# Create Contextualized Embeddings

POST

/

v1

/

contextualizedembeddings

Create Contextualized Embeddings

```
curl --request POST \
  --url https://api.perplexity.ai/v1/contextualizedembeddings \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "input": [
    [
      "<string>"
    ]
  ]
}
'
```

:::code-group
```title="200"
{
  "object": "list",
  "data": [
    {
      "object": "list",
      "index": 123,
      "data": [
        {
          "object": "embedding",
          "index": 123,
          "embedding": "<string>"
        }
      ]
    }
  ],
  "model": "<string>",
  "usage": {
    "prompt_tokens": 123,
    "total_tokens": 123,
    "cost": {
      "input_cost": 123,
      "total_cost": 123,
      "currency": "USD"
    }
  }
}
```

```title="422"
{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>"
    }
  ]
}
```
:::

#### Authorizations

Authorization

string

header

required

Bearer authentication header of the form `Bearer <token>`, where `<token>` is your auth token.

#### Body

application/json

Request body for creating contextualized embeddings

input

string\[]\[]

required

Nested array structure where each inner array contains chunks from a single document. Chunks within the same document are encoded with document-level context awareness. Maximum 512 documents. Total chunks across all documents must not exceed 16,000. Total tokens per document must not exceed 32K. All chunks in a single request must not exceed 120,000 tokens combined. Empty strings are not allowed.

Required array length: `1 - 512` elements

Minimum array length: `1`

Minimum string length: `1`

model

enum\<string>

required

The contextualized embedding model to use

Available options:

`pplx-embed-context-v1-0.6b`,

`pplx-embed-context-v1-4b`

dimensions

integer

Number of dimensions for output embeddings (Matryoshka). Range: 128-1024 for pplx-embed-context-v1-0.6b, 128-2560 for pplx-embed-context-v1-4b. Defaults to full dimensions (1024 or 2560).

Required range: `128 <= x <= 2560`

encoding\_format

enum\<string>

default\:base64\_int8

Output encoding format for embeddings. base64\_int8 returns base64-encoded signed int8 values. base64\_binary returns base64-encoded packed binary (1 bit per dimension).

Available options:

`base64_int8`,

`base64_binary`

#### Response

Successful Response

Response body for contextualized embeddings request

object

string

The object type

Example:

`"list"`

data

Contextualized Embedding Object · object\[]

List of contextualized embedding objects

:::accordion{title="Show child attributes"}
:::

model

string

The model used to generate embeddings

usage

Embeddings Usage · object

Token usage for the embeddings request

:::accordion{title="Show child attributes"}
:::

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## Related pages

- [Admin & Management](./admin-management-index.md)
- [Agent API](./agent-api-2-index.md)
- [Agent API](./agent-api-index.md)
- [Analytics API](./analytics-api-index.md)
- [Authentication](./authentication-index.md)
- [Changelog](../changelog.md)
- [Cookbook](./cookbook-2-index.md)
- [Embeddings API](./embeddings-api-2-index.md)
- [Embeddings API](./embeddings-api-index.md)
- [Getting Started](./getting-started-index.md)

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