## Direct Retrieve `client.retrievers.search(RetrieverSearchParamsparams, RequestOptionsoptions?): CompositeRetrievalResult` **post** `/api/v1/retrievers/retrieve` Retrieve data using specified pipelines without creating a persistent retriever. ### Parameters - `params: RetrieverSearchParams` - `query: string` Body param: The query to retrieve against. - `organization_id?: string | null` Query param - `project_id?: string | null` Query param - `mode?: CompositeRetrievalMode` Body param: The mode of composite retrieval. - `"routing"` - `"full"` - `pipelines?: Array` Body param: The pipelines to use for retrieval. - `description: string | null` A description of the retriever tool. - `name: string | null` A name for the retriever tool. Will default to the pipeline name if not provided. - `pipeline_id: string` The ID of the pipeline this tool uses. - `preset_retrieval_parameters?: PresetRetrievalParams` 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. - `class_name?: string` - `dense_similarity_cutoff?: number | null` Minimum similarity score wrt query for retrieval - `dense_similarity_top_k?: number | null` Number of nodes for dense retrieval. - `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). - `rerank_top_n?: number | null` Number of reranked nodes for returning. - `retrieval_mode?: RetrievalMode` The retrieval mode for the query. - `"chunks"` - `"files_via_metadata"` - `"files_via_content"` - `"auto_routed"` - `retrieve_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 | null` Metadata filters for vector stores. - `filters: Array` - `MetadataFilter` 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 | 2 more | null` - `number` - `string` - `Array` - `Array` - `Array` - `operator?: "==" | ">" | "<" | 11 more` Vector store filter operator. - `"=="` - `">"` - `"<"` - `"!="` - `">="` - `"<="` - `"in"` - `"nin"` - `"any"` - `"all"` - `"text_match"` - `"text_match_insensitive"` - `"contains"` - `"is_empty"` - `MetadataFilters` Metadata filters for vector stores. - `condition?: "and" | "or" | "not" | null` Vector store filter conditions to combine different filters. - `"and"` - `"or"` - `"not"` - `search_filters_inference_schema?: Record | Array | string | 2 more | null> | null` JSON Schema that will be used to infer search_filters. Omit or leave as null to skip inference. - `Record` - `Array` - `string` - `number` - `boolean` - `sparse_similarity_top_k?: number | null` Number of nodes for sparse retrieval. - `rerank_config?: ReRankConfig` Body param: The rerank configuration for composite retrieval. - `top_n?: number` The number of nodes to retrieve after reranking over retrieved nodes from all retrieval tools. - `type?: "system_default" | "llm" | "cohere" | 3 more` The type of reranker to use. - `"system_default"` - `"llm"` - `"cohere"` - `"bedrock"` - `"score"` - `"disabled"` - `rerank_top_n?: number | null` Body param: (use rerank_config.top_n instead) The number of nodes to retrieve after reranking over retrieved nodes from all retrieval tools. ### Returns - `CompositeRetrievalResult` - `image_nodes?: Array` The image nodes retrieved by the pipeline for the given query. Deprecated - will soon be replaced with 'page_screenshot_nodes'. - `node: Node` - `file_id: string` The ID of the file that the page screenshot was taken from - `image_size: number` The size of the image in bytes - `page_index: number` The index of the page for which the screenshot is taken (0-indexed) - `metadata?: Record | null` Metadata for the screenshot - `score: number` The score of the screenshot node - `class_name?: string` - `nodes?: Array` The retrieved nodes from the composite retrieval. - `node: Node` - `id: string` The ID of the retrieved node. - `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. - `retriever_id: string` The ID of the retriever this node was retrieved from. - `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` Metadata associated with the retrieved node. - `class_name?: string` - `score?: number | null` - `page_figure_nodes?: Array` The page figure nodes retrieved by the pipeline for the given query. - `node: Node` - `confidence: number` The confidence of the figure - `figure_name: string` The name of the figure - `figure_size: number` The size of the figure in bytes - `file_id: string` The ID of the file that the figure was taken from - `page_index: number` The index of the page for which the figure is taken (0-indexed) - `is_likely_noise?: boolean` Whether the figure is likely to be noise - `metadata?: Record | null` Metadata for the figure - `score: number` The score of the figure node - `class_name?: string` ### Example ```typescript import LlamaCloud from '@llamaindex/llama-cloud'; const client = new LlamaCloud({ apiKey: process.env['LLAMA_CLOUD_API_KEY'], // This is the default and can be omitted }); const compositeRetrievalResult = await client.retrievers.search({ query: 'x' }); console.log(compositeRetrievalResult.image_nodes); ``` #### 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" } ] } ```