querychat (version 0.2.0)

querychat: QueryChat convenience functions

Description

Convenience functions for wrapping QueryChat creation (i.e., querychat()) and app launching (i.e., querychat_app()).

Usage

querychat(
  data_source,
  table_name = missing_arg(),
  ...,
  id = NULL,
  greeting = NULL,
  client = NULL,
  tools = c("update", "query"),
  data_description = NULL,
  categorical_threshold = 20,
  extra_instructions = NULL,
  prompt_template = NULL,
  cleanup = NA
)
querychat_app(
  data_source,
  table_name = missing_arg(),
  ...,
  id = NULL,
  greeting = NULL,
  client = NULL,
  tools = c("update", "query"),
  data_description = NULL,
  categorical_threshold = 20,
  extra_instructions = NULL,
  prompt_template = NULL,
  cleanup = NA,
  bookmark_store = "url"
)

Value

A QueryChat object. See QueryChat for available methods.

Invisibly returns the chat object after the app stops.

Arguments

data_source

Either a data.frame or a database connection (e.g., DBI connection).

table_name

A string specifying the table name to use in SQL queries. If data_source is a data.frame, this is the name to refer to it by in queries (typically the variable name). If not provided, will be inferred from the variable name for data.frame inputs. For database connections, this parameter is required.

...

Additional arguments (currently unused).

id

Optional module ID for the QueryChat instance. If not provided, will be auto-generated from table_name. The ID is used to namespace the Shiny module.

greeting

Optional initial message to display to users. Can be a character string (in Markdown format) or a file path. If not provided, a greeting will be generated at the start of each conversation using the LLM, which adds latency and cost. Use $generate_greeting() to create a greeting to save and reuse.

client

Optional chat client. Can be:

• An ellmer::Chat object

• A string to pass to ellmer::chat() (e.g., "openai/gpt-4o")

• NULL (default): Uses the querychat.client option, the QUERYCHAT_CLIENT environment variable, or defaults to ellmer::chat_openai()

tools

Which querychat tools to include in the chat client, by default. "update" includes the tools for updating and resetting the dashboard and "query" includes the tool for executing SQL queries. Use tools = "update" when you only want the dashboard updating tools, or when you want to disable the querying tool entirely to prevent the LLM from seeing any of the data in your dataset.

data_description

Optional description of the data in plain text or Markdown. Can be a string or a file path. This provides context to the LLM about what the data represents.

categorical_threshold

For text columns, the maximum number of unique values to consider as a categorical variable. Default is 20.

extra_instructions

Optional additional instructions for the chat model in plain text or Markdown. Can be a string or a file path.

prompt_template

Optional path to or string of a custom prompt template file. If not provided, the default querychat template will be used. See the package prompts directory for the default template format.

cleanup

Whether or not to automatically run $cleanup() when the Shiny session/app stops. By default, cleanup only occurs if QueryChat is created within a Shiny app. Set to TRUE to always clean up, or FALSE to never clean up automatically.

In querychat_app(), in-memory databases created for data frames are always cleaned up.

bookmark_store

The bookmarking storage method. Passed to shiny::enableBookmarking(). If "url" or "server", the chat state (including current query) will be bookmarked. Default is "url".

Examples

if (FALSE) { # rlang::is_interactive() && rlang::is_installed("RSQLite")
# Quick start - chat with mtcars dataset in one line
querychat_app(mtcars)

# Add options
querychat_app(
  mtcars,
  greeting = "Welcome to the mtcars explorer!",
  client = "openai/gpt-4o"
)

# Chat with a database table (table_name required)
con <- DBI::dbConnect(RSQLite::SQLite(), ":memory:")
DBI::dbWriteTable(con, "mtcars", mtcars)
querychat_app(con, "mtcars")

# Create QueryChat class object
qc <- querychat(mtcars, greeting = "Welcome to the mtcars explorer!")

# Run the app later
qc$app()
}