---
title: "POST /v1/documents/query/"
method: POST
path: "/v1/documents/query/"
tags: ["query"]
---

# POST /v1/documents/query/

`POST /v1/documents/query/`

## Request

- Base URL: `https://api.ai.sakura.ad.jp`
- URL: `https://api.ai.sakura.ad.jp/v1/documents/query/`
- Auth: HTTP bearer
- TypeScript: <https://skmtc.dev/sakura/apis/sakura-ai-engine-rag-api/docs/v1/documents/query/post.ts> (a function with typed inputs; its response is checked against the schema)

## Query parameters

- `model` string
- `name` string
- `tag` string

## Request body

- QueryRequest
  - `model` string: クエリのベクトル化に利用するモデル。
  - `query` string, required
  - `tags` string[]: すべてのタグを持つドキュメントのみ対象。
  - `top_k` integer: 返す検索結果の最大件数。
  - `threshold` number, double: ベクトル距離のしきい値。この值よりも距離が大きいドキュメントは検索結果から除外されます。
  - `distance_type` 'cosine' | 'l2': * `cosine` - cosine * `l2` - l2

## Response `200`

- PaginatedQueryResultChunkList
  - `results` QueryResultChunk[], required
    - `document` DocumentList, required
      - `id` string, uuid, required
      - `created_at` string, date-time, required
      - `status` 'pending' | 'processing' | 'available' | 'deleted' | 'error', required: * `pending` - Pending * `processing` - Processing * `available` - Available * `deleted` - Deleted * `error` - Error
      - `name` string, required
      - `model` string, required
      - `chunk_size` integer, required
      - `chunk_count` integer, required
      - `tags` string[]
      - `error_message` string, required
    - `chunk_index` integer, required
    - `distance` number, double, required
    - `content` string, required
    - `metadata` object, required

---

[API](https://skmtc.dev/sakura/apis/sakura-ai-engine-rag-api.md) - [All operations](https://skmtc.dev/sakura/apis/sakura-ai-engine-rag-api/llms.txt) - [OpenAPI document](https://skmtc.dev/sakura/apis/sakura-ai-engine-rag-api/revisions/229dfe3a3f2a?raw)