add_msg_to_chat_history
                        Add a message to a chat history
add_text                Add text to a tidyprompt
answer_as_boolean       Make LLM answer as a boolean (TRUE or FALSE)
answer_as_category      Make LLM answer as a category
answer_as_integer       Make LLM answer as an integer (between min and
                        max)
answer_as_json          Make LLM answer as JSON (with optional schema;
                        structured output)
answer_as_key_value     Make LLM answer as a list of key-value pairs
answer_as_list          Make LLM answer as a list of items
answer_as_multi_category
                        Build prompt for categorizing a text into
                        multiple categories
answer_as_named_list    Make LLM answer as a named list
answer_as_regex_match   Make LLM answer match a specific regex
answer_as_text          Make LLM answer as a constrained text response
answer_by_chain_of_thought
                        Set chain of thought mode for a prompt
answer_by_react         Set ReAct mode for a prompt
answer_using_r          Enable LLM to draft and execute R code
answer_using_sql        Enable LLM to draft and execute SQL queries on
                        a database
answer_using_tools      Enable LLM to call R functions (and/or MCP
                        server tools)
chat_history            Create or validate 'chat_history' object
construct_prompt_text   Construct prompt text from a tidyprompt object
df_to_string            Convert a dataframe to a string representation
extract_from_return_list
                        Function to extract a specific element from a
                        list
get_chat_history        Get the chat history of a tidyprompt object
get_prompt_wraps        Get prompt wraps from a tidyprompt object
is_tidyprompt           Check if object is a tidyprompt object
llm_break               Create an 'llm_break' object
llm_break_soft          Create an 'llm_break_soft' object
llm_feedback            Create an 'llm_feedback' object
llm_provider-class      LlmProvider R6 Class
llm_provider_ellmer     Create a new LLM provider from an
                        'ellmer::chat()' object
llm_provider_google_gemini
                        Create a new Google Gemini LLM provider
llm_provider_groq       Create a new Groq LLM provider
llm_provider_mistral    Create a new Mistral LLM provider
llm_provider_ollama     Create a new Ollama LLM provider
llm_provider_openai     Create a new OpenAI LLM provider
llm_provider_openrouter
                        Create a new OpenRouter LLM provider
llm_provider_xai        Create a new XAI (Grok) LLM provider
llm_verify              Have LLM check the result of a prompt
                        (LLM-in-the-loop)
persistent_chat-class   PersistentChat R6 class
prompt_wrap             Wrap a prompt with functions for modification
                        and handling the LLM response
provider_prompt_wrap    Create a provider-level prompt wrap
quit_if                 Make evaluation of a prompt stop if LLM gives a
                        specific response
r_json_schema_to_example
                        Generate an example object from a JSON schema
send_prompt             Send a prompt to a LLM provider
set_chat_history        Set the chat history of a tidyprompt object
set_system_prompt       Set system prompt of a tidyprompt object
skim_with_labels_and_levels
                        Skim a dataframe and include labels and levels
tidyprompt              Create a tidyprompt object
tidyprompt-class        Tidyprompt R6 Class
tools_add_docs          Add tidyprompt function documentation to a
                        function
tools_get_docs          Extract documentation from a function
user_verify             Have user check the result of a prompt
                        (human-in-the-loop)
vector_list_to_string   Convert a named or unnamed list/vector to a
                        string representation
