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v1

latestOpenAPI 3.1.02026-07-2675394318.9 KB
inference

Create chat completion

Creates a model response for the given chat conversation.

post/v1/chat/completions

Query parameters

ai_project_idstring nullable

current project ID

current project ID

Request body

modelstring required

ID of the model to use.

storeboolean nullable

Whether or not to store the output of this chat completion request for use in our model distillation.

max_tokensinteger nullable

The maximum number of tokens that can be generated in the completion.

The token count of your prompt plus max_tokens cannot exceed the model's context length. Example Python code for counting tokens.

If omitted or set to null, defaults to 8192 tokens.

max_completion_tokensinteger nullable

An upper bound for the number of tokens that can be generated for a completion, including visible output tokens and reasoning tokens.

temperaturenumber nullable

What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.

We generally recommend altering this or top_p but not both.

top_pnumber nullable

An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.

We generally recommend altering this or temperature but not both.

ninteger nullable

How many completions to generate for each prompt.

Note: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for max_tokens and stop.

streamboolean nullable

If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message. Example Python code.

stream_optionsobject nullable

If set to {"include_usage": True}, usage stats will be sent with the last chunk of dataExample Python code

stopstring[] nullable

Up to 4 sequences where the API will stop generating further tokens.

presence_penaltynumber nullable

Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far,increasing the model's likelihood to talk about new topics.

See more information about frequency and presence penalties.

frequency_penaltynumber nullable

Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.

See more information about frequency and presence penalties.

logit_biasobject nullable

Modify the likelihood of specified tokens appearing in the completion.

Accepts a JSON object that maps tokens (specified by their token ID in the GPT tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.

As an example, you can pass {"50256": -100} to prevent the token from being generated.

logprobsboolean nullable

Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the content of message.

top_logprobsinteger nullable

An non-negative integer specifying the number of most likely tokens to return at each token position, each with an associated log probability. logprobs must be set to true if this parameter is used.

userstring nullable

A unique identifier representing your end-user, which can help us to monitor and detect abuse. Learn more.

extra_bodyobject nullable

To provide extra parameters.

service_tier'auto' | 'default' | 'over-limit' | 'flex' | 'no-limit'

Represents the service tier for requests.

Attributes: Auto: Automatically choose the best available tier for the request (Default or OverLimit). Analyze response to determine which tier was used. Default: Return 429 errors on hitting the rate limit, do not exceed to the OverLimit tier. OverLimit: Indicate that the request was over the user limit. This tier cannot be set by user in the request, but us used in a response for tier=Auto. Flex: Do not consume rate-limit credits, but run with lower priority. May still result in 429 errors in case of if there is no resources to process.

Example request

{
  "model": "meta-llama/Meta-Llama-3.1-70B-Instruct",
  "messages": [
    {
      "content": "Hello!",
      "role": "user"
    }
  ],
  "max_tokens": 100,
  "max_completion_tokens": 100
}

Response

OK

OR