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Create an Anthropic Message Batch

Source: R/anthropic_batch_api.R
anthropic_create_batch.Rd

This is a thin wrapper around Anthropic's /v1/messages/batches endpoint. It accepts a list of request objects (each with custom_id and params) and returns the resulting Message Batch object.

Usage

anthropic_create_batch(
  requests,
  api_key = Sys.getenv("ANTHROPIC_API_KEY"),
  anthropic_version = "2023-06-01"
)

Arguments

requests

List of request objects, each of the form list(custom_id = <chr>, params = <list>). You can obtain this list from the output of build_anthropic_batch_requests via split / Map, or use run_anthropic_batch_pipeline.

api_key

Optional Anthropic API key. Defaults to Sys.getenv("ANTHROPIC_API_KEY").

anthropic_version

Anthropic API version string passed as the anthropic-version HTTP header. Defaults to "2023-06-01".

Value

A list representing the Message Batch object returned by Anthropic. Important fields include id, processing_status, request_counts, and (after completion) results_url.

Details

Typically you will not call this directly; instead, use run_anthropic_batch_pipeline which builds requests from a tibble of pairs, creates the batch, polls for completion, and downloads the results.

See also

llm_submit_pairs_batch(), llm_download_batch_results()

Other batch backends: anthropic_download_batch_results(), anthropic_get_batch(), anthropic_poll_batch_until_complete(), build_anthropic_batch_requests(), build_gemini_batch_requests(), build_openai_batch_requests(), gemini_create_batch(), gemini_download_batch_results(), gemini_get_batch(), gemini_poll_batch_until_complete(), llm_download_batch_results(), llm_resume_multi_batches(), llm_submit_pairs_batch(), llm_submit_pairs_multi_batch(), openai_create_batch(), openai_download_batch_errors(), openai_download_batch_output(), openai_get_batch(), openai_poll_batch_until_complete(), openai_upload_batch_file(), run_anthropic_batch_pipeline(), run_gemini_batch_pipeline(), run_openai_batch_pipeline(), write_openai_batch_file()

Examples

if (FALSE) { # \dontrun{
# Requires ANTHROPIC_API_KEY and network access.
library(pairwiseLLM)

data("example_writing_samples", package = "pairwiseLLM")

pairs <- example_writing_samples |>
  make_pairs() |>
  sample_pairs(n_pairs = 2, seed = 123) |>
  randomize_pair_order(seed = 456)

td <- trait_description("overall_quality")
tmpl <- set_prompt_template()

req_tbl <- build_anthropic_batch_requests(
  pairs             = pairs,
  model             = "claude-sonnet-4-5",
  trait_name        = td$name,
  trait_description = td$description,
  prompt_template   = tmpl
)

requests <- lapply(seq_len(nrow(req_tbl)), function(i) {
  list(
    custom_id = req_tbl$custom_id[i],
    params    = req_tbl$params[[i]]
  )
})

batch <- anthropic_create_batch(requests = requests)
batch$id
batch$processing_status
} # }