The send_batch() function allows you to send a list of LLMMessage objects
to an API.
It routes the input to the appropriate provider-specific batch API function.
Usage
send_batch(
.llms,
.provider = getOption("tidyllm_sbatch_default"),
.dry_run = NULL,
.temperature = NULL,
.timeout = NULL,
.top_p = NULL,
.max_tries = NULL,
.model = NULL,
.verbose = NULL,
.json_schema = NULL,
.seed = NULL,
.stop = NULL,
.frequency_penalty = NULL,
.presence_penalty = NULL,
.id_prefix = NULL
)Arguments
- .llms
A list of
LLMMessageobjects containing conversation histories.- .provider
A function or function call specifying the language model provider and any additional parameters. This should be a call to a provider function like
openai(),claude(), etc. You can also set a default provider function via thetidyllm_sbatch_defaultoption.- .dry_run
Logical; if
TRUE, simulates the request without sending it to the provider. Useful for testing.- .temperature
Numeric; controls the randomness of the model's output (0 = deterministic).
- .timeout
Numeric; the maximum time (in seconds) to wait for a response.
- .top_p
Numeric; nucleus sampling parameter, which limits the sampling to the top cumulative probability
p.- .max_tries
Integer; the maximum number of retries for failed requests.
- .model
Character; the model identifier to use (e.g.,
"gpt-4").- .verbose
Logical; if
TRUE, prints additional information about the request and response.- .json_schema
List; A JSON schema object as R list to enforce the output structure
- .seed
Integer; sets a random seed for reproducibility.
- .stop
Character vector; specifies sequences where the model should stop generating further tokens.
- .frequency_penalty
Numeric; adjusts the likelihood of repeating tokens (positive values decrease repetition).
- .presence_penalty
Numeric; adjusts the likelihood of introducing new tokens (positive values encourage novelty).
- .id_prefix
Character string to specify a prefix for generating custom IDs when names in
.llmsare missing