---
title: "Create an embedding"
method: POST
path: "/genai/{connection_id}/embedding"
tags: ["genai", "embedding"]
---

# Create an embedding

`POST /genai/{connection_id}/embedding`

## Path parameters

- `connection_id` string, required

## Query parameters

- `fields` string[]
- `raw` string

## Request body

- GenaiEmbedding
  - `model_id` string
  - `content` GenaiEmbeddingContent[]
    - `text` string, required
  - `enconding_format` 'FLOAT' | 'UINT8' | 'INT8' | 'BINARY' | 'UBINARY' | 'BASE64'
  - `type` string
  - `dimension` number
  - `max_tokens` number
  - `embeddings` string
  - `tokens_used` number
  - `raw` object
  - `id` string

## Response `200`

Successful

- GenaiEmbedding
  - `model_id` string
  - `content` GenaiEmbeddingContent[]
    - `text` string, required
  - `enconding_format` 'FLOAT' | 'UINT8' | 'INT8' | 'BINARY' | 'UBINARY' | 'BASE64'
  - `type` string
  - `dimension` number
  - `max_tokens` number
  - `embeddings` string
  - `tokens_used` number
  - `raw` object
  - `id` string

---

[API](https://skmtc.net/unified/apis/unified-to-api.md) · [All operations](https://skmtc.net/unified/apis/unified-to-api/llms.txt) · [OpenAPI document](https://skmtc-service-staging.skmtc.workers.dev/v1/apis/unified/unified-to-api/versions/1f72720916e4/schema)