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| library(shiny) | |
| library(bslib) | |
| library(htmltools) | |
| #library(markdown) | |
| library(fontawesome) | |
| library(bsicons) | |
| library(gt) | |
| library(glue) | |
| library(ggplot2) | |
| library(readr) | |
| library(dplyr) | |
| library(mapgl) | |
| library(duckdbfs) | |
| duckdbfs::load_spatial() | |
| css <- | |
| HTML(paste0("<link rel='stylesheet' type='text/css' ", | |
| "href='https://demos.creative-tim.com/", | |
| "material-dashboard/assets/css/", | |
| "material-dashboard.min.css?v=3.2.0'>")) | |
| # Define the UI | |
| ui <- page_sidebar( | |
| fillable = FALSE, # do not squeeze to vertical screen space | |
| tags$head(css), | |
| titlePanel("Demo App"), | |
| " | |
| This is a proof-of-principle for a simple chat-driven interface | |
| to dynamically explore geospatial data. | |
| ", | |
| card( | |
| layout_columns( | |
| textInput("chat", | |
| label = NULL, | |
| "Which four counties in California have the highest average social vulnerability?", | |
| width = "100%"), | |
| div( | |
| actionButton("user_msg", "", icon = icon("paper-plane"), | |
| class = "btn-primary btn-sm align-bottom"), | |
| class = "align-text-bottom"), | |
| col_widths = c(11, 1)), | |
| fill = FALSE | |
| ), | |
| textOutput("agent"), | |
| layout_columns( | |
| card(maplibreOutput("map")), | |
| card(includeMarkdown("## Plot"), | |
| plotOutput("chart1"), | |
| plotOutput("chart2"), | |
| ), | |
| col_widths = c(8, 4), | |
| row_heights = c("500px"), | |
| max_height = "600px" | |
| ), | |
| gt_output("table"), | |
| card(fill = TRUE, | |
| card_header(fa("robot"), textOutput("model", inline = TRUE)), | |
| accordion( | |
| open = FALSE, | |
| accordion_panel( | |
| title = "show sql", | |
| icon = fa("terminal"), | |
| verbatimTextOutput("sql_code"), | |
| ), | |
| accordion_panel( | |
| title = "explain", | |
| icon = fa("user", prefer_type="solid"), | |
| textOutput("explanation"), | |
| ) | |
| ), | |
| ), | |
| card( | |
| card_header("Errata"), | |
| shiny::markdown(readr::read_file("footer.md")), | |
| ), | |
| sidebar = sidebar( | |
| selectInput( | |
| "select", | |
| "Select an LLM:", | |
| list("LLama3" = "llama3", | |
| #"OLMO2 (AllenAI)" = "olmo", | |
| "Gorilla (UC Berkeley)" = "gorilla" | |
| ) | |
| ), | |
| input_switch("redlines", "Redlined Areas", value = FALSE), | |
| input_switch("svi", "Social Vulnerability", value = TRUE), | |
| input_switch("richness", "Biodiversity Richness", value = FALSE), | |
| input_switch("rsr", "Biodiversity Range Size Rarity", value = FALSE), | |
| card( | |
| card_header(bs_icon("github"), "Source code:"), | |
| a(href = "https://github.com/boettiger-lab/geo-llm-r", | |
| "https://github.com/boettiger-lab/geo-llm-r")) | |
| ), | |
| theme = bs_theme(version = "5") | |
| ) | |
| repo <- "https://data.source.coop/cboettig/social-vulnerability" | |
| pmtiles <- glue("{repo}/2022/SVI2022_US_tract.pmtiles") | |
| parquet <- glue("{repo}/2022/SVI2022_US_tract.parquet") | |
| con <- duckdbfs::cached_connection() | |
| svi <- open_dataset(parquet, tblname = "svi") |> filter(RPL_THEMES > 0) | |
| safe_parse <- function(txt) { | |
| gsub("[\r\n]", " ", txt) |> gsub("\\s+", " ", x = _) | |
| } | |
| # helper utilities | |
| # faster/more scalable to pass maplibre the ids to refilter pmtiles, | |
| # than to pass it the full geospatial/sf object | |
| filter_column <- function(full_data, filtered_data, id_col = "FIPS") { | |
| if (nrow(filtered_data) < 1) return(NULL) | |
| values <- full_data |> | |
| inner_join(filtered_data, copy = TRUE) |> | |
| pull(id_col) | |
| # maplibre syntax for the filter of PMTiles | |
| list("in", list("get", id_col), list("literal", values)) | |
| } | |
| # Define the server | |
| server <- function(input, output, session) { | |
| chart1_data <- svi |> | |
| group_by(COUNTY) |> | |
| summarise(mean_svi = mean(RPL_THEMES)) |> | |
| collect() | |
| chart1 <- chart1_data |> | |
| ggplot(aes(mean_svi)) + geom_density(fill="darkred") + | |
| ggtitle("County-level vulnerability nation-wide") | |
| data <- reactiveValues(df = tibble()) | |
| output$chart1 <- renderPlot(chart1) | |
| model <- reactive(input$select) | |
| output$model <- renderText(input$select) | |
| observe({ | |
| schema <- read_file("schema.yml") | |
| system_prompt <- glue::glue(readr::read_file("system-prompt.md"), | |
| .open = "<", .close = ">") | |
| chat <- ellmer::chat_vllm( | |
| base_url = "https://llm.nrp-nautilus.io/", | |
| model = model(), | |
| api_key = Sys.getenv("NRP_API_KEY"), | |
| system_prompt = system_prompt, | |
| api_args = list(temperature = 0) | |
| ) | |
| observeEvent(input$user_msg, { | |
| stream <- chat$chat(input$chat) | |
| # Parse response | |
| response <- jsonlite::fromJSON(safe_parse(stream)) | |
| #response <- jsonlite::fromJSON(stream) | |
| if ("query" %in% names(response)) { | |
| output$sql_code <- renderText(stringr::str_wrap(response$query, width = 60)) | |
| output$explanation <- renderText(response$explanation) | |
| # Actually execute the SQL query generated: | |
| df <- DBI::dbGetQuery(con, response$query) | |
| # don't display shape column in render | |
| df <- df |> select(-any_of("Shape")) | |
| output$table <- render_gt(df, height = 300) | |
| y_axis <- colnames(df)[!colnames(df) %in% colnames(svi)] | |
| chart2 <- df |> | |
| rename(social_vulnerability = y_axis) |> | |
| ggplot(aes(social_vulnerability)) + | |
| geom_density(fill = "darkred") + | |
| xlim(c(0, 1)) + | |
| ggtitle("Vulnerability of selected areas") | |
| output$chart2 <- renderPlot(chart2) | |
| # We need to somehow trigger this df to update the map. | |
| data$df <- df | |
| # Note: ellmer will preserve full chat history automatically. | |
| # this can confuse the agent and mess up behavior, so we reset: | |
| chat$set_turns(NULL) | |
| } else { | |
| output$agent <- renderText(response$agent) | |
| } | |
| }) | |
| }) | |
| output$map <- renderMaplibre({ | |
| m <- maplibre(center = c(-104.9, 40.3), zoom = 3, height = "400") | |
| if (input$redlines) { | |
| m <- m |> | |
| add_fill_layer( | |
| id = "redlines", | |
| source = list(type = "vector", | |
| url = paste0("pmtiles://", "https://data.source.coop/cboettig/us-boundaries/mappinginequality.pmtiles")), | |
| source_layer = "mappinginequality", | |
| fill_color = list("get", "fill") | |
| ) | |
| } | |
| if (input$richness) { | |
| m <- m |> | |
| add_raster_source(id = "richness", | |
| tiles = "https://data.source.coop/cboettig/mobi/tiles/red/species-richness-all/{z}/{x}/{y}.png", | |
| maxzoom = 11 | |
| ) |> | |
| add_raster_layer(id = "richness-layer", | |
| source = "richness") | |
| } | |
| if (input$rsr) { | |
| m <- m |> | |
| add_raster_source(id = "rsr", | |
| tiles = "https://data.source.coop/cboettig/mobi/tiles/green/range-size-rarity-all/{z}/{x}/{y}.png", | |
| maxzoom = 11 | |
| ) |> | |
| add_raster_layer(id = "richness-layer", | |
| source = "rsr") | |
| } | |
| if (input$svi) { | |
| m <- m |> | |
| add_fill_layer( | |
| id = "svi_layer", | |
| source = list(type = "vector", | |
| url = paste0("pmtiles://", pmtiles)), | |
| source_layer = "svi", | |
| filter = filter_column(svi, data$df, "FIPS"), | |
| fill_opacity = 0.5, | |
| fill_color = interpolate(column = "RPL_THEMES", | |
| values = c(0, 1), | |
| stops = c("lightpink", "darkred"), | |
| na_color = "lightgrey") | |
| ) | |
| } | |
| m | |
| }) | |
| } | |
| # Run the app | |
| shinyApp(ui = ui, server = server) |