Prompt Large Language Models and Enhance Their Functionality

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Documentation for package ‘tidyprompt’ version 0.0.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

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_integer	Make LLM answer as an integer (between min and max)
answer_as_json	Make LLM answer as JSON (with optional schema)
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_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
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_feedback	Create an 'llm_feedback' object
llm_provider-class	LlmProvider R6 Class
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
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