Case study


  • Key functionality: Enable the user to toggle between traditional data filters and a natural language chat interface to update reactive output

First, the app

Live app is hosted on Posit Connect Cloud here.

SQL queries?

Why did it write this?

SELECT * FROM master_dat WHERE DiagnosisCategory = 'HF' ORDER BY Excess DESC LIMIT 10

  • Comes from the querychat R package

  • Conceptual flow:

    1. User asks a question
    2. LLM generates a SQL query based on metadata
    3. Query is executed on your dataset locally
    4. Filtered data can be consumed by downstream reactives as normal

  • Provides a clever way to manipulate your app content through natural language while maintaining data security

How the code looks

1. Initialize chat object

library(querychat)

# In global.R
querychat_config <-
  querychat_init(
    data_source = querychat_data_source(master_dat, tbl_name = "HospitalHRRP"),
    client = ellmer::chat_google_gemini,
    greeting = "Ask me a question about the HRRP in Wisconsin",
    data_description = readLines("data_description.md")
  )

2. Create chat UI

# In ui.R
querychat_ui(id = "chat")

3. Access filtered data

# In server.R
querychat <- querychat_server("chat", querychat_config)
current_hospitals <- reactive({querychat$df()})

4. Use in app content

# In server.R (display hospital count)
output$hospital_count <-
  renderText({
    n_distinct(current_hospitals()$FacilityID)
  })

The key to success

Supply thorough context about your data



querychat_init(
  data_source = querychat_data_source(master_dat, tbl_name = "HospitalHRRP"),
  client = ellmer::chat_google_gemini,
  greeting = "Ask me a question about the HRRP in Wisconsin",
  data_description = readLines("data_description.md")
)

View source document here.

data_description.md

Back to the toggle…

How do we make this work?

Using conditional panels!

In ui.R

# Make a toggle
bslib::input_switch(
  id = "chat_mode",
  label = "Chat Mode"
),
        
# Show manual filters
conditionalPanel(
  condition = "!input.chat_mode",
  datamods::select_group_ui(id = "hospitals", params = ...)
),

# Show chat interface
conditionalPanel(
  condition = "input.chat_mode",
  querychat_ui(id = "chat") 
),

Click to see the full ui.R and server.R files.

In server.R

# Traditional (simultaneous) filter
current_hospitals_temp <-
  datamods::select_group_server(
    id = "hospitals",
    data = reactive(master_dat),
    vars = reactive(c("FacilityName", "City", "County", "Zip"))
  )

# Make the chat server
querychat <- querychat_server("chat", querychat_config)

# Select data based on toggle state
current_hospitals <- reactive({
    if (input$chat_mode) {
      temp_hospitals <- querychat$df()
    } else {
      temp_hospitals <- current_hospitals_temp()
      # APPLY MANUAL FILTER LOGIC
    }
    temp_hospitals
  })

Summary

  • Use the querychat package to build the chat interface and server connection

    • It’s key to specify the data_description argument thoroughly for better chat experience

  • The bslib::input_switch() function creates the toggle, and conditionalPanel() renders the set of filters displayed to the user, depending on what is selected

  • reactive() objects on the server side help pick the right dataset depending on the state of the toggle

    • Keep things upstream: Recommend designing/pre-processing your data in a sensisble way to allow congruency among filtered data output regardless of method (so downstream content doesn’t care about source)

Thank you!

Links: