anes_2024_personas      Example participant profiles derived from ANES
                        2024
bind_tools              Bind tools to a config (provider-agnostic)
build_factorial_experiments
                        Build Factorial Experiment Design
call_llm                Call an LLM (chat/completions or embeddings)
                        with optional multimodal input
call_llm_broadcast      Parallel API calls: Fixed Config, Multiple
                        Messages
call_llm_compare        Parallel API calls: Multiple Configs, Fixed
                        Message
call_llm_par            Parallel LLM Processing with Tibble-Based
                        Experiments (Core Engine)
call_llm_par_structured
                        Parallel experiments with structured parsing
call_llm_par_tags       Parallel experiments with tag parsing
call_llm_robust         Robustly Call LLM API (Simple Retry)
call_llm_stream         Stream a chat completion token by token
call_llm_sweep          Parallel API calls: Parameter Sweep - Vary One
                        Parameter, Fixed Message
call_llm_tools          Call an LLM with tools and run the tool loop
diagnostics             Machine-readable diagnostics for an LLMR-family
                        result object
disable_structured_output
                        Disable Structured Output (clean provider
                        toggles)
enable_structured_output
                        Enable Structured Output (Provider-Agnostic)
ensure_alternating_messages
                        Make a message array provider-safe
                        (alternating, user-leading)
expand_llm_config       Expand an LLM Config Grid
get_batched_embeddings
                        Generate Embeddings in Batches
llm_add_request_hash    Append the audit-log request hash to a
                        parallel-results frame
llm_agreement           Agreement across replicated LLM annotations
llm_api_key_env         Declare an API key sourced from an environment
                        variable
llm_batch_cancel        Cancel a batch job
llm_batch_fetch         Fetch the results of a batch job
llm_batch_status        Check the status of a batch job
llm_batch_submit        Submit a batch job to a provider's batch API
llm_chat_session        Chat Session Object and Methods
llm_config              Create an LLM configuration (provider-agnostic)
llm_cross_design        Cross a data frame with LLM configs
llm_failures            List the rows of an LLM run that failed or were
                        truncated
llm_fn                  Apply an LLM prompt over vectors/data frames
llm_fn_structured       Vectorized structured-output LLM
llm_fn_tags             Vectorized LLM with tag extraction
llm_hash                Content hash for research artifacts
llm_judge               LLM-as-a-Judge Evaluation
llm_log_enable          Record every LLM call in a local audit log
llm_log_read            Read an LLMR audit log into records and a
                        manifest
llm_logprobs            Extract token log-probabilities from a response
llm_methods_text        Draft a methods-section paragraph from an LLM
                        run
llm_mutate              Mutate a data frame with LLM output
llm_mutate_structured   Data-frame mutate with structured output
llm_mutate_tags         Data-frame mutate with XML-like tag output
llm_par_resume          Resume failed parallel LLM calls
llm_parse_rowpack_tags
                        Parse a batched, row-wrapped tag response into
                        per-row field lists
llm_parse_structured    Parse structured output emitted by an LLM
llm_parse_structured_col
                        Parse structured fields from a column into
                        typed vectors
llm_parse_tags          Parse XML-like tags emitted by an LLM
llm_parse_tags_col      Parse XML-like tag fields from a column
llm_persona_demographic_fields
                        Which columns of a persona frame are
                        demographics
llm_persona_dictionary
                        The question dictionary attached to a persona
                        data frame
llm_persona_overview    A compact overview of a persona frame for
                        display
llm_persona_split       Split one persona into labeled demographics and
                        labeled answers
llm_preview             Preview a tidy LLM call without spending
                        anything
llm_render_messages     Render tidy messages without calling any API
llm_replicate           Run the same prompt several times per row
llm_request_from_log    Rebuild a callable request from a logged record
llm_request_hash        Stable request hash for an LLM call
llm_response_record     Flatten one LLM response to a provenance row
llm_tool                Define a tool the model may call
llm_tool_signature      A stable signature for a tool's identity
llm_usage               Summarize token usage and outcomes of an LLM
                        run
llm_uuid                A short, sortable, process-unique identifier
llm_validate_persona_frame
                        Check that a data frame follows the persona
                        contract
llm_validate_structured_col
                        Validate structured JSON objects against a JSON
                        Schema (locally)
llmr_response           LLMR Response Object
parse_embeddings        Parse Embedding Response into a Numeric Matrix
print.llm_config        Print an LLM configuration with the API key
                        masked
report                  Draft a methods-section report from an
                        LLMR-family result object
reset                   Reset a stateful object to its initial position
reset_llm_parallel      Reset Parallel Environment
setup_llm_parallel      Setup Parallel Environment for LLM Processing
tool_calls              Extract tool calls from a response
transcript_as_messages
                        Build a role-flipped message array from a
                        multi-speaker transcript
