call_llm_broadcast {LLMR} | R Documentation |
Parallel API calls: Fixed Config, Multiple Messages
Description
Broadcasts different messages using the same configuration in parallel.
Perfect for batch processing different prompts with consistent settings.
This function requires setting up the parallel environment using setup_llm_parallel
.
Usage
call_llm_broadcast(config, messages, ...)
Arguments
config |
Single llm_config object to use for all calls. |
messages |
A character vector (each element is a prompt) OR a list where each element is a pre-formatted message list. |
... |
Additional arguments passed to |
Value
A tibble with columns: message_index (metadata), provider, model, all model parameters, response_text, raw_response_json, success, error_message.
Parallel Workflow
All parallel functions require the future
backend to be configured.
The recommended workflow is:
Call
setup_llm_parallel()
once at the start of your script.Run one or more parallel experiments (e.g.,
call_llm_broadcast()
).Call
reset_llm_parallel()
at the end to restore sequential processing.
See Also
setup_llm_parallel
, reset_llm_parallel
Examples
## Not run:
# Broadcast different questions
config <- llm_config(provider = "openai", model = "gpt-4.1-nano",
api_key = Sys.getenv("OPENAI_API_KEY"))
messages <- list(
list(list(role = "user", content = "What is 2+2?")),
list(list(role = "user", content = "What is 3*5?")),
list(list(role = "user", content = "What is 10/2?"))
)
setup_llm_parallel(workers = 4, verbose = TRUE)
results <- call_llm_broadcast(config, messages)
reset_llm_parallel(verbose = TRUE)
## End(Not run)