LAlangdock
Chat

Creates a model response for the given chat conversation.

Changed on
post/openai/{region}/v1/chat/completions

Request

  • Base URL
    https://api.langdock.com
  • URL
    https://api.langdock.com/openai/{region}/v1/chat/completions
  • Auth
    HTTP bearer

Path parameters

region'eu' | 'us' | 'global' | 'ch' required

The region of the API to use.

Request body

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 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.

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 integer between 0 and 20 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.

max_tokensinteger nullable

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

The total length of input tokens and generated tokens is limited by the model's context length. Example Python code for counting 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.

seedinteger nullable

This feature is in Beta. If specified, OpenAI's system will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.

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.

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.

reasoning_effort'none' | 'minimal' | 'low' | 'medium' | 'high' | 'xhigh' nullable

Constrains how much effort the model spends on reasoning before responding. Lower values produce faster, cheaper responses; higher values produce more thorough reasoning. Supported values are none, minimal, low, medium, high, and xhigh. Not all values are supported by all models.

userstring

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

Example request

{
  "response_format": {
    "type": "json_object"
  },
  "temperature": 1,
  "top_p": 1,
  "user": "user-1234"
}

Response

OK

idstring required

A unique identifier for the chat completion.

createdinteger required

The Unix timestamp (in seconds) of when the chat completion was created.

modelstring required

The model used for the chat completion.

system_fingerprintstring

This fingerprint represents the backend configuration that the model runs with.

Can be used in conjunction with the seed request parameter to understand when backend changes have been made that might impact determinism.

object'chat.completion' required

The object type, which is always chat.completion.

Changes