# Retrievers ## Create Retriever `client.Retrievers.New(ctx, params) (*Retriever, error)` **post** `/api/v1/retrievers` Create a new Retriever. ### Parameters - `params RetrieverNewParams` - `RetrieverCreate param.Field[RetrieverCreate]` Body param - `OrganizationID param.Field[string]` Query param - `ProjectID param.Field[string]` Query param ### Returns - `type Retriever struct{…}` An entity that retrieves context nodes from several sub RetrieverTools. - `ID string` Unique identifier - `Name string` A name for the retriever tool. Will default to the pipeline name if not provided. - `ProjectID string` The ID of the project this retriever resides in. - `CreatedAt Time` Creation datetime - `Pipelines []RetrieverPipeline` The pipelines this retriever uses. - `Description string` A description of the retriever tool. - `Name string` A name for the retriever tool. Will default to the pipeline name if not provided. - `PipelineID string` The ID of the pipeline this tool uses. - `PresetRetrievalParameters PresetRetrievalParamsResp` Parameters for retrieval configuration. - `Alpha float64` Alpha value for hybrid retrieval to determine the weights between dense and sparse retrieval. 0 is sparse retrieval and 1 is dense retrieval. - `ClassName string` - `DenseSimilarityCutoff float64` Minimum similarity score wrt query for retrieval - `DenseSimilarityTopK int64` Number of nodes for dense retrieval. - `EnableReranking bool` Enable reranking for retrieval - `FilesTopK int64` Number of files to retrieve (only for retrieval mode files_via_metadata and files_via_content). - `RerankTopN int64` Number of reranked nodes for returning. - `RetrievalMode RetrievalMode` The retrieval mode for the query. - `const RetrievalModeChunks RetrievalMode = "chunks"` - `const RetrievalModeFilesViaMetadata RetrievalMode = "files_via_metadata"` - `const RetrievalModeFilesViaContent RetrievalMode = "files_via_content"` - `const RetrievalModeAutoRouted RetrievalMode = "auto_routed"` - `RetrieveImageNodes bool` Whether to retrieve image nodes. - `RetrievePageFigureNodes bool` Whether to retrieve page figure nodes. - `RetrievePageScreenshotNodes bool` Whether to retrieve page screenshot nodes. - `SearchFilters MetadataFilters` Metadata filters for vector stores. - `Filters []MetadataFiltersFilterUnion` - `type MetadataFiltersFilterMetadataFilter struct{…}` 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 MetadataFiltersFilterMetadataFilterValueUnion` - `float64` - `string` - `type MetadataFiltersFilterMetadataFilterValueArray []string` - `type MetadataFiltersFilterMetadataFilterValueArray []float64` - `type MetadataFiltersFilterMetadataFilterValueArray []int64` - `Operator string` Vector store filter operator. - `const MetadataFiltersFilterMetadataFilterOperatorEquals MetadataFiltersFilterMetadataFilterOperator = "=="` - `const MetadataFiltersFilterMetadataFilterOperatorGreater MetadataFiltersFilterMetadataFilterOperator = ">"` - `const MetadataFiltersFilterMetadataFilterOperatorLess MetadataFiltersFilterMetadataFilterOperator = "<"` - `const MetadataFiltersFilterMetadataFilterOperatorNotEquals MetadataFiltersFilterMetadataFilterOperator = "!="` - `const MetadataFiltersFilterMetadataFilterOperatorGreaterOrEquals MetadataFiltersFilterMetadataFilterOperator = ">="` - `const MetadataFiltersFilterMetadataFilterOperatorLessOrEquals MetadataFiltersFilterMetadataFilterOperator = "<="` - `const MetadataFiltersFilterMetadataFilterOperatorIn MetadataFiltersFilterMetadataFilterOperator = "in"` - `const MetadataFiltersFilterMetadataFilterOperatorNin MetadataFiltersFilterMetadataFilterOperator = "nin"` - `const MetadataFiltersFilterMetadataFilterOperatorAny MetadataFiltersFilterMetadataFilterOperator = "any"` - `const MetadataFiltersFilterMetadataFilterOperatorAll MetadataFiltersFilterMetadataFilterOperator = "all"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatch MetadataFiltersFilterMetadataFilterOperator = "text_match"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatchInsensitive MetadataFiltersFilterMetadataFilterOperator = "text_match_insensitive"` - `const MetadataFiltersFilterMetadataFilterOperatorContains MetadataFiltersFilterMetadataFilterOperator = "contains"` - `const MetadataFiltersFilterMetadataFilterOperatorIsEmpty MetadataFiltersFilterMetadataFilterOperator = "is_empty"` - `type MetadataFilters struct{…}` Metadata filters for vector stores. - `Condition MetadataFiltersCondition` Vector store filter conditions to combine different filters. - `const MetadataFiltersConditionAnd MetadataFiltersCondition = "and"` - `const MetadataFiltersConditionOr MetadataFiltersCondition = "or"` - `const MetadataFiltersConditionNot MetadataFiltersCondition = "not"` - `SearchFiltersInferenceSchema map[string, PresetRetrievalParamsSearchFiltersInferenceSchemaUnionResp]` JSON Schema that will be used to infer search_filters. Omit or leave as null to skip inference. - `type PresetRetrievalParamsSearchFiltersInferenceSchemaMap map[string, any]` - `type PresetRetrievalParamsSearchFiltersInferenceSchemaArray []any` - `string` - `float64` - `bool` - `SparseSimilarityTopK int64` Number of nodes for sparse retrieval. - `UpdatedAt Time` Update datetime ### Example ```go package main import ( "context" "fmt" "github.com/stainless-sdks/llamacloud-prod-go" "github.com/stainless-sdks/llamacloud-prod-go/option" ) func main() { client := llamacloudprod.NewClient( option.WithAPIKey("My API Key"), ) retriever, err := client.Retrievers.New(context.TODO(), llamacloudprod.RetrieverNewParams{ RetrieverCreate: llamacloudprod.RetrieverCreateParam{ Name: "x", }, }) if err != nil { panic(err.Error()) } fmt.Printf("%+v\n", retriever.ID) } ``` #### Response ```json { "id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "name": "x", "project_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "created_at": "2019-12-27T18:11:19.117Z", "pipelines": [ { "description": "description", "name": "x", "pipeline_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "preset_retrieval_parameters": { "alpha": 0, "class_name": "class_name", "dense_similarity_cutoff": 0, "dense_similarity_top_k": 1, "enable_reranking": true, "files_top_k": 1, "rerank_top_n": 1, "retrieval_mode": "chunks", "retrieve_image_nodes": true, "retrieve_page_figure_nodes": true, "retrieve_page_screenshot_nodes": true, "search_filters": { "filters": [ { "key": "key", "value": 0, "operator": "==" } ], "condition": "and" }, "search_filters_inference_schema": { "foo": { "foo": "bar" } }, "sparse_similarity_top_k": 1 } } ], "updated_at": "2019-12-27T18:11:19.117Z" } ``` ## Upsert Retriever `client.Retrievers.Upsert(ctx, params) (*Retriever, error)` **put** `/api/v1/retrievers` Upsert a new Retriever. ### Parameters - `params RetrieverUpsertParams` - `RetrieverCreate param.Field[RetrieverCreate]` Body param - `OrganizationID param.Field[string]` Query param - `ProjectID param.Field[string]` Query param ### Returns - `type Retriever struct{…}` An entity that retrieves context nodes from several sub RetrieverTools. - `ID string` Unique identifier - `Name string` A name for the retriever tool. Will default to the pipeline name if not provided. - `ProjectID string` The ID of the project this retriever resides in. - `CreatedAt Time` Creation datetime - `Pipelines []RetrieverPipeline` The pipelines this retriever uses. - `Description string` A description of the retriever tool. - `Name string` A name for the retriever tool. Will default to the pipeline name if not provided. - `PipelineID string` The ID of the pipeline this tool uses. - `PresetRetrievalParameters PresetRetrievalParamsResp` Parameters for retrieval configuration. - `Alpha float64` Alpha value for hybrid retrieval to determine the weights between dense and sparse retrieval. 0 is sparse retrieval and 1 is dense retrieval. - `ClassName string` - `DenseSimilarityCutoff float64` Minimum similarity score wrt query for retrieval - `DenseSimilarityTopK int64` Number of nodes for dense retrieval. - `EnableReranking bool` Enable reranking for retrieval - `FilesTopK int64` Number of files to retrieve (only for retrieval mode files_via_metadata and files_via_content). - `RerankTopN int64` Number of reranked nodes for returning. - `RetrievalMode RetrievalMode` The retrieval mode for the query. - `const RetrievalModeChunks RetrievalMode = "chunks"` - `const RetrievalModeFilesViaMetadata RetrievalMode = "files_via_metadata"` - `const RetrievalModeFilesViaContent RetrievalMode = "files_via_content"` - `const RetrievalModeAutoRouted RetrievalMode = "auto_routed"` - `RetrieveImageNodes bool` Whether to retrieve image nodes. - `RetrievePageFigureNodes bool` Whether to retrieve page figure nodes. - `RetrievePageScreenshotNodes bool` Whether to retrieve page screenshot nodes. - `SearchFilters MetadataFilters` Metadata filters for vector stores. - `Filters []MetadataFiltersFilterUnion` - `type MetadataFiltersFilterMetadataFilter struct{…}` 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 MetadataFiltersFilterMetadataFilterValueUnion` - `float64` - `string` - `type MetadataFiltersFilterMetadataFilterValueArray []string` - `type MetadataFiltersFilterMetadataFilterValueArray []float64` - `type MetadataFiltersFilterMetadataFilterValueArray []int64` - `Operator string` Vector store filter operator. - `const MetadataFiltersFilterMetadataFilterOperatorEquals MetadataFiltersFilterMetadataFilterOperator = "=="` - `const MetadataFiltersFilterMetadataFilterOperatorGreater MetadataFiltersFilterMetadataFilterOperator = ">"` - `const MetadataFiltersFilterMetadataFilterOperatorLess MetadataFiltersFilterMetadataFilterOperator = "<"` - `const MetadataFiltersFilterMetadataFilterOperatorNotEquals MetadataFiltersFilterMetadataFilterOperator = "!="` - `const MetadataFiltersFilterMetadataFilterOperatorGreaterOrEquals MetadataFiltersFilterMetadataFilterOperator = ">="` - `const MetadataFiltersFilterMetadataFilterOperatorLessOrEquals MetadataFiltersFilterMetadataFilterOperator = "<="` - `const MetadataFiltersFilterMetadataFilterOperatorIn MetadataFiltersFilterMetadataFilterOperator = "in"` - `const MetadataFiltersFilterMetadataFilterOperatorNin MetadataFiltersFilterMetadataFilterOperator = "nin"` - `const MetadataFiltersFilterMetadataFilterOperatorAny MetadataFiltersFilterMetadataFilterOperator = "any"` - `const MetadataFiltersFilterMetadataFilterOperatorAll MetadataFiltersFilterMetadataFilterOperator = "all"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatch MetadataFiltersFilterMetadataFilterOperator = "text_match"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatchInsensitive MetadataFiltersFilterMetadataFilterOperator = "text_match_insensitive"` - `const MetadataFiltersFilterMetadataFilterOperatorContains MetadataFiltersFilterMetadataFilterOperator = "contains"` - `const MetadataFiltersFilterMetadataFilterOperatorIsEmpty MetadataFiltersFilterMetadataFilterOperator = "is_empty"` - `type MetadataFilters struct{…}` Metadata filters for vector stores. - `Condition MetadataFiltersCondition` Vector store filter conditions to combine different filters. - `const MetadataFiltersConditionAnd MetadataFiltersCondition = "and"` - `const MetadataFiltersConditionOr MetadataFiltersCondition = "or"` - `const MetadataFiltersConditionNot MetadataFiltersCondition = "not"` - `SearchFiltersInferenceSchema map[string, PresetRetrievalParamsSearchFiltersInferenceSchemaUnionResp]` JSON Schema that will be used to infer search_filters. Omit or leave as null to skip inference. - `type PresetRetrievalParamsSearchFiltersInferenceSchemaMap map[string, any]` - `type PresetRetrievalParamsSearchFiltersInferenceSchemaArray []any` - `string` - `float64` - `bool` - `SparseSimilarityTopK int64` Number of nodes for sparse retrieval. - `UpdatedAt Time` Update datetime ### Example ```go package main import ( "context" "fmt" "github.com/stainless-sdks/llamacloud-prod-go" "github.com/stainless-sdks/llamacloud-prod-go/option" ) func main() { client := llamacloudprod.NewClient( option.WithAPIKey("My API Key"), ) retriever, err := client.Retrievers.Upsert(context.TODO(), llamacloudprod.RetrieverUpsertParams{ RetrieverCreate: llamacloudprod.RetrieverCreateParam{ Name: "x", }, }) if err != nil { panic(err.Error()) } fmt.Printf("%+v\n", retriever.ID) } ``` #### Response ```json { "id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "name": "x", "project_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "created_at": "2019-12-27T18:11:19.117Z", "pipelines": [ { "description": "description", "name": "x", "pipeline_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "preset_retrieval_parameters": { "alpha": 0, "class_name": "class_name", "dense_similarity_cutoff": 0, "dense_similarity_top_k": 1, "enable_reranking": true, "files_top_k": 1, "rerank_top_n": 1, "retrieval_mode": "chunks", "retrieve_image_nodes": true, "retrieve_page_figure_nodes": true, "retrieve_page_screenshot_nodes": true, "search_filters": { "filters": [ { "key": "key", "value": 0, "operator": "==" } ], "condition": "and" }, "search_filters_inference_schema": { "foo": { "foo": "bar" } }, "sparse_similarity_top_k": 1 } } ], "updated_at": "2019-12-27T18:11:19.117Z" } ``` ## List Retrievers `client.Retrievers.List(ctx, query) (*[]Retriever, error)` **get** `/api/v1/retrievers` List Retrievers for a project. ### Parameters - `query RetrieverListParams` - `Name param.Field[string]` - `OrganizationID param.Field[string]` - `ProjectID param.Field[string]` ### Returns - `type RetrieverListResponse []Retriever` - `ID string` Unique identifier - `Name string` A name for the retriever tool. Will default to the pipeline name if not provided. - `ProjectID string` The ID of the project this retriever resides in. - `CreatedAt Time` Creation datetime - `Pipelines []RetrieverPipeline` The pipelines this retriever uses. - `Description string` A description of the retriever tool. - `Name string` A name for the retriever tool. Will default to the pipeline name if not provided. - `PipelineID string` The ID of the pipeline this tool uses. - `PresetRetrievalParameters PresetRetrievalParamsResp` Parameters for retrieval configuration. - `Alpha float64` Alpha value for hybrid retrieval to determine the weights between dense and sparse retrieval. 0 is sparse retrieval and 1 is dense retrieval. - `ClassName string` - `DenseSimilarityCutoff float64` Minimum similarity score wrt query for retrieval - `DenseSimilarityTopK int64` Number of nodes for dense retrieval. - `EnableReranking bool` Enable reranking for retrieval - `FilesTopK int64` Number of files to retrieve (only for retrieval mode files_via_metadata and files_via_content). - `RerankTopN int64` Number of reranked nodes for returning. - `RetrievalMode RetrievalMode` The retrieval mode for the query. - `const RetrievalModeChunks RetrievalMode = "chunks"` - `const RetrievalModeFilesViaMetadata RetrievalMode = "files_via_metadata"` - `const RetrievalModeFilesViaContent RetrievalMode = "files_via_content"` - `const RetrievalModeAutoRouted RetrievalMode = "auto_routed"` - `RetrieveImageNodes bool` Whether to retrieve image nodes. - `RetrievePageFigureNodes bool` Whether to retrieve page figure nodes. - `RetrievePageScreenshotNodes bool` Whether to retrieve page screenshot nodes. - `SearchFilters MetadataFilters` Metadata filters for vector stores. - `Filters []MetadataFiltersFilterUnion` - `type MetadataFiltersFilterMetadataFilter struct{…}` 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 MetadataFiltersFilterMetadataFilterValueUnion` - `float64` - `string` - `type MetadataFiltersFilterMetadataFilterValueArray []string` - `type MetadataFiltersFilterMetadataFilterValueArray []float64` - `type MetadataFiltersFilterMetadataFilterValueArray []int64` - `Operator string` Vector store filter operator. - `const MetadataFiltersFilterMetadataFilterOperatorEquals MetadataFiltersFilterMetadataFilterOperator = "=="` - `const MetadataFiltersFilterMetadataFilterOperatorGreater MetadataFiltersFilterMetadataFilterOperator = ">"` - `const MetadataFiltersFilterMetadataFilterOperatorLess MetadataFiltersFilterMetadataFilterOperator = "<"` - `const MetadataFiltersFilterMetadataFilterOperatorNotEquals MetadataFiltersFilterMetadataFilterOperator = "!="` - `const MetadataFiltersFilterMetadataFilterOperatorGreaterOrEquals MetadataFiltersFilterMetadataFilterOperator = ">="` - `const MetadataFiltersFilterMetadataFilterOperatorLessOrEquals MetadataFiltersFilterMetadataFilterOperator = "<="` - `const MetadataFiltersFilterMetadataFilterOperatorIn MetadataFiltersFilterMetadataFilterOperator = "in"` - `const MetadataFiltersFilterMetadataFilterOperatorNin MetadataFiltersFilterMetadataFilterOperator = "nin"` - `const MetadataFiltersFilterMetadataFilterOperatorAny MetadataFiltersFilterMetadataFilterOperator = "any"` - `const MetadataFiltersFilterMetadataFilterOperatorAll MetadataFiltersFilterMetadataFilterOperator = "all"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatch MetadataFiltersFilterMetadataFilterOperator = "text_match"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatchInsensitive MetadataFiltersFilterMetadataFilterOperator = "text_match_insensitive"` - `const MetadataFiltersFilterMetadataFilterOperatorContains MetadataFiltersFilterMetadataFilterOperator = "contains"` - `const MetadataFiltersFilterMetadataFilterOperatorIsEmpty MetadataFiltersFilterMetadataFilterOperator = "is_empty"` - `type MetadataFilters struct{…}` Metadata filters for vector stores. - `Condition MetadataFiltersCondition` Vector store filter conditions to combine different filters. - `const MetadataFiltersConditionAnd MetadataFiltersCondition = "and"` - `const MetadataFiltersConditionOr MetadataFiltersCondition = "or"` - `const MetadataFiltersConditionNot MetadataFiltersCondition = "not"` - `SearchFiltersInferenceSchema map[string, PresetRetrievalParamsSearchFiltersInferenceSchemaUnionResp]` JSON Schema that will be used to infer search_filters. Omit or leave as null to skip inference. - `type PresetRetrievalParamsSearchFiltersInferenceSchemaMap map[string, any]` - `type PresetRetrievalParamsSearchFiltersInferenceSchemaArray []any` - `string` - `float64` - `bool` - `SparseSimilarityTopK int64` Number of nodes for sparse retrieval. - `UpdatedAt Time` Update datetime ### Example ```go package main import ( "context" "fmt" "github.com/stainless-sdks/llamacloud-prod-go" "github.com/stainless-sdks/llamacloud-prod-go/option" ) func main() { client := llamacloudprod.NewClient( option.WithAPIKey("My API Key"), ) retrievers, err := client.Retrievers.List(context.TODO(), llamacloudprod.RetrieverListParams{ }) if err != nil { panic(err.Error()) } fmt.Printf("%+v\n", retrievers) } ``` #### Response ```json [ { "id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "name": "x", "project_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "created_at": "2019-12-27T18:11:19.117Z", "pipelines": [ { "description": "description", "name": "x", "pipeline_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "preset_retrieval_parameters": { "alpha": 0, "class_name": "class_name", "dense_similarity_cutoff": 0, "dense_similarity_top_k": 1, "enable_reranking": true, "files_top_k": 1, "rerank_top_n": 1, "retrieval_mode": "chunks", "retrieve_image_nodes": true, "retrieve_page_figure_nodes": true, "retrieve_page_screenshot_nodes": true, "search_filters": { "filters": [ { "key": "key", "value": 0, "operator": "==" } ], "condition": "and" }, "search_filters_inference_schema": { "foo": { "foo": "bar" } }, "sparse_similarity_top_k": 1 } } ], "updated_at": "2019-12-27T18:11:19.117Z" } ] ``` ## Get Retriever `client.Retrievers.Get(ctx, retrieverID, query) (*Retriever, error)` **get** `/api/v1/retrievers/{retriever_id}` Get a Retriever by ID. ### Parameters - `retrieverID string` - `query RetrieverGetParams` - `OrganizationID param.Field[string]` - `ProjectID param.Field[string]` ### Returns - `type Retriever struct{…}` An entity that retrieves context nodes from several sub RetrieverTools. - `ID string` Unique identifier - `Name string` A name for the retriever tool. Will default to the pipeline name if not provided. - `ProjectID string` The ID of the project this retriever resides in. - `CreatedAt Time` Creation datetime - `Pipelines []RetrieverPipeline` The pipelines this retriever uses. - `Description string` A description of the retriever tool. - `Name string` A name for the retriever tool. Will default to the pipeline name if not provided. - `PipelineID string` The ID of the pipeline this tool uses. - `PresetRetrievalParameters PresetRetrievalParamsResp` Parameters for retrieval configuration. - `Alpha float64` Alpha value for hybrid retrieval to determine the weights between dense and sparse retrieval. 0 is sparse retrieval and 1 is dense retrieval. - `ClassName string` - `DenseSimilarityCutoff float64` Minimum similarity score wrt query for retrieval - `DenseSimilarityTopK int64` Number of nodes for dense retrieval. - `EnableReranking bool` Enable reranking for retrieval - `FilesTopK int64` Number of files to retrieve (only for retrieval mode files_via_metadata and files_via_content). - `RerankTopN int64` Number of reranked nodes for returning. - `RetrievalMode RetrievalMode` The retrieval mode for the query. - `const RetrievalModeChunks RetrievalMode = "chunks"` - `const RetrievalModeFilesViaMetadata RetrievalMode = "files_via_metadata"` - `const RetrievalModeFilesViaContent RetrievalMode = "files_via_content"` - `const RetrievalModeAutoRouted RetrievalMode = "auto_routed"` - `RetrieveImageNodes bool` Whether to retrieve image nodes. - `RetrievePageFigureNodes bool` Whether to retrieve page figure nodes. - `RetrievePageScreenshotNodes bool` Whether to retrieve page screenshot nodes. - `SearchFilters MetadataFilters` Metadata filters for vector stores. - `Filters []MetadataFiltersFilterUnion` - `type MetadataFiltersFilterMetadataFilter struct{…}` 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 MetadataFiltersFilterMetadataFilterValueUnion` - `float64` - `string` - `type MetadataFiltersFilterMetadataFilterValueArray []string` - `type MetadataFiltersFilterMetadataFilterValueArray []float64` - `type MetadataFiltersFilterMetadataFilterValueArray []int64` - `Operator string` Vector store filter operator. - `const MetadataFiltersFilterMetadataFilterOperatorEquals MetadataFiltersFilterMetadataFilterOperator = "=="` - `const MetadataFiltersFilterMetadataFilterOperatorGreater MetadataFiltersFilterMetadataFilterOperator = ">"` - `const MetadataFiltersFilterMetadataFilterOperatorLess MetadataFiltersFilterMetadataFilterOperator = "<"` - `const MetadataFiltersFilterMetadataFilterOperatorNotEquals MetadataFiltersFilterMetadataFilterOperator = "!="` - `const MetadataFiltersFilterMetadataFilterOperatorGreaterOrEquals MetadataFiltersFilterMetadataFilterOperator = ">="` - `const MetadataFiltersFilterMetadataFilterOperatorLessOrEquals MetadataFiltersFilterMetadataFilterOperator = "<="` - `const MetadataFiltersFilterMetadataFilterOperatorIn MetadataFiltersFilterMetadataFilterOperator = "in"` - `const MetadataFiltersFilterMetadataFilterOperatorNin MetadataFiltersFilterMetadataFilterOperator = "nin"` - `const MetadataFiltersFilterMetadataFilterOperatorAny MetadataFiltersFilterMetadataFilterOperator = "any"` - `const MetadataFiltersFilterMetadataFilterOperatorAll MetadataFiltersFilterMetadataFilterOperator = "all"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatch MetadataFiltersFilterMetadataFilterOperator = "text_match"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatchInsensitive MetadataFiltersFilterMetadataFilterOperator = "text_match_insensitive"` - `const MetadataFiltersFilterMetadataFilterOperatorContains MetadataFiltersFilterMetadataFilterOperator = "contains"` - `const MetadataFiltersFilterMetadataFilterOperatorIsEmpty MetadataFiltersFilterMetadataFilterOperator = "is_empty"` - `type MetadataFilters struct{…}` Metadata filters for vector stores. - `Condition MetadataFiltersCondition` Vector store filter conditions to combine different filters. - `const MetadataFiltersConditionAnd MetadataFiltersCondition = "and"` - `const MetadataFiltersConditionOr MetadataFiltersCondition = "or"` - `const MetadataFiltersConditionNot MetadataFiltersCondition = "not"` - `SearchFiltersInferenceSchema map[string, PresetRetrievalParamsSearchFiltersInferenceSchemaUnionResp]` JSON Schema that will be used to infer search_filters. Omit or leave as null to skip inference. - `type PresetRetrievalParamsSearchFiltersInferenceSchemaMap map[string, any]` - `type PresetRetrievalParamsSearchFiltersInferenceSchemaArray []any` - `string` - `float64` - `bool` - `SparseSimilarityTopK int64` Number of nodes for sparse retrieval. - `UpdatedAt Time` Update datetime ### Example ```go package main import ( "context" "fmt" "github.com/stainless-sdks/llamacloud-prod-go" "github.com/stainless-sdks/llamacloud-prod-go/option" ) func main() { client := llamacloudprod.NewClient( option.WithAPIKey("My API Key"), ) retriever, err := client.Retrievers.Get( context.TODO(), "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", llamacloudprod.RetrieverGetParams{ }, ) if err != nil { panic(err.Error()) } fmt.Printf("%+v\n", retriever.ID) } ``` #### Response ```json { "id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "name": "x", "project_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "created_at": "2019-12-27T18:11:19.117Z", "pipelines": [ { "description": "description", "name": "x", "pipeline_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "preset_retrieval_parameters": { "alpha": 0, "class_name": "class_name", "dense_similarity_cutoff": 0, "dense_similarity_top_k": 1, "enable_reranking": true, "files_top_k": 1, "rerank_top_n": 1, "retrieval_mode": "chunks", "retrieve_image_nodes": true, "retrieve_page_figure_nodes": true, "retrieve_page_screenshot_nodes": true, "search_filters": { "filters": [ { "key": "key", "value": 0, "operator": "==" } ], "condition": "and" }, "search_filters_inference_schema": { "foo": { "foo": "bar" } }, "sparse_similarity_top_k": 1 } } ], "updated_at": "2019-12-27T18:11:19.117Z" } ``` ## Update Retriever `client.Retrievers.Update(ctx, retrieverID, params) (*Retriever, error)` **put** `/api/v1/retrievers/{retriever_id}` Update an existing Retriever. ### Parameters - `retrieverID string` - `params RetrieverUpdateParams` - `Pipelines param.Field[[]RetrieverPipeline]` Body param: The pipelines this retriever uses. - `Description string` A description of the retriever tool. - `Name string` A name for the retriever tool. Will default to the pipeline name if not provided. - `PipelineID string` The ID of the pipeline this tool uses. - `PresetRetrievalParameters PresetRetrievalParamsResp` Parameters for retrieval configuration. - `Alpha float64` Alpha value for hybrid retrieval to determine the weights between dense and sparse retrieval. 0 is sparse retrieval and 1 is dense retrieval. - `ClassName string` - `DenseSimilarityCutoff float64` Minimum similarity score wrt query for retrieval - `DenseSimilarityTopK int64` Number of nodes for dense retrieval. - `EnableReranking bool` Enable reranking for retrieval - `FilesTopK int64` Number of files to retrieve (only for retrieval mode files_via_metadata and files_via_content). - `RerankTopN int64` Number of reranked nodes for returning. - `RetrievalMode RetrievalMode` The retrieval mode for the query. - `const RetrievalModeChunks RetrievalMode = "chunks"` - `const RetrievalModeFilesViaMetadata RetrievalMode = "files_via_metadata"` - `const RetrievalModeFilesViaContent RetrievalMode = "files_via_content"` - `const RetrievalModeAutoRouted RetrievalMode = "auto_routed"` - `RetrieveImageNodes bool` Whether to retrieve image nodes. - `RetrievePageFigureNodes bool` Whether to retrieve page figure nodes. - `RetrievePageScreenshotNodes bool` Whether to retrieve page screenshot nodes. - `SearchFilters MetadataFilters` Metadata filters for vector stores. - `Filters []MetadataFiltersFilterUnion` - `type MetadataFiltersFilterMetadataFilter struct{…}` 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 MetadataFiltersFilterMetadataFilterValueUnion` - `float64` - `string` - `type MetadataFiltersFilterMetadataFilterValueArray []string` - `type MetadataFiltersFilterMetadataFilterValueArray []float64` - `type MetadataFiltersFilterMetadataFilterValueArray []int64` - `Operator string` Vector store filter operator. - `const MetadataFiltersFilterMetadataFilterOperatorEquals MetadataFiltersFilterMetadataFilterOperator = "=="` - `const MetadataFiltersFilterMetadataFilterOperatorGreater MetadataFiltersFilterMetadataFilterOperator = ">"` - `const MetadataFiltersFilterMetadataFilterOperatorLess MetadataFiltersFilterMetadataFilterOperator = "<"` - `const MetadataFiltersFilterMetadataFilterOperatorNotEquals MetadataFiltersFilterMetadataFilterOperator = "!="` - `const MetadataFiltersFilterMetadataFilterOperatorGreaterOrEquals MetadataFiltersFilterMetadataFilterOperator = ">="` - `const MetadataFiltersFilterMetadataFilterOperatorLessOrEquals MetadataFiltersFilterMetadataFilterOperator = "<="` - `const MetadataFiltersFilterMetadataFilterOperatorIn MetadataFiltersFilterMetadataFilterOperator = "in"` - `const MetadataFiltersFilterMetadataFilterOperatorNin MetadataFiltersFilterMetadataFilterOperator = "nin"` - `const MetadataFiltersFilterMetadataFilterOperatorAny MetadataFiltersFilterMetadataFilterOperator = "any"` - `const MetadataFiltersFilterMetadataFilterOperatorAll MetadataFiltersFilterMetadataFilterOperator = "all"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatch MetadataFiltersFilterMetadataFilterOperator = "text_match"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatchInsensitive MetadataFiltersFilterMetadataFilterOperator = "text_match_insensitive"` - `const MetadataFiltersFilterMetadataFilterOperatorContains MetadataFiltersFilterMetadataFilterOperator = "contains"` - `const MetadataFiltersFilterMetadataFilterOperatorIsEmpty MetadataFiltersFilterMetadataFilterOperator = "is_empty"` - `type MetadataFilters struct{…}` Metadata filters for vector stores. - `Condition MetadataFiltersCondition` Vector store filter conditions to combine different filters. - `const MetadataFiltersConditionAnd MetadataFiltersCondition = "and"` - `const MetadataFiltersConditionOr MetadataFiltersCondition = "or"` - `const MetadataFiltersConditionNot MetadataFiltersCondition = "not"` - `SearchFiltersInferenceSchema map[string, PresetRetrievalParamsSearchFiltersInferenceSchemaUnionResp]` JSON Schema that will be used to infer search_filters. Omit or leave as null to skip inference. - `type PresetRetrievalParamsSearchFiltersInferenceSchemaMap map[string, any]` - `type PresetRetrievalParamsSearchFiltersInferenceSchemaArray []any` - `string` - `float64` - `bool` - `SparseSimilarityTopK int64` Number of nodes for sparse retrieval. - `OrganizationID param.Field[string]` Query param - `ProjectID param.Field[string]` Query param - `Name param.Field[string]` Body param: A name for the retriever. ### Returns - `type Retriever struct{…}` An entity that retrieves context nodes from several sub RetrieverTools. - `ID string` Unique identifier - `Name string` A name for the retriever tool. Will default to the pipeline name if not provided. - `ProjectID string` The ID of the project this retriever resides in. - `CreatedAt Time` Creation datetime - `Pipelines []RetrieverPipeline` The pipelines this retriever uses. - `Description string` A description of the retriever tool. - `Name string` A name for the retriever tool. Will default to the pipeline name if not provided. - `PipelineID string` The ID of the pipeline this tool uses. - `PresetRetrievalParameters PresetRetrievalParamsResp` Parameters for retrieval configuration. - `Alpha float64` Alpha value for hybrid retrieval to determine the weights between dense and sparse retrieval. 0 is sparse retrieval and 1 is dense retrieval. - `ClassName string` - `DenseSimilarityCutoff float64` Minimum similarity score wrt query for retrieval - `DenseSimilarityTopK int64` Number of nodes for dense retrieval. - `EnableReranking bool` Enable reranking for retrieval - `FilesTopK int64` Number of files to retrieve (only for retrieval mode files_via_metadata and files_via_content). - `RerankTopN int64` Number of reranked nodes for returning. - `RetrievalMode RetrievalMode` The retrieval mode for the query. - `const RetrievalModeChunks RetrievalMode = "chunks"` - `const RetrievalModeFilesViaMetadata RetrievalMode = "files_via_metadata"` - `const RetrievalModeFilesViaContent RetrievalMode = "files_via_content"` - `const RetrievalModeAutoRouted RetrievalMode = "auto_routed"` - `RetrieveImageNodes bool` Whether to retrieve image nodes. - `RetrievePageFigureNodes bool` Whether to retrieve page figure nodes. - `RetrievePageScreenshotNodes bool` Whether to retrieve page screenshot nodes. - `SearchFilters MetadataFilters` Metadata filters for vector stores. - `Filters []MetadataFiltersFilterUnion` - `type MetadataFiltersFilterMetadataFilter struct{…}` 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 MetadataFiltersFilterMetadataFilterValueUnion` - `float64` - `string` - `type MetadataFiltersFilterMetadataFilterValueArray []string` - `type MetadataFiltersFilterMetadataFilterValueArray []float64` - `type MetadataFiltersFilterMetadataFilterValueArray []int64` - `Operator string` Vector store filter operator. - `const MetadataFiltersFilterMetadataFilterOperatorEquals MetadataFiltersFilterMetadataFilterOperator = "=="` - `const MetadataFiltersFilterMetadataFilterOperatorGreater MetadataFiltersFilterMetadataFilterOperator = ">"` - `const MetadataFiltersFilterMetadataFilterOperatorLess MetadataFiltersFilterMetadataFilterOperator = "<"` - `const MetadataFiltersFilterMetadataFilterOperatorNotEquals MetadataFiltersFilterMetadataFilterOperator = "!="` - `const MetadataFiltersFilterMetadataFilterOperatorGreaterOrEquals MetadataFiltersFilterMetadataFilterOperator = ">="` - `const MetadataFiltersFilterMetadataFilterOperatorLessOrEquals MetadataFiltersFilterMetadataFilterOperator = "<="` - `const MetadataFiltersFilterMetadataFilterOperatorIn MetadataFiltersFilterMetadataFilterOperator = "in"` - `const MetadataFiltersFilterMetadataFilterOperatorNin MetadataFiltersFilterMetadataFilterOperator = "nin"` - `const MetadataFiltersFilterMetadataFilterOperatorAny MetadataFiltersFilterMetadataFilterOperator = "any"` - `const MetadataFiltersFilterMetadataFilterOperatorAll MetadataFiltersFilterMetadataFilterOperator = "all"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatch MetadataFiltersFilterMetadataFilterOperator = "text_match"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatchInsensitive MetadataFiltersFilterMetadataFilterOperator = "text_match_insensitive"` - `const MetadataFiltersFilterMetadataFilterOperatorContains MetadataFiltersFilterMetadataFilterOperator = "contains"` - `const MetadataFiltersFilterMetadataFilterOperatorIsEmpty MetadataFiltersFilterMetadataFilterOperator = "is_empty"` - `type MetadataFilters struct{…}` Metadata filters for vector stores. - `Condition MetadataFiltersCondition` Vector store filter conditions to combine different filters. - `const MetadataFiltersConditionAnd MetadataFiltersCondition = "and"` - `const MetadataFiltersConditionOr MetadataFiltersCondition = "or"` - `const MetadataFiltersConditionNot MetadataFiltersCondition = "not"` - `SearchFiltersInferenceSchema map[string, PresetRetrievalParamsSearchFiltersInferenceSchemaUnionResp]` JSON Schema that will be used to infer search_filters. Omit or leave as null to skip inference. - `type PresetRetrievalParamsSearchFiltersInferenceSchemaMap map[string, any]` - `type PresetRetrievalParamsSearchFiltersInferenceSchemaArray []any` - `string` - `float64` - `bool` - `SparseSimilarityTopK int64` Number of nodes for sparse retrieval. - `UpdatedAt Time` Update datetime ### Example ```go package main import ( "context" "fmt" "github.com/stainless-sdks/llamacloud-prod-go" "github.com/stainless-sdks/llamacloud-prod-go/option" ) func main() { client := llamacloudprod.NewClient( option.WithAPIKey("My API Key"), ) retriever, err := client.Retrievers.Update( context.TODO(), "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", llamacloudprod.RetrieverUpdateParams{ Pipelines: []llamacloudprod.RetrieverPipelineParam{llamacloudprod.RetrieverPipelineParam{ Description: llamacloudprod.String("description"), Name: llamacloudprod.String("x"), PipelineID: "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", }}, }, ) if err != nil { panic(err.Error()) } fmt.Printf("%+v\n", retriever.ID) } ``` #### Response ```json { "id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "name": "x", "project_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "created_at": "2019-12-27T18:11:19.117Z", "pipelines": [ { "description": "description", "name": "x", "pipeline_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "preset_retrieval_parameters": { "alpha": 0, "class_name": "class_name", "dense_similarity_cutoff": 0, "dense_similarity_top_k": 1, "enable_reranking": true, "files_top_k": 1, "rerank_top_n": 1, "retrieval_mode": "chunks", "retrieve_image_nodes": true, "retrieve_page_figure_nodes": true, "retrieve_page_screenshot_nodes": true, "search_filters": { "filters": [ { "key": "key", "value": 0, "operator": "==" } ], "condition": "and" }, "search_filters_inference_schema": { "foo": { "foo": "bar" } }, "sparse_similarity_top_k": 1 } } ], "updated_at": "2019-12-27T18:11:19.117Z" } ``` ## Delete Retriever `client.Retrievers.Delete(ctx, retrieverID, body) error` **delete** `/api/v1/retrievers/{retriever_id}` Delete a Retriever by ID. ### Parameters - `retrieverID string` - `body RetrieverDeleteParams` - `OrganizationID param.Field[string]` - `ProjectID param.Field[string]` ### Example ```go package main import ( "context" "github.com/stainless-sdks/llamacloud-prod-go" "github.com/stainless-sdks/llamacloud-prod-go/option" ) func main() { client := llamacloudprod.NewClient( option.WithAPIKey("My API Key"), ) err := client.Retrievers.Delete( context.TODO(), "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", llamacloudprod.RetrieverDeleteParams{ }, ) if err != nil { panic(err.Error()) } } ``` ## Direct Retrieve `client.Retrievers.Search(ctx, params) (*CompositeRetrievalResult, error)` **post** `/api/v1/retrievers/retrieve` Retrieve data using specified pipelines without creating a persistent retriever. ### Parameters - `params RetrieverSearchParams` - `Query param.Field[string]` Body param: The query to retrieve against. - `OrganizationID param.Field[string]` Query param - `ProjectID param.Field[string]` Query param - `Mode param.Field[CompositeRetrievalMode]` Body param: The mode of composite retrieval. - `Pipelines param.Field[[]RetrieverPipeline]` Body param: The pipelines to use for retrieval. - `Description string` A description of the retriever tool. - `Name string` A name for the retriever tool. Will default to the pipeline name if not provided. - `PipelineID string` The ID of the pipeline this tool uses. - `PresetRetrievalParameters PresetRetrievalParamsResp` Parameters for retrieval configuration. - `Alpha float64` Alpha value for hybrid retrieval to determine the weights between dense and sparse retrieval. 0 is sparse retrieval and 1 is dense retrieval. - `ClassName string` - `DenseSimilarityCutoff float64` Minimum similarity score wrt query for retrieval - `DenseSimilarityTopK int64` Number of nodes for dense retrieval. - `EnableReranking bool` Enable reranking for retrieval - `FilesTopK int64` Number of files to retrieve (only for retrieval mode files_via_metadata and files_via_content). - `RerankTopN int64` Number of reranked nodes for returning. - `RetrievalMode RetrievalMode` The retrieval mode for the query. - `const RetrievalModeChunks RetrievalMode = "chunks"` - `const RetrievalModeFilesViaMetadata RetrievalMode = "files_via_metadata"` - `const RetrievalModeFilesViaContent RetrievalMode = "files_via_content"` - `const RetrievalModeAutoRouted RetrievalMode = "auto_routed"` - `RetrieveImageNodes bool` Whether to retrieve image nodes. - `RetrievePageFigureNodes bool` Whether to retrieve page figure nodes. - `RetrievePageScreenshotNodes bool` Whether to retrieve page screenshot nodes. - `SearchFilters MetadataFilters` Metadata filters for vector stores. - `Filters []MetadataFiltersFilterUnion` - `type MetadataFiltersFilterMetadataFilter struct{…}` 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 MetadataFiltersFilterMetadataFilterValueUnion` - `float64` - `string` - `type MetadataFiltersFilterMetadataFilterValueArray []string` - `type MetadataFiltersFilterMetadataFilterValueArray []float64` - `type MetadataFiltersFilterMetadataFilterValueArray []int64` - `Operator string` Vector store filter operator. - `const MetadataFiltersFilterMetadataFilterOperatorEquals MetadataFiltersFilterMetadataFilterOperator = "=="` - `const MetadataFiltersFilterMetadataFilterOperatorGreater MetadataFiltersFilterMetadataFilterOperator = ">"` - `const MetadataFiltersFilterMetadataFilterOperatorLess MetadataFiltersFilterMetadataFilterOperator = "<"` - `const MetadataFiltersFilterMetadataFilterOperatorNotEquals MetadataFiltersFilterMetadataFilterOperator = "!="` - `const MetadataFiltersFilterMetadataFilterOperatorGreaterOrEquals MetadataFiltersFilterMetadataFilterOperator = ">="` - `const MetadataFiltersFilterMetadataFilterOperatorLessOrEquals MetadataFiltersFilterMetadataFilterOperator = "<="` - `const MetadataFiltersFilterMetadataFilterOperatorIn MetadataFiltersFilterMetadataFilterOperator = "in"` - `const MetadataFiltersFilterMetadataFilterOperatorNin MetadataFiltersFilterMetadataFilterOperator = "nin"` - `const MetadataFiltersFilterMetadataFilterOperatorAny MetadataFiltersFilterMetadataFilterOperator = "any"` - `const MetadataFiltersFilterMetadataFilterOperatorAll MetadataFiltersFilterMetadataFilterOperator = "all"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatch MetadataFiltersFilterMetadataFilterOperator = "text_match"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatchInsensitive MetadataFiltersFilterMetadataFilterOperator = "text_match_insensitive"` - `const MetadataFiltersFilterMetadataFilterOperatorContains MetadataFiltersFilterMetadataFilterOperator = "contains"` - `const MetadataFiltersFilterMetadataFilterOperatorIsEmpty MetadataFiltersFilterMetadataFilterOperator = "is_empty"` - `type MetadataFilters struct{…}` Metadata filters for vector stores. - `Condition MetadataFiltersCondition` Vector store filter conditions to combine different filters. - `const MetadataFiltersConditionAnd MetadataFiltersCondition = "and"` - `const MetadataFiltersConditionOr MetadataFiltersCondition = "or"` - `const MetadataFiltersConditionNot MetadataFiltersCondition = "not"` - `SearchFiltersInferenceSchema map[string, PresetRetrievalParamsSearchFiltersInferenceSchemaUnionResp]` JSON Schema that will be used to infer search_filters. Omit or leave as null to skip inference. - `type PresetRetrievalParamsSearchFiltersInferenceSchemaMap map[string, any]` - `type PresetRetrievalParamsSearchFiltersInferenceSchemaArray []any` - `string` - `float64` - `bool` - `SparseSimilarityTopK int64` Number of nodes for sparse retrieval. - `RerankConfig param.Field[ReRankConfig]` Body param: The rerank configuration for composite retrieval. - `RerankTopN param.Field[int64]` Body param: (use rerank_config.top_n instead) The number of nodes to retrieve after reranking over retrieved nodes from all retrieval tools. ### Returns - `type CompositeRetrievalResult struct{…}` - `ImageNodes []PageScreenshotNodeWithScore` The image nodes retrieved by the pipeline for the given query. Deprecated - will soon be replaced with 'page_screenshot_nodes'. - `Node PageScreenshotNodeWithScoreNode` - `FileID string` The ID of the file that the page screenshot was taken from - `ImageSize int64` The size of the image in bytes - `PageIndex int64` The index of the page for which the screenshot is taken (0-indexed) - `Metadata map[string, any]` Metadata for the screenshot - `Score float64` The score of the screenshot node - `ClassName string` - `Nodes []CompositeRetrievalResultNode` The retrieved nodes from the composite retrieval. - `Node CompositeRetrievalResultNodeNode` - `ID string` The ID of the retrieved node. - `EndCharIdx int64` The end character index of the retrieved node in the document - `PipelineID string` The ID of the pipeline this node was retrieved from. - `RetrieverID string` The ID of the retriever this node was retrieved from. - `RetrieverPipelineName string` The name of the retrieval pipeline this node was retrieved from. - `StartCharIdx int64` The start character index of the retrieved node in the document - `Text string` The text of the retrieved node. - `Metadata map[string, any]` Metadata associated with the retrieved node. - `ClassName string` - `Score float64` - `PageFigureNodes []PageFigureNodeWithScore` The page figure nodes retrieved by the pipeline for the given query. - `Node PageFigureNodeWithScoreNode` - `Confidence float64` The confidence of the figure - `FigureName string` The name of the figure - `FigureSize int64` The size of the figure in bytes - `FileID string` The ID of the file that the figure was taken from - `PageIndex int64` The index of the page for which the figure is taken (0-indexed) - `IsLikelyNoise bool` Whether the figure is likely to be noise - `Metadata map[string, any]` Metadata for the figure - `Score float64` The score of the figure node - `ClassName string` ### Example ```go package main import ( "context" "fmt" "github.com/stainless-sdks/llamacloud-prod-go" "github.com/stainless-sdks/llamacloud-prod-go/option" ) func main() { client := llamacloudprod.NewClient( option.WithAPIKey("My API Key"), ) compositeRetrievalResult, err := client.Retrievers.Search(context.TODO(), llamacloudprod.RetrieverSearchParams{ Query: "x", }) if err != nil { panic(err.Error()) } fmt.Printf("%+v\n", compositeRetrievalResult.ImageNodes) } ``` #### Response ```json { "image_nodes": [ { "node": { "file_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "image_size": 0, "page_index": 0, "metadata": { "foo": "bar" } }, "score": 0, "class_name": "class_name" } ], "nodes": [ { "node": { "id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "end_char_idx": 0, "pipeline_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "retriever_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "retriever_pipeline_name": "retriever_pipeline_name", "start_char_idx": 0, "text": "text", "metadata": { "foo": "bar" } }, "class_name": "class_name", "score": 0 } ], "page_figure_nodes": [ { "node": { "confidence": 0, "figure_name": "figure_name", "figure_size": 0, "file_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "page_index": 0, "is_likely_noise": true, "metadata": { "foo": "bar" } }, "score": 0, "class_name": "class_name" } ] } ``` ## Domain Types ### Composite Retrieval Mode - `type CompositeRetrievalMode string` Enum for the mode of composite retrieval. - `const CompositeRetrievalModeRouting CompositeRetrievalMode = "routing"` - `const CompositeRetrievalModeFull CompositeRetrievalMode = "full"` ### Composite Retrieval Result - `type CompositeRetrievalResult struct{…}` - `ImageNodes []PageScreenshotNodeWithScore` The image nodes retrieved by the pipeline for the given query. Deprecated - will soon be replaced with 'page_screenshot_nodes'. - `Node PageScreenshotNodeWithScoreNode` - `FileID string` The ID of the file that the page screenshot was taken from - `ImageSize int64` The size of the image in bytes - `PageIndex int64` The index of the page for which the screenshot is taken (0-indexed) - `Metadata map[string, any]` Metadata for the screenshot - `Score float64` The score of the screenshot node - `ClassName string` - `Nodes []CompositeRetrievalResultNode` The retrieved nodes from the composite retrieval. - `Node CompositeRetrievalResultNodeNode` - `ID string` The ID of the retrieved node. - `EndCharIdx int64` The end character index of the retrieved node in the document - `PipelineID string` The ID of the pipeline this node was retrieved from. - `RetrieverID string` The ID of the retriever this node was retrieved from. - `RetrieverPipelineName string` The name of the retrieval pipeline this node was retrieved from. - `StartCharIdx int64` The start character index of the retrieved node in the document - `Text string` The text of the retrieved node. - `Metadata map[string, any]` Metadata associated with the retrieved node. - `ClassName string` - `Score float64` - `PageFigureNodes []PageFigureNodeWithScore` The page figure nodes retrieved by the pipeline for the given query. - `Node PageFigureNodeWithScoreNode` - `Confidence float64` The confidence of the figure - `FigureName string` The name of the figure - `FigureSize int64` The size of the figure in bytes - `FileID string` The ID of the file that the figure was taken from - `PageIndex int64` The index of the page for which the figure is taken (0-indexed) - `IsLikelyNoise bool` Whether the figure is likely to be noise - `Metadata map[string, any]` Metadata for the figure - `Score float64` The score of the figure node - `ClassName string` ### Re Rank Config - `type ReRankConfig struct{…}` - `TopN int64` The number of nodes to retrieve after reranking over retrieved nodes from all retrieval tools. - `Type ReRankConfigType` The type of reranker to use. - `const ReRankConfigTypeSystemDefault ReRankConfigType = "system_default"` - `const ReRankConfigTypeLlm ReRankConfigType = "llm"` - `const ReRankConfigTypeCohere ReRankConfigType = "cohere"` - `const ReRankConfigTypeBedrock ReRankConfigType = "bedrock"` - `const ReRankConfigTypeScore ReRankConfigType = "score"` - `const ReRankConfigTypeDisabled ReRankConfigType = "disabled"` ### Retriever - `type Retriever struct{…}` An entity that retrieves context nodes from several sub RetrieverTools. - `ID string` Unique identifier - `Name string` A name for the retriever tool. Will default to the pipeline name if not provided. - `ProjectID string` The ID of the project this retriever resides in. - `CreatedAt Time` Creation datetime - `Pipelines []RetrieverPipeline` The pipelines this retriever uses. - `Description string` A description of the retriever tool. - `Name string` A name for the retriever tool. Will default to the pipeline name if not provided. - `PipelineID string` The ID of the pipeline this tool uses. - `PresetRetrievalParameters PresetRetrievalParamsResp` Parameters for retrieval configuration. - `Alpha float64` Alpha value for hybrid retrieval to determine the weights between dense and sparse retrieval. 0 is sparse retrieval and 1 is dense retrieval. - `ClassName string` - `DenseSimilarityCutoff float64` Minimum similarity score wrt query for retrieval - `DenseSimilarityTopK int64` Number of nodes for dense retrieval. - `EnableReranking bool` Enable reranking for retrieval - `FilesTopK int64` Number of files to retrieve (only for retrieval mode files_via_metadata and files_via_content). - `RerankTopN int64` Number of reranked nodes for returning. - `RetrievalMode RetrievalMode` The retrieval mode for the query. - `const RetrievalModeChunks RetrievalMode = "chunks"` - `const RetrievalModeFilesViaMetadata RetrievalMode = "files_via_metadata"` - `const RetrievalModeFilesViaContent RetrievalMode = "files_via_content"` - `const RetrievalModeAutoRouted RetrievalMode = "auto_routed"` - `RetrieveImageNodes bool` Whether to retrieve image nodes. - `RetrievePageFigureNodes bool` Whether to retrieve page figure nodes. - `RetrievePageScreenshotNodes bool` Whether to retrieve page screenshot nodes. - `SearchFilters MetadataFilters` Metadata filters for vector stores. - `Filters []MetadataFiltersFilterUnion` - `type MetadataFiltersFilterMetadataFilter struct{…}` 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 MetadataFiltersFilterMetadataFilterValueUnion` - `float64` - `string` - `type MetadataFiltersFilterMetadataFilterValueArray []string` - `type MetadataFiltersFilterMetadataFilterValueArray []float64` - `type MetadataFiltersFilterMetadataFilterValueArray []int64` - `Operator string` Vector store filter operator. - `const MetadataFiltersFilterMetadataFilterOperatorEquals MetadataFiltersFilterMetadataFilterOperator = "=="` - `const MetadataFiltersFilterMetadataFilterOperatorGreater MetadataFiltersFilterMetadataFilterOperator = ">"` - `const MetadataFiltersFilterMetadataFilterOperatorLess MetadataFiltersFilterMetadataFilterOperator = "<"` - `const MetadataFiltersFilterMetadataFilterOperatorNotEquals MetadataFiltersFilterMetadataFilterOperator = "!="` - `const MetadataFiltersFilterMetadataFilterOperatorGreaterOrEquals MetadataFiltersFilterMetadataFilterOperator = ">="` - `const MetadataFiltersFilterMetadataFilterOperatorLessOrEquals MetadataFiltersFilterMetadataFilterOperator = "<="` - `const MetadataFiltersFilterMetadataFilterOperatorIn MetadataFiltersFilterMetadataFilterOperator = "in"` - `const MetadataFiltersFilterMetadataFilterOperatorNin MetadataFiltersFilterMetadataFilterOperator = "nin"` - `const MetadataFiltersFilterMetadataFilterOperatorAny MetadataFiltersFilterMetadataFilterOperator = "any"` - `const MetadataFiltersFilterMetadataFilterOperatorAll MetadataFiltersFilterMetadataFilterOperator = "all"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatch MetadataFiltersFilterMetadataFilterOperator = "text_match"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatchInsensitive MetadataFiltersFilterMetadataFilterOperator = "text_match_insensitive"` - `const MetadataFiltersFilterMetadataFilterOperatorContains MetadataFiltersFilterMetadataFilterOperator = "contains"` - `const MetadataFiltersFilterMetadataFilterOperatorIsEmpty MetadataFiltersFilterMetadataFilterOperator = "is_empty"` - `type MetadataFilters struct{…}` Metadata filters for vector stores. - `Condition MetadataFiltersCondition` Vector store filter conditions to combine different filters. - `const MetadataFiltersConditionAnd MetadataFiltersCondition = "and"` - `const MetadataFiltersConditionOr MetadataFiltersCondition = "or"` - `const MetadataFiltersConditionNot MetadataFiltersCondition = "not"` - `SearchFiltersInferenceSchema map[string, PresetRetrievalParamsSearchFiltersInferenceSchemaUnionResp]` JSON Schema that will be used to infer search_filters. Omit or leave as null to skip inference. - `type PresetRetrievalParamsSearchFiltersInferenceSchemaMap map[string, any]` - `type PresetRetrievalParamsSearchFiltersInferenceSchemaArray []any` - `string` - `float64` - `bool` - `SparseSimilarityTopK int64` Number of nodes for sparse retrieval. - `UpdatedAt Time` Update datetime ### Retriever Create - `type RetrieverCreate struct{…}` - `Name string` A name for the retriever tool. Will default to the pipeline name if not provided. - `Pipelines []RetrieverPipeline` The pipelines this retriever uses. - `Description string` A description of the retriever tool. - `Name string` A name for the retriever tool. Will default to the pipeline name if not provided. - `PipelineID string` The ID of the pipeline this tool uses. - `PresetRetrievalParameters PresetRetrievalParamsResp` Parameters for retrieval configuration. - `Alpha float64` Alpha value for hybrid retrieval to determine the weights between dense and sparse retrieval. 0 is sparse retrieval and 1 is dense retrieval. - `ClassName string` - `DenseSimilarityCutoff float64` Minimum similarity score wrt query for retrieval - `DenseSimilarityTopK int64` Number of nodes for dense retrieval. - `EnableReranking bool` Enable reranking for retrieval - `FilesTopK int64` Number of files to retrieve (only for retrieval mode files_via_metadata and files_via_content). - `RerankTopN int64` Number of reranked nodes for returning. - `RetrievalMode RetrievalMode` The retrieval mode for the query. - `const RetrievalModeChunks RetrievalMode = "chunks"` - `const RetrievalModeFilesViaMetadata RetrievalMode = "files_via_metadata"` - `const RetrievalModeFilesViaContent RetrievalMode = "files_via_content"` - `const RetrievalModeAutoRouted RetrievalMode = "auto_routed"` - `RetrieveImageNodes bool` Whether to retrieve image nodes. - `RetrievePageFigureNodes bool` Whether to retrieve page figure nodes. - `RetrievePageScreenshotNodes bool` Whether to retrieve page screenshot nodes. - `SearchFilters MetadataFilters` Metadata filters for vector stores. - `Filters []MetadataFiltersFilterUnion` - `type MetadataFiltersFilterMetadataFilter struct{…}` 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 MetadataFiltersFilterMetadataFilterValueUnion` - `float64` - `string` - `type MetadataFiltersFilterMetadataFilterValueArray []string` - `type MetadataFiltersFilterMetadataFilterValueArray []float64` - `type MetadataFiltersFilterMetadataFilterValueArray []int64` - `Operator string` Vector store filter operator. - `const MetadataFiltersFilterMetadataFilterOperatorEquals MetadataFiltersFilterMetadataFilterOperator = "=="` - `const MetadataFiltersFilterMetadataFilterOperatorGreater MetadataFiltersFilterMetadataFilterOperator = ">"` - `const MetadataFiltersFilterMetadataFilterOperatorLess MetadataFiltersFilterMetadataFilterOperator = "<"` - `const MetadataFiltersFilterMetadataFilterOperatorNotEquals MetadataFiltersFilterMetadataFilterOperator = "!="` - `const MetadataFiltersFilterMetadataFilterOperatorGreaterOrEquals MetadataFiltersFilterMetadataFilterOperator = ">="` - `const MetadataFiltersFilterMetadataFilterOperatorLessOrEquals MetadataFiltersFilterMetadataFilterOperator = "<="` - `const MetadataFiltersFilterMetadataFilterOperatorIn MetadataFiltersFilterMetadataFilterOperator = "in"` - `const MetadataFiltersFilterMetadataFilterOperatorNin MetadataFiltersFilterMetadataFilterOperator = "nin"` - `const MetadataFiltersFilterMetadataFilterOperatorAny MetadataFiltersFilterMetadataFilterOperator = "any"` - `const MetadataFiltersFilterMetadataFilterOperatorAll MetadataFiltersFilterMetadataFilterOperator = "all"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatch MetadataFiltersFilterMetadataFilterOperator = "text_match"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatchInsensitive MetadataFiltersFilterMetadataFilterOperator = "text_match_insensitive"` - `const MetadataFiltersFilterMetadataFilterOperatorContains MetadataFiltersFilterMetadataFilterOperator = "contains"` - `const MetadataFiltersFilterMetadataFilterOperatorIsEmpty MetadataFiltersFilterMetadataFilterOperator = "is_empty"` - `type MetadataFilters struct{…}` Metadata filters for vector stores. - `Condition MetadataFiltersCondition` Vector store filter conditions to combine different filters. - `const MetadataFiltersConditionAnd MetadataFiltersCondition = "and"` - `const MetadataFiltersConditionOr MetadataFiltersCondition = "or"` - `const MetadataFiltersConditionNot MetadataFiltersCondition = "not"` - `SearchFiltersInferenceSchema map[string, PresetRetrievalParamsSearchFiltersInferenceSchemaUnionResp]` JSON Schema that will be used to infer search_filters. Omit or leave as null to skip inference. - `type PresetRetrievalParamsSearchFiltersInferenceSchemaMap map[string, any]` - `type PresetRetrievalParamsSearchFiltersInferenceSchemaArray []any` - `string` - `float64` - `bool` - `SparseSimilarityTopK int64` Number of nodes for sparse retrieval. ### Retriever Pipeline - `type RetrieverPipeline struct{…}` - `Description string` A description of the retriever tool. - `Name string` A name for the retriever tool. Will default to the pipeline name if not provided. - `PipelineID string` The ID of the pipeline this tool uses. - `PresetRetrievalParameters PresetRetrievalParamsResp` Parameters for retrieval configuration. - `Alpha float64` Alpha value for hybrid retrieval to determine the weights between dense and sparse retrieval. 0 is sparse retrieval and 1 is dense retrieval. - `ClassName string` - `DenseSimilarityCutoff float64` Minimum similarity score wrt query for retrieval - `DenseSimilarityTopK int64` Number of nodes for dense retrieval. - `EnableReranking bool` Enable reranking for retrieval - `FilesTopK int64` Number of files to retrieve (only for retrieval mode files_via_metadata and files_via_content). - `RerankTopN int64` Number of reranked nodes for returning. - `RetrievalMode RetrievalMode` The retrieval mode for the query. - `const RetrievalModeChunks RetrievalMode = "chunks"` - `const RetrievalModeFilesViaMetadata RetrievalMode = "files_via_metadata"` - `const RetrievalModeFilesViaContent RetrievalMode = "files_via_content"` - `const RetrievalModeAutoRouted RetrievalMode = "auto_routed"` - `RetrieveImageNodes bool` Whether to retrieve image nodes. - `RetrievePageFigureNodes bool` Whether to retrieve page figure nodes. - `RetrievePageScreenshotNodes bool` Whether to retrieve page screenshot nodes. - `SearchFilters MetadataFilters` Metadata filters for vector stores. - `Filters []MetadataFiltersFilterUnion` - `type MetadataFiltersFilterMetadataFilter struct{…}` 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 MetadataFiltersFilterMetadataFilterValueUnion` - `float64` - `string` - `type MetadataFiltersFilterMetadataFilterValueArray []string` - `type MetadataFiltersFilterMetadataFilterValueArray []float64` - `type MetadataFiltersFilterMetadataFilterValueArray []int64` - `Operator string` Vector store filter operator. - `const MetadataFiltersFilterMetadataFilterOperatorEquals MetadataFiltersFilterMetadataFilterOperator = "=="` - `const MetadataFiltersFilterMetadataFilterOperatorGreater MetadataFiltersFilterMetadataFilterOperator = ">"` - `const MetadataFiltersFilterMetadataFilterOperatorLess MetadataFiltersFilterMetadataFilterOperator = "<"` - `const MetadataFiltersFilterMetadataFilterOperatorNotEquals MetadataFiltersFilterMetadataFilterOperator = "!="` - `const MetadataFiltersFilterMetadataFilterOperatorGreaterOrEquals MetadataFiltersFilterMetadataFilterOperator = ">="` - `const MetadataFiltersFilterMetadataFilterOperatorLessOrEquals MetadataFiltersFilterMetadataFilterOperator = "<="` - `const MetadataFiltersFilterMetadataFilterOperatorIn MetadataFiltersFilterMetadataFilterOperator = "in"` - `const MetadataFiltersFilterMetadataFilterOperatorNin MetadataFiltersFilterMetadataFilterOperator = "nin"` - `const MetadataFiltersFilterMetadataFilterOperatorAny MetadataFiltersFilterMetadataFilterOperator = "any"` - `const MetadataFiltersFilterMetadataFilterOperatorAll MetadataFiltersFilterMetadataFilterOperator = "all"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatch MetadataFiltersFilterMetadataFilterOperator = "text_match"` - `const MetadataFiltersFilterMetadataFilterOperatorTextMatchInsensitive MetadataFiltersFilterMetadataFilterOperator = "text_match_insensitive"` - `const MetadataFiltersFilterMetadataFilterOperatorContains MetadataFiltersFilterMetadataFilterOperator = "contains"` - `const MetadataFiltersFilterMetadataFilterOperatorIsEmpty MetadataFiltersFilterMetadataFilterOperator = "is_empty"` - `type MetadataFilters struct{…}` Metadata filters for vector stores. - `Condition MetadataFiltersCondition` Vector store filter conditions to combine different filters. - `const MetadataFiltersConditionAnd MetadataFiltersCondition = "and"` - `const MetadataFiltersConditionOr MetadataFiltersCondition = "or"` - `const MetadataFiltersConditionNot MetadataFiltersCondition = "not"` - `SearchFiltersInferenceSchema map[string, PresetRetrievalParamsSearchFiltersInferenceSchemaUnionResp]` JSON Schema that will be used to infer search_filters. Omit or leave as null to skip inference. - `type PresetRetrievalParamsSearchFiltersInferenceSchemaMap map[string, any]` - `type PresetRetrievalParamsSearchFiltersInferenceSchemaArray []any` - `string` - `float64` - `bool` - `SparseSimilarityTopK int64` Number of nodes for sparse retrieval. # Retriever ## Retrieve `client.Retrievers.Retriever.Search(ctx, retrieverID, params) (*CompositeRetrievalResult, error)` **post** `/api/v1/retrievers/{retriever_id}/retrieve` Retrieve data using a Retriever. ### Parameters - `retrieverID string` - `params RetrieverRetrieverSearchParams` - `Query param.Field[string]` Body param: The query to retrieve against. - `OrganizationID param.Field[string]` Query param - `ProjectID param.Field[string]` Query param - `Mode param.Field[CompositeRetrievalMode]` Body param: The mode of composite retrieval. - `RerankConfig param.Field[ReRankConfig]` Body param: The rerank configuration for composite retrieval. - `RerankTopN param.Field[int64]` Body param: (use rerank_config.top_n instead) The number of nodes to retrieve after reranking over retrieved nodes from all retrieval tools. ### Returns - `type CompositeRetrievalResult struct{…}` - `ImageNodes []PageScreenshotNodeWithScore` The image nodes retrieved by the pipeline for the given query. Deprecated - will soon be replaced with 'page_screenshot_nodes'. - `Node PageScreenshotNodeWithScoreNode` - `FileID string` The ID of the file that the page screenshot was taken from - `ImageSize int64` The size of the image in bytes - `PageIndex int64` The index of the page for which the screenshot is taken (0-indexed) - `Metadata map[string, any]` Metadata for the screenshot - `Score float64` The score of the screenshot node - `ClassName string` - `Nodes []CompositeRetrievalResultNode` The retrieved nodes from the composite retrieval. - `Node CompositeRetrievalResultNodeNode` - `ID string` The ID of the retrieved node. - `EndCharIdx int64` The end character index of the retrieved node in the document - `PipelineID string` The ID of the pipeline this node was retrieved from. - `RetrieverID string` The ID of the retriever this node was retrieved from. - `RetrieverPipelineName string` The name of the retrieval pipeline this node was retrieved from. - `StartCharIdx int64` The start character index of the retrieved node in the document - `Text string` The text of the retrieved node. - `Metadata map[string, any]` Metadata associated with the retrieved node. - `ClassName string` - `Score float64` - `PageFigureNodes []PageFigureNodeWithScore` The page figure nodes retrieved by the pipeline for the given query. - `Node PageFigureNodeWithScoreNode` - `Confidence float64` The confidence of the figure - `FigureName string` The name of the figure - `FigureSize int64` The size of the figure in bytes - `FileID string` The ID of the file that the figure was taken from - `PageIndex int64` The index of the page for which the figure is taken (0-indexed) - `IsLikelyNoise bool` Whether the figure is likely to be noise - `Metadata map[string, any]` Metadata for the figure - `Score float64` The score of the figure node - `ClassName string` ### Example ```go package main import ( "context" "fmt" "github.com/stainless-sdks/llamacloud-prod-go" "github.com/stainless-sdks/llamacloud-prod-go/option" ) func main() { client := llamacloudprod.NewClient( option.WithAPIKey("My API Key"), ) compositeRetrievalResult, err := client.Retrievers.Retriever.Search( context.TODO(), "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", llamacloudprod.RetrieverRetrieverSearchParams{ Query: "x", }, ) if err != nil { panic(err.Error()) } fmt.Printf("%+v\n", compositeRetrievalResult.ImageNodes) } ``` #### Response ```json { "image_nodes": [ { "node": { "file_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "image_size": 0, "page_index": 0, "metadata": { "foo": "bar" } }, "score": 0, "class_name": "class_name" } ], "nodes": [ { "node": { "id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "end_char_idx": 0, "pipeline_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "retriever_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "retriever_pipeline_name": "retriever_pipeline_name", "start_char_idx": 0, "text": "text", "metadata": { "foo": "bar" } }, "class_name": "class_name", "score": 0 } ], "page_figure_nodes": [ { "node": { "confidence": 0, "figure_name": "figure_name", "figure_size": 0, "file_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "page_index": 0, "is_likely_noise": true, "metadata": { "foo": "bar" } }, "score": 0, "class_name": "class_name" } ] } ```