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Repair failed chapter simulation units

Source: R/repair_run_ai_on_chapters.R
repair_run_ai_on_chapters.Rd

Reads a saved result (or accepts one in memory), reruns retryable failed simulation units, and returns a copy with those units replaced. Permanent Azure content-policy failures are retained without being retried. The source file is never modified; inspect the result and call saveRDS() yourself.

Usage

repair_run_ai_on_chapters(
  x,
  book_texts,
  groups,
  context_text,
  question_text,
  output_mode = c("structured", "text"),
  temperature = NULL,
  seed = 42,
  model = NULL,
  integration = getOption("nalanda.integration"),
  virtual_key = getOption("nalanda.virtual_key"),
  base_url = getOption("nalanda.base_url"),
  excerpt_chars = 200,
  on_error = c("stop", "skip")
)

Arguments

x

A result from run_ai_on_chapters() or a path to its .Rds file.

book_texts

A single character (one chapter) or a nested list of books -> chapters as returned by read_book_texts().

groups

Character vector of group labels (length >= 2). These are the groups being compared. Example: c("Democrat", "Republican").

context_text

Character. Either:

  • A scalar template containing {identity}, which will be expanded once for each group (e.g., "You are simulating an American adult who politically identifies as a {identity}."), or

  • A character vector of length equal to length(groups), where each element is the full context for the corresponding group identity.

question_text

Character scalar. A question template containing the placeholder {group}, which will be replaced with each group label. Example: "On a scale from 0 to 100, how warmly do you feel towards {group}s?"

output_mode

Character. "structured" (default) uses the backend's structured-output support. "text" is a compatibility mode for models that do not support structured outputs (for example some Anthropic models): nalanda appends strict JSON-only instructions to the prompt, calls the model as free text, then parses the JSON back into the same fields used by the rest of the pipeline. Text mode is best-effort and stores the original model reply in raw_response.

temperature

Numeric. Sampling temperature passed to the chat backend.

seed

Integer. Random seed for reproducibility (incremented for each simulation).

model

Character. Model name for the chat backend (for example, "gemini-2.5-flash-lite"). The value is passed directly to ellmer::chat_portkey(model = ...).

integration

Optional Portkey/gateway route slug. Should look like "vertexai" or another route returned by ellmer::models_portkey(base_url = "https://ai-gateway.apps.cloud.rt.nyu.edu/v1/"). If supplied and model is not fully-qualified (does not start with "@"), nalanda will build "@{integration}/{model}". In some gateways this slug is not the upstream provider name. When available, a fully-qualified model string such as "@gpt-5-mini/gpt-5-mini" is the most reliable option. When both nalanda.integration and nalanda.virtual_key options are set and neither argument is supplied, integration is preferred.

virtual_key

Optional legacy virtual key. Should look like "gemini-8c2498" or similar. If supplied and model is not fully-qualified, nalanda will build "@{virtual_key}/{model}". Use either integration or virtual_key, not both when explicitly supplying function arguments.

base_url

Character. Base URL for API calls.

excerpt_chars

Integer. Number of chapter characters to retain in the stored post-prompt preview shown in results.

on_error

Error policy for the repair attempts.

Value

A repaired result with the same outer shape as x. Attributes repaired_units and non_retryable_units identify the units selected for retry and those retained because of content-policy failures, respectively.