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Send LLM Messages to an Azure OpenAI Chat Completions endpoint

Source: R/api_azure_openai.R
azure_openai_chat.Rd

This function sends a message history to the Azure OpenAI Chat Completions API and returns the assistant's reply.

Usage

azure_openai_chat(
  .llm,
  .endpoint_url = Sys.getenv("AZURE_ENDPOINT_URL"),
  .deployment = "gpt-4o-mini",
  .api_version = "2024-08-01-preview",
  .max_completion_tokens = NULL,
  .reasoning_effort = NULL,
  .frequency_penalty = NULL,
  .logit_bias = NULL,
  .presence_penalty = NULL,
  .seed = NULL,
  .stop = NULL,
  .stream = FALSE,
  .temperature = NULL,
  .top_p = NULL,
  .timeout = 60,
  .verbose = FALSE,
  .json_schema = NULL,
  .max_tries = 3,
  .dry_run = FALSE,
  .logprobs = NULL,
  .top_logprobs = NULL,
  .tools = NULL,
  .tool_choice = NULL
)

Arguments

.llm

An LLMMessage object containing the conversation history.

.endpoint_url

Base URL for the API (default: Sys.getenv("AZURE_ENDPOINT_URL")).

.deployment

The identifier of the model that is deployed (default: "gpt-4o-mini").

.api_version

Which version of the API is deployed (default: "2024-08-01-preview").

.max_completion_tokens

An upper bound for the number of tokens that can be generated for a completion.

.reasoning_effort

How long should reasoning models reason (can either be "low","medium" or "high").

.frequency_penalty

Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency.

.logit_bias

A named list modifying the likelihood of specified tokens appearing in the completion.

.presence_penalty

Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far.

.seed

If specified, the system will make a best effort to sample deterministically.

.stop

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

.stream

If set to TRUE, the answer will be streamed to console as it comes (default: FALSE).

.temperature

What sampling temperature to use, between 0 and 2. Higher values make the output more random.

.top_p

An alternative to sampling with temperature, called nucleus sampling.

.timeout

Request timeout in seconds (default: 60).

.verbose

Should additional information be shown after the API call (default: FALSE).

.json_schema

A JSON schema object provided by tidyllm schema or ellmer schemata.

.max_tries

Maximum retries to perform request.

.dry_run

If TRUE, perform a dry run and return the request object (default: FALSE).

.logprobs

If TRUE, get the log probabilities of each output token (default: NULL).

.top_logprobs

If specified, get the top N log probabilities of each output token (0-5, default: NULL).

.tools

Either a single TOOL object or a list of TOOL objects representing the available functions for tool calls.

.tool_choice

A character string specifying the tool-calling behavior; valid values are "none", "auto", or "required".

Value

A new LLMMessage object containing the original messages plus the assistant's response.