Constructs an LLM-powered research agent that performs web searches (via Tavily API) and generates structured responses based on search results. The agent handles different question types (general knowledge, comparisons, controversial topics) with appropriate response formats.
Arguments
- llm
A function that accepts a character prompt and returns an LLM response. (It must accept `prompt` and optionally `verbose`.)
- tavily_search
Tavily API key as a string or NULL to use `Sys.getenv("TAVILY_API_KEY")`.
- system_prompt
Optional custom system prompt for the researcher agent.
- max_results
Number of web search results to retrieve per query (default: 5).
- max_tries
Maximum number of retry attempts for search or LLM call (default: 3).
- backoff
Initial wait time in seconds between retries (default: 2).
- verbose
Logical flag to control progress messages (default: TRUE).
Value
A function that accepts a user query string and returns a list with:
query - The original research query.
prompt - The full prompt sent to the LLM.
response - The generated LLM response.
search_results - Raw search results (if any were found).
success - Logical indicating if research succeeded (both search and LLM).
Examples
if (FALSE) { # \dontrun{
# Initialize researcher agent
researcher_agent <- build_researcher_agent(
llm = my_llm_wrapper,
tavily_search = NULL,
system_prompt = NULL,
max_results = 5,
max_tries = 3,
backoff = 2,
verbose = FALSE
)
# Perform research
result <- researcher_agent("Who is Messi?")
} # }