---
title: "Classify"
method: POST
path: "/v1/classify"
deprecated: true
---

# Classify

`POST /v1/classify`

> **Deprecated.**

This endpoint makes a prediction about which label fits the specified text inputs best. To make a prediction, Classify uses the provided `examples` of text + label pairs as a reference.
Note: [Fine-tuned models](https://docs.cohere.com/docs/classify-fine-tuning) trained on classification examples don't require the `examples` parameter to be passed in explicitly.

## Headers

- `X-Client-Name` string

## Request body

- object
  - `inputs` string[], required — A list of up to 96 texts to be classified. Each one must be a non-empty string. There is, however, no consistent, universal limit to the length a particular input can be. We perform classification on the first `x` tokens of each input, and `x` varies depending on which underlying model is powering classification. The maximum token length for each model is listed in the "max tokens" column [here](https://docs.cohere.com/docs/models). Note: by default the `truncate` parameter is set to `END`, so tokens exceeding the limit will be automatically dropped. This behavior can be disabled by setting `truncate` to `NONE`, which will result in validation errors for longer texts.
  - `examples` ClassifyExample[] — An array of examples to provide context to the model. Each example is a text string and its associated label/class. Each unique label requires at least 2 examples associated with it; the maximum number of examples is 2500, and each example has a maximum length of 512 tokens. The values should be structured as `{text: "...",label: "..."}`. Note: [Fine-tuned Models](https://docs.cohere.com/docs/classify-fine-tuning) trained on classification examples don't require the `examples` parameter to be passed in explicitly.
    - `text` string
    - `label` string
  - `model` string — ID of a [Fine-tuned](https://docs.cohere.com/v2/docs/classify-starting-the-training) Classify model
  - `preset` string — The ID of a custom playground preset. You can create presets in the [playground](https://dashboard.cohere.com/playground). If you use a preset, all other parameters become optional, and any included parameters will override the preset's parameters.
  - `truncate` 'NONE' | 'START' | 'END' — One of `NONE|START|END` to specify how the API will handle inputs longer than the maximum token length. Passing `START` will discard the start of the input. `END` will discard the end of the input. In both cases, input is discarded until the remaining input is exactly the maximum input token length for the model. If `NONE` is selected, when the input exceeds the maximum input token length an error will be returned.

## Response `200`

OK

- object
  - `id` string, required
  - `classifications` object[], required
    - `id` string, required
    - `input` string — The input text that was classified
    - `prediction` string — The predicted label for the associated query (only filled for single-label models)
    - `predictions` string[], required — An array containing the predicted labels for the associated query (only filled for single-label classification)
    - `confidence` number, float — The confidence score for the top predicted class (only filled for single-label classification)
    - `confidences` number[], required — An array containing the confidence scores of all the predictions in the same order
    - `labels` object, required — A map containing each label and its confidence score according to the classifier. All the confidence scores add up to 1 for single-label classification. For multi-label classification the label confidences are independent of each other, so they don't have to sum up to 1.
    - `classification_type` 'single-label' | 'multi-label', required — The type of classification performed
  - `meta` ApiMeta
    - `api_version` object
      - `version` string, required
      - `is_deprecated` boolean
      - `is_experimental` boolean
    - `billed_units` object
      - `images` number — The number of billed images.
      - `input_tokens` number — The number of billed input tokens.
      - `image_tokens` number — The number of billed image tokens.
      - `output_tokens` number — The number of billed output tokens.
      - `search_units` number — The number of billed search units.
      - `classifications` number — The number of billed classifications units.
    - `tokens` object
      - `input_tokens` number — The number of tokens used as input to the model.
      - `output_tokens` number — The number of tokens produced by the model.
    - `cached_tokens` number — The number of prompt tokens that hit the inference cache.
    - `warnings` string[]

## Other responses

- `400` — This error is returned when the request is not well formed. This could be because: - JSON is invalid - The request is missing required fields - The request contains an invalid combination of fields
- `401` — This error indicates that the operation attempted to be performed is not allowed. This could be because: - The api token is invalid - The user does not have the necessary permissions
- `403` — This error indicates that the operation attempted to be performed is not allowed. This could be because: - The api token is invalid - The user does not have the necessary permissions
- `404` — This error is returned when a resource is not found. This could be because: - The endpoint does not exist - The resource does not exist eg model id, dataset id
- `422` — This error is returned when the request is not well formed. This could be because: - JSON is invalid - The request is missing required fields - The request contains an invalid combination of fields
- `429` — Too many requests
- `498` — This error is returned when a request or response contains a deny-listed token.
- `499` — This error is returned when a request is cancelled by the user.
- `500` — This error is returned when an uncategorised internal server error occurs.
- `501` — This error is returned when the requested feature is not implemented.
- `503` — This error is returned when the service is unavailable. This could be due to: - Too many users trying to access the service at the same time
- `504` — This error is returned when a request to the server times out. This could be due to: - An internal services taking too long to respond

---

[API](https://skmtc.net/cohere-ai/apis/api-reference.md) · [All operations](https://skmtc.net/cohere-ai/apis/api-reference/llms.txt) · [OpenAPI document](https://skmtc-service-staging.skmtc.workers.dev/v1/apis/cohere-ai/api-reference/versions/dbed69eda210/schema)