---
title: "Create Retriever"
method: POST
path: "/api/v1/retrievers"
tags: ["Retrievers"]
---

# Create Retriever

`POST /api/v1/retrievers`

Create a new Retriever.

## Query parameters

- `project_id` string, uuid, nullable
- `organization_id` string, uuid, nullable

## Cookies

- `session` string, nullable

## Request body

- RetrieverCreate
  - `name` string, required — A name for the retriever tool. Will default to the pipeline name if not provided.
  - `pipelines` RetrieverPipeline[] — The pipelines this retriever uses.
    - `name` string, nullable, required — A name for the retriever tool. Will default to the pipeline name if not provided.
    - `description` string, nullable, required — A description of the retriever tool.
    - `pipeline_id` string, uuid, required — The ID of the pipeline this tool uses.
    - `preset_retrieval_parameters` PresetRetrievalParams — Schema for the search params for an retrieval execution that can be preset for a pipeline.
      - `dense_similarity_top_k` integer, nullable — Number of nodes for dense retrieval.
      - `dense_similarity_cutoff` number, nullable — Minimum similarity score wrt query for retrieval
      - `sparse_similarity_top_k` integer, nullable — Number of nodes for sparse retrieval.
      - `enable_reranking` boolean, nullable — Enable reranking for retrieval
      - `rerank_top_n` integer, nullable — Number of reranked nodes for returning.
      - `alpha` number, nullable — Alpha value for hybrid retrieval to determine the weights between dense and sparse retrieval. 0 is sparse retrieval and 1 is dense retrieval.
      - `search_filters` MetadataFilters — Metadata filters for vector stores.
        - `filters` union[], required
          - union
            - 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
              - …
            - MetadataFilters — recursive
        - `condition` 'and' | 'or' | 'not' — Vector store filter conditions to combine different filters.
      - `search_filters_inference_schema` object, nullable — JSON Schema that will be used to infer search_filters. Omit or leave as null to skip inference.
      - `files_top_k` integer, nullable — Number of files to retrieve (only for retrieval mode files_via_metadata and files_via_content).
      - `retrieval_mode` 'chunks' | 'files_via_metadata' | 'files_via_content' | 'auto_routed'
      - `retrieve_image_nodes` boolean — Whether to retrieve image nodes.
      - `retrieve_page_screenshot_nodes` boolean — Whether to retrieve page screenshot nodes.
      - `retrieve_page_figure_nodes` boolean — Whether to retrieve page figure nodes.
      - `class_name` string

## Response `200`

Successful Response

- Retriever — An entity that retrieves context nodes from several sub RetrieverTools.
  - `name` string, required — A name for the retriever tool. Will default to the pipeline name if not provided.
  - `pipelines` RetrieverPipeline[] — The pipelines this retriever uses.
    - `name` string, nullable, required — A name for the retriever tool. Will default to the pipeline name if not provided.
    - `description` string, nullable, required — A description of the retriever tool.
    - `pipeline_id` string, uuid, required — The ID of the pipeline this tool uses.
    - `preset_retrieval_parameters` PresetRetrievalParams — Schema for the search params for an retrieval execution that can be preset for a pipeline.
      - `dense_similarity_top_k` integer, nullable — Number of nodes for dense retrieval.
      - `dense_similarity_cutoff` number, nullable — Minimum similarity score wrt query for retrieval
      - `sparse_similarity_top_k` integer, nullable — Number of nodes for sparse retrieval.
      - `enable_reranking` boolean, nullable — Enable reranking for retrieval
      - `rerank_top_n` integer, nullable — Number of reranked nodes for returning.
      - `alpha` number, nullable — Alpha value for hybrid retrieval to determine the weights between dense and sparse retrieval. 0 is sparse retrieval and 1 is dense retrieval.
      - `search_filters` MetadataFilters — Metadata filters for vector stores.
        - `filters` union[], required
          - union
            - 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
              - …
            - MetadataFilters — recursive
        - `condition` 'and' | 'or' | 'not' — Vector store filter conditions to combine different filters.
      - `search_filters_inference_schema` object, nullable — JSON Schema that will be used to infer search_filters. Omit or leave as null to skip inference.
      - `files_top_k` integer, nullable — Number of files to retrieve (only for retrieval mode files_via_metadata and files_via_content).
      - `retrieval_mode` 'chunks' | 'files_via_metadata' | 'files_via_content' | 'auto_routed'
      - `retrieve_image_nodes` boolean — Whether to retrieve image nodes.
      - `retrieve_page_screenshot_nodes` boolean — Whether to retrieve page screenshot nodes.
      - `retrieve_page_figure_nodes` boolean — Whether to retrieve page figure nodes.
      - `class_name` string
  - `id` string, uuid, required — Unique identifier
  - `created_at` string, date-time, nullable — Creation datetime
  - `updated_at` string, date-time, nullable — Update datetime
  - `project_id` string, uuid, required — The ID of the project this retriever resides in.

## Other responses

- `422` — Validation Error

---

[API](https://skmtc.net/run-llama/apis/llama-platform.md) · [All operations](https://skmtc.net/run-llama/apis/llama-platform/llms.txt) · [OpenAPI document](https://skmtc-service-staging.skmtc.workers.dev/v1/apis/run-llama/llama-platform/versions/b17341164de9/schema)