Chat

POST

Generates a message from the model in response to a provided conversation. To learn more about the features of the Chat API follow our Text Generation guides.

Follow the Migration Guide for instructions on moving from API v1 to API v2.

Headers

X-Client-NamestringOptional

The name of the project that is making the request.

Request

This endpoint expects an object.
modelstringRequired

The name of a compatible Cohere model (such as command-r or command-r-plus) or the ID of a fine-tuned model.

messageslist of objectsRequired

A list of chat messages in chronological order, representing a conversation between the user and the model.

Messages can be from User, Assistant, Tool and System roles. Learn more about messages and roles in the Chat API guide.

streamfalseRequired
toolslist of objectsOptional

A list of available tools (functions) that the model may suggest invoking before producing a text response.

When tools is passed (without tool_results), the text content in the response will be empty and the tool_calls field in the response will be populated with a list of tool calls that need to be made. If no calls need to be made, the tool_calls array will be empty.

documentslist of strings or objectsOptional

A list of relevant documents that the model can cite to generate a more accurate reply. Each document is either a string or document object with content and metadata.

citation_optionsobjectOptional

Options for controlling citation generation.

response_formatobjectOptional

Configuration for forcing the model output to adhere to the specified format. Supported on Command R, Command R+ and newer models.

The model can be forced into outputting JSON objects by setting { "type": "json_object" }.

A JSON Schema can optionally be provided, to ensure a specific structure.

Note: When using { "type": "json_object" } your message should always explicitly instruct the model to generate a JSON (eg: “Generate a JSON …”) . Otherwise the model may end up getting stuck generating an infinite stream of characters and eventually run out of context length.

Note: When json_schema is not specified, the generated object can have up to 5 layers of nesting.

Limitation: The parameter is not supported when used in combinations with the documents or tools parameters.

safety_modeenumOptional
Allowed values: CONTEXTUALSTRICTOFF

Used to select the safety instruction inserted into the prompt. Defaults to CONTEXTUAL. When OFF is specified, the safety instruction will be omitted.

Safety modes are not yet configurable in combination with tools, tool_results and documents parameters.

Note: This parameter is only compatible with models Command R 08-2024, Command R+ 08-2024 and newer.

max_tokensintegerOptional

The maximum number of tokens the model will generate as part of the response.

Note: Setting a low value may result in incomplete generations.

stop_sequenceslist of stringsOptional

A list of up to 5 strings that the model will use to stop generation. If the model generates a string that matches any of the strings in the list, it will stop generating tokens and return the generated text up to that point not including the stop sequence.

temperaturedoubleOptional

Defaults to 0.3.

A non-negative float that tunes the degree of randomness in generation. Lower temperatures mean less random generations, and higher temperatures mean more random generations.

Randomness can be further maximized by increasing the value of the p parameter.

seedintegerOptional

If specified, the backend will make a best effort to sample tokens deterministically, such that repeated requests with the same seed and parameters should return the same result. However, determinism cannot be totally guaranteed.

frequency_penaltydoubleOptional

Defaults to 0.0, min value of 0.0, max value of 1.0. Used to reduce repetitiveness of generated tokens. The higher the value, the stronger a penalty is applied to previously present tokens, proportional to how many times they have already appeared in the prompt or prior generation.

presence_penaltydoubleOptional

Defaults to 0.0, min value of 0.0, max value of 1.0. Used to reduce repetitiveness of generated tokens. Similar to frequency_penalty, except that this penalty is applied equally to all tokens that have already appeared, regardless of their exact frequencies.

kdoubleOptional

Ensures only the top k most likely tokens are considered for generation at each step. Defaults to 0, min value of 0, max value of 500.

pdoubleOptional

Ensures that only the most likely tokens, with total probability mass of p, are considered for generation at each step. If both k and p are enabled, p acts after k. Defaults to 0.75. min value of 0.01, max value of 0.99.

Response

This endpoint returns an object.
idstring

Unique identifier for the generated reply. Useful for submitting feedback.

finish_reasonenum
Allowed values: COMPLETESTOP_SEQUENCEMAX_TOKENSTOOL_CALLERROR

The reason a chat request has finished.

  • complete: The model finished sending a complete message.
  • max_tokens: The number of generated tokens exceeded the model’s context length or the value specified via the max_tokens parameter.
  • stop_sequence: One of the provided stop_sequence entries was reached in the model’s generation.
  • tool_call: The model generated a Tool Call and is expecting a Tool Message in return
  • error: The generation failed due to an internal error
messageobjectOptional

A message from the assistant role can contain text and tool call information.

usageobjectOptional