openai to
llmcoder: Core rating for text stimuli now uses
llmcoder::call_llm(), enabling multi-provider support
(OpenAI, Anthropic, Ollama, LM Studio, DeepSeek, Groq, Mistral,
OpenRouter, OpenAI-compatible).return_type parameter: Control output
format: "numeric" (default, extract numbers only),
"text" (return full text response), "raw"
(return unprocessed API response).columns parameter (experimental):
Select which columns appear in the returned data frame. Available
columns: "stim", "rating",
"iteration", "scale", "type",
"provider", "model". Default NULL
returns all columns.curl::form_file() usage in Whisper API upload
(previously used incorrect httr2 multipart syntax).debug parameter not passed to
rate_build_content_blocks(), causing
"argument is not interpretable as logical" error when
processing audio or image stimuli.@examples in generate_ratings()
and generate_ratings_for_all(): 9 detailed examples
covering text (string), image (local file + URL), and audio (local file)
stimuli, with both numeric rating and full-text description
workflows.get_lexical_coverage(), get_word_frequency(),
get_zipf_metric(), get_levenshtein_d(),
get_semantic_transparency() have been removed to focus the
package on its core rating functionality.generate_ratings() and
generate_ratings_for_all() are now exported.openai package).generate_ratings() for single-stimulus rating via
LLM.generate_ratings_for_all() for batch rating of multiple
stimuli.get_lexical_coverage(): Calculate lexical coverage of a
text.get_word_frequency(): Look up word frequency
information.get_zipf_metric(): Calculate Zipf metric for a
text.get_levenshtein_d(): Calculate Levenshtein distance
between strings.get_semantic_transparency(): Rate semantic
transparency."1-7",
"0-10", etc.).
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