POST /v2/chat

Default value: "application/json"

The name of the project that is making the request.

Defaults to false.

When true, the response will be a SSE stream of events.

Streaming is beneficial for user interfaces that render the contents of the response piece by piece, as it gets generated.

Ensures that only the top k most likely tokens are considered for generation at each step. When k is set to 0, k-sampling is disabled. Defaults to 0, min value of 0, max value of 500.

Default value: 0

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 and documents parameters.

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

Note: command-r7b-12-2024 and newer models only support "CONTEXTUAL" and "STRICT" modes.

Valid values:

• "CONTEXTUAL"
• false
• "STRICT"

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.

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.

Default value: 0.75

A list of tools (functions) available to the model. The model response may contain 'tool_calls' to the specified tools.

Learn more in the Tool Use guide.

The function to be executed.

The name of the function.

The description of the function.

The parameters of the function as a JSON schema.

Valid values:

• "function"

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.

Used to control whether or not the model will be forced to use a tool when answering. When REQUIRED is specified, the model will be forced to use at least one of the user-defined tools, and the tools parameter must be passed in the request. When NONE is specified, the model will be forced not to use one of the specified tools, and give a direct response. If tool_choice isn't specified, then the model is free to choose whether to use the specified tools or not.

Note: This parameter is only compatible with models Command-r7b and newer.

Valid values:

• "REQUIRED"
• "NONE"

The name of a compatible Cohere model or the ID of a fine-tuned model.

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.

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.

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.

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.

When set to true, tool calls in the Assistant message will be forced to follow the tool definition strictly. Learn more in the Structured Outputs (Tools) guide.

Note: The first few requests with a new set of tools will take longer to process.

Options for controlling citation generation.

Defaults to "accurate". Dictates the approach taken to generating citations as part of the RAG flow by allowing the user to specify whether they want "accurate" results, "fast" results or no results.

Note: command-r7b-12-2024 and command-a-03-2025 only support "fast" and "off" modes. The default is "fast".

Valid values:

• "ACCURATE"
• false
• "FAST"

Configuration for reasoning features.

The maximum number of tokens the model can use for thinking, which must be set to a positive integer. The model will stop thinking if it reaches the thinking token budget and will proceed with the response.

Reasoning is enabled by default for models that support it, but can be turned off by setting "type": "disabled".

Valid values:

• "disabled"
• "enabled"

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.

The maximum number of output tokens the model will generate in the response. If not set, max_tokens defaults to the model's maximum output token limit. You can find the maximum output token limits for each model in the model documentation.

Note: Setting a low value may result in incomplete generations. In such cases, the finish_reason field in the response will be set to "MAX_TOKENS".

Note: If max_tokens is set higher than the model's maximum output token limit, the generation will be capped at that model-specific maximum limit.

Defaults to false. When set to true, the log probabilities of the generated tokens will be included in the response.

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.