Send LLMMessage to Mistral API

Usage

mistral_chat(
  .llm,
  .model = "mistral-large-latest",
  .frequency_penalty = NULL,
  .logit_bias = NULL,
  .presence_penalty = NULL,
  .seed = NULL,
  .stop = NULL,
  .stream = FALSE,
  .temperature = 0.7,
  .top_p = 1,
  .min_tokens = NULL,
  .max_tokens = NULL,
  .json_schema = NULL,
  .safe_prompt = FALSE,
  .timeout = 120,
  .max_tries = 3,
  .dry_run = FALSE,
  .verbose = FALSE,
  .tools = NULL,
  .tool_choice = NULL
)

Arguments

.llm: An LLMMessage object.
.model: The model identifier to use (default: "mistral-large-latest").
.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.
.min_tokens: The minimum number of tokens to generate in the completion. Must be >= 0 (optional).
.max_tokens: An upper bound for the number of tokens that can be generated for a completion.
.json_schema: A JSON schema object provided by tidyllm schema or ellmer schemata.
.safe_prompt: Whether to inject a safety prompt before all conversations (default: FALSE).
.timeout: When should our connection time out in seconds (default: 120).
.max_tries: Maximum retries to peform request
.dry_run: If TRUE, perform a dry run and return the request object (default: FALSE).
.verbose: Should additional information be shown after the API call? (default: FALSE)
.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

Returns an updated LLMMessage object.