.

node: Node { confidence, figure_name, figure_size, 4 more }

confidence: number

The confidence of the figure

maximum1

minimum0

figure_name: string

The name of the figure

figure_size: number

The size of the figure in bytes

minimum0

file_id: string

The ID of the file that the figure was taken from

formatuuid

page_index: number

The index of the page for which the figure is taken (0-indexed)

minimum0

is_likely_noise?: boolean

Whether the figure is likely to be noise

metadata?: Record<string, unknown> | null

Metadata for the figure

score: number

The score of the figure node

class_name?: string

ReRankConfig { top_n, type }

top_n?: number

The number of nodes to retrieve after reranking over retrieved nodes from all retrieval tools.

minimum1

type?: "system_default" | "llm" | "cohere" | 3 more

The type of reranker to use.

One of the following:

"system_default"

"llm"

"cohere"

"bedrock"

"score"

"disabled"

Retriever { id, name, project_id, 3 more }

An entity that retrieves context nodes from several sub RetrieverTools.

id: string

Unique identifier

formatuuid

name: string

A name for the retriever tool. Will default to the pipeline name if not provided.

maxLength3000

minLength1

project_id: string

The ID of the project this retriever resides in.

formatuuid

created_at?: string | null

Creation datetime

formatdate-time

pipelines?: Array<RetrieverPipeline { description, name, pipeline_id, preset_retrieval_parameters } >

The pipelines this retriever uses.

description: string | null

A description of the retriever tool.

maxLength15000

name: string | null

A name for the retriever tool. Will default to the pipeline name if not provided.

maxLength3000

minLength1

pipeline_id: string

The ID of the pipeline this tool uses.

formatuuid

preset_retrieval_parameters?: PresetRetrievalParams { alpha, class_name, dense_similarity_cutoff, 11 more }

Parameters for retrieval configuration.

alpha?: number | null

Alpha value for hybrid retrieval to determine the weights between dense and sparse retrieval. 0 is sparse retrieval and 1 is dense retrieval.

maximum1

minimum0

class_name?: string

dense_similarity_cutoff?: number | null

Minimum similarity score wrt query for retrieval

maximum1

minimum0

dense_similarity_top_k?: number | null

Number of nodes for dense retrieval.

maximum100

minimum1

enable_reranking?: boolean | null

Enable reranking for retrieval

files_top_k?: number | null

Number of files to retrieve (only for retrieval mode files_via_metadata and files_via_content).

maximum5

minimum1

rerank_top_n?: number | null

Number of reranked nodes for returning.

maximum100

minimum1

retrieval_mode?: RetrievalMode

The retrieval mode for the query.

One of the following:

"chunks"

"files_via_metadata"

"files_via_content"

"auto_routed"

Deprecatedretrieve_image_nodes?: boolean

Whether to retrieve image nodes.

retrieve_page_figure_nodes?: boolean

Whether to retrieve page figure nodes.

retrieve_page_screenshot_nodes?: boolean

Whether to retrieve page screenshot nodes.

search_filters?: MetadataFilters { filters, condition } | null

Metadata filters for vector stores.

filters: Array<MetadataFilter { key, value, operator } | MetadataFilters { filters, condition } >

One of the following:

MetadataFilter { key, value, operator }

Comprehensive metadata filter for vector stores to support more operators.

Value uses Strict types, as int, float and str are compatible types and were all converted to string before.

See: https://docs.pydantic.dev/latest/usage/types/#strict-types

key: string

value: number | string | Array<string> | 2 more | null

One of the following:

number

string

Array<string>

Array<number>

Array<number>

operator?: "==" | ">" | "<" | 11 more

Vector store filter operator.

One of the following:

"=="

">"

"<"

"!="

">="

"<="

"in"

"nin"

"any"

"all"

"text_match"

"text_match_insensitive"

"contains"

"is_empty"

MetadataFilters = MetadataFilters { filters, condition }

condition?: "and" | "or" | "not" | null

Vector store filter conditions to combine different filters.

One of the following:

"and"

"or"

"not"

search_filters_inference_schema?: Record<string, Record<string, unknown> | Array<unknown> | string | 2 more | null> | null

JSON Schema that will be used to infer search_filters. Omit or leave as null to skip inference.

One of the following:

Record<string, unknown>

Array<unknown>

string

number

boolean

sparse_similarity_top_k?: number | null

Number of nodes for sparse retrieval.

maximum100

minimum1

updated_at?: string | null

Update datetime

formatdate-time

RetrieverCreate { name, pipelines }

name: string

A name for the retriever tool. Will default to the pipeline name if not provided.

maxLength3000

minLength1

pipelines?: Array<RetrieverPipeline { description, name, pipeline_id, preset_retrieval_parameters } >

The pipelines this retriever uses.

description: string | null

A description of the retriever tool.

maxLength15000

name: string | null

A name for the retriever tool. Will default to the pipeline name if not provided.

maxLength3000

minLength1

pipeline_id: string

The ID of the pipeline this tool uses.

formatuuid

preset_retrieval_parameters?: PresetRetrievalParams { alpha, class_name, dense_similarity_cutoff, 11 more }

Parameters for retrieval configuration.

alpha?: number | null

Alpha value for hybrid retrieval to determine the weights between dense and sparse retrieval. 0 is sparse retrieval and 1 is dense retrieval.

maximum1

minimum0

class_name?: string

dense_similarity_cutoff?: number | null

Minimum similarity score wrt query for retrieval

maximum1

minimum0

dense_similarity_top_k?: number | null

Number of nodes for dense retrieval.

maximum100

minimum1

enable_reranking?: boolean | null

Enable reranking for retrieval

files_top_k?: number | null

Number of files to retrieve (only for retrieval mode files_via_metadata and files_via_content).

maximum5

minimum1

rerank_top_n?: number | null

Number of reranked nodes for returning.

maximum100

minimum1

retrieval_mode?: RetrievalMode

The retrieval mode for the query.

One of the following:

"chunks"

"files_via_metadata"

"files_via_content"

"auto_routed"

Deprecatedretrieve_image_nodes?: boolean

Whether to retrieve image nodes.

retrieve_page_figure_nodes?: boolean

Whether to retrieve page figure nodes.

retrieve_page_screenshot_nodes?: boolean

Whether to retrieve page screenshot nodes.

search_filters?: MetadataFilters { filters, condition } | null

Metadata filters for vector stores.

filters: Array<MetadataFilter { key, value, operator } | MetadataFilters { filters, condition } >

One of the following:

MetadataFilter { key, value, operator }

Comprehensive metadata filter for vector stores to support more operators.

Value uses Strict types, as int, float and str are compatible types and were all converted to string before.

See: https://docs.pydantic.dev/latest/usage/types/#strict-types

key: string

value: number | string | Array<string> | 2 more | null

One of the following:

number

string

Array<string>

Array<number>

Array<number>

operator?: "==" | ">" | "<" | 11 more

Vector store filter operator.

One of the following:

"=="

">"

"<"

"!="

">="

"<="

"in"

"nin"

"any"

"all"

"text_match"

"text_match_insensitive"

"contains"

"is_empty"

MetadataFilters = MetadataFilters { filters, condition }

condition?: "and" | "or" | "not" | null

Vector store filter conditions to combine different filters.

One of the following:

"and"

"or"

"not"

search_filters_inference_schema?: Record<string, Record<string, unknown> | Array<unknown> | string | 2 more | null> | null

JSON Schema that will be used to infer search_filters. Omit or leave as null to skip inference.

One of the following:

Record<string, unknown>

Array<unknown>

string

number

boolean

sparse_similarity_top_k?: number | null

Number of nodes for sparse retrieval.

maximum100

minimum1

RetrieverPipeline { description, name, pipeline_id, preset_retrieval_parameters }

description: string | null

A description of the retriever tool.

maxLength15000

name: string | null

A name for the retriever tool. Will default to the pipeline name if not provided.

maxLength3000

minLength1

pipeline_id: string

The ID of the pipeline this tool uses.

formatuuid

preset_retrieval_parameters?: PresetRetrievalParams { alpha, class_name, dense_similarity_cutoff, 11 more }

Parameters for retrieval configuration.

alpha?: number | null

Alpha value for hybrid retrieval to determine the weights between dense and sparse retrieval. 0 is sparse retrieval and 1 is dense retrieval.

maximum1

minimum0

class_name?: string

dense_similarity_cutoff?: number | null

Minimum similarity score wrt query for retrieval

maximum1

minimum0

dense_similarity_top_k?: number | null

Number of nodes for dense retrieval.

maximum100

minimum1

enable_reranking?: boolean | null

Enable reranking for retrieval

files_top_k?: number | null

Number of files to retrieve (only for retrieval mode files_via_metadata and files_via_content).

maximum5

minimum1

rerank_top_n?: number | null

Number of reranked nodes for returning.

maximum100

minimum1

retrieval_mode?: RetrievalMode

The retrieval mode for the query.

One of the following:

"chunks"

"files_via_metadata"

"files_via_content"

"auto_routed"

Deprecatedretrieve_image_nodes?: boolean

Whether to retrieve image nodes.

retrieve_page_figure_nodes?: boolean

Whether to retrieve page figure nodes.

retrieve_page_screenshot_nodes?: boolean

Whether to retrieve page screenshot nodes.

search_filters?: MetadataFilters { filters, condition } | null

Metadata filters for vector stores.

filters: Array<MetadataFilter { key, value, operator } | MetadataFilters { filters, condition } >

One of the following:

MetadataFilter { key, value, operator }

Comprehensive metadata filter for vector stores to support more operators.

Value uses Strict types, as int, float and str are compatible types and were all converted to string before.

See: https://docs.pydantic.dev/latest/usage/types/#strict-types

key: string

value: number | string | Array<string> | 2 more | null

One of the following:

number

string

Array<string>

Array<number>

Array<number>

operator?: "==" | ">" | "<" | 11 more

Vector store filter operator.

One of the following:

"=="

">"

"<"

"!="

">="

"<="

"in"

"nin"

"any"

"all"

"text_match"

"text_match_insensitive"

"contains"

"is_empty"

MetadataFilters = MetadataFilters { filters, condition }

condition?: "and" | "or" | "not" | null

Vector store filter conditions to combine different filters.

One of the following:

"and"

"or"

"not"

search_filters_inference_schema?: Record<string, Record<string, unknown> | Array<unknown> | string | 2 more | null> | null

JSON Schema that will be used to infer search_filters. Omit or leave as null to skip inference.

One of the following:

Record<string, unknown>

Array<unknown>

string

number

boolean

sparse_similarity_top_k?: number | null

Number of nodes for sparse retrieval.

maximum100

minimum1

RetrieverListResponse = Array<Retriever { id, name, project_id, 3 more } >

id: string

Unique identifier

formatuuid

name: string

A name for the retriever tool. Will default to the pipeline name if not provided.

maxLength3000

minLength1

project_id: string

The ID of the project this retriever resides in.

formatuuid

created_at?: string | null

Creation datetime

formatdate-time

pipelines?: Array<RetrieverPipeline { description, name, pipeline_id, preset_retrieval_parameters } >

The pipelines this retriever uses.

description: string | null

A description of the retriever tool.

maxLength15000

name: string | null

A name for the retriever tool. Will default to the pipeline name if not provided.

maxLength3000

minLength1

pipeline_id: string

The ID of the pipeline this tool uses.

formatuuid

preset_retrieval_parameters?: PresetRetrievalParams { alpha, class_name, dense_similarity_cutoff, 11 more }

Parameters for retrieval configuration.

alpha?: number | null

Alpha value for hybrid retrieval to determine the weights between dense and sparse retrieval. 0 is sparse retrieval and 1 is dense retrieval.

maximum1

minimum0

class_name?: string

dense_similarity_cutoff?: number | null

Minimum similarity score wrt query for retrieval

maximum1

minimum0

dense_similarity_top_k?: number | null

Number of nodes for dense retrieval.

maximum100

minimum1

enable_reranking?: boolean | null

Enable reranking for retrieval

files_top_k?: number | null

Number of files to retrieve (only for retrieval mode files_via_metadata and files_via_content).

maximum5

minimum1

rerank_top_n?: number | null

Number of reranked nodes for returning.

maximum100

minimum1

retrieval_mode?: RetrievalMode

The retrieval mode for the query.

One of the following:

"chunks"

"files_via_metadata"

"files_via_content"

"auto_routed"

Deprecatedretrieve_image_nodes?: boolean

Whether to retrieve image nodes.

retrieve_page_figure_nodes?: boolean

Whether to retrieve page figure nodes.

retrieve_page_screenshot_nodes?: boolean

Whether to retrieve page screenshot nodes.

search_filters?: MetadataFilters { filters, condition } | null

Metadata filters for vector stores.

filters: Array<MetadataFilter { key, value, operator } | MetadataFilters { filters, condition } >

One of the following:

MetadataFilter { key, value, operator }

Comprehensive metadata filter for vector stores to support more operators.

Value uses Strict types, as int, float and str are compatible types and were all converted to string before.

See: https://docs.pydantic.dev/latest/usage/types/#strict-types

key: string

value: number | string | Array<string> | 2 more | null

One of the following:

number

string

Array<string>

Array<number>

Array<number>

operator?: "==" | ">" | "<" | 11 more

Vector store filter operator.

One of the following:

"=="

">"

"<"

"!="

">="

"<="

"in"

"nin"

"any"

"all"

"text_match"

"text_match_insensitive"

"contains"

"is_empty"

MetadataFilters = MetadataFilters { filters, condition }

condition?: "and" | "or" | "not" | null

Vector store filter conditions to combine different filters.

One of the following:

"and"

"or"

"not"

search_filters_inference_schema?: Record<string, Record<string, unknown> | Array<unknown> | string | 2 more | null> | null

JSON Schema that will be used to infer search_filters. Omit or leave as null to skip inference.

One of the following:

Record<string, unknown>

Array<unknown>

string

number

boolean

sparse_similarity_top_k?: number | null

Number of nodes for sparse retrieval.

maximum100

minimum1

updated_at?: string | null

Update datetime

formatdate-time

RetrieversRetriever

Retrieve

client.retrievers.retriever.search(stringretrieverID, RetrieverSearchParams { query, organization_id, project_id, 3 more } params, RequestOptionsoptions?): CompositeRetrievalResult { image_nodes, nodes, page_figure_nodes }

POST/api/v1/retrievers/{retriever_id}/retrieve