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| library(shiny) | |
| library(httr) | |
| library(jsonlite) | |
| library(commonmark) | |
| library(glue) | |
| source("llm_api.R") | |
| source("package_manager_module.R") | |
| ui <- fluidPage( | |
| titlePanel("AI-Assisted R Analysis Tool"), | |
| sidebarLayout( | |
| sidebarPanel( | |
| h4("LLM Chat"), | |
| passwordInput("api_key", "Enter your Groq API Key:", ""), | |
| div( | |
| style = 'overflow-y: auto; overflow-x: hidden; height: 300px; border: 1px solid #ccc; padding: 10px; word-wrap: break-word;', | |
| uiOutput("chat_output") | |
| ), | |
| textInput("chat_input", "Your Question or Command:", ""), | |
| actionButton("chat_submit", "Ask LLM") | |
| ), | |
| mainPanel( | |
| tabsetPanel( | |
| type = "tabs", | |
| tabPanel( | |
| "R Code Box", | |
| textAreaInput( | |
| "r_code_input", | |
| "R Script Editor:", | |
| "plot(1:10, 1:10, main = 'Example Plot')", | |
| height = "300px", | |
| width = "100%" | |
| ), | |
| actionButton("run_r_code", "Run Code") | |
| ), | |
| tabPanel( | |
| "Console Output", | |
| uiOutput("console_output") | |
| ), | |
| tabPanel( | |
| "Display Pane", | |
| plotOutput("display_plot") | |
| ), | |
| packageManagerUI("package_manager"), | |
| tabPanel( | |
| "LLM API", | |
| verbatimTextOutput("llm_api_output") | |
| ) | |
| ) | |
| ) | |
| ) | |
| ) | |
| server <- function(input, output, session) { | |
| conversation_history <- reactiveVal(list()) | |
| console_output_value <- reactiveVal(NULL) | |
| last_response <- reactiveVal(NULL) | |
| last_request <- reactiveVal(NULL) | |
| model <- "llama3-8b-8192" # Replace with your desired model | |
| packageManagerServer("package_manager") | |
| submit_chat <- function() { | |
| req(input$chat_input) | |
| api_key <- input$api_key | |
| if (is.null(api_key) || api_key == "") { | |
| showNotification("Please enter your Groq API Key.", type = "error") | |
| return(NULL) | |
| } | |
| # Create the history variable | |
| history <- conversation_history() | |
| # Append the user's message to the history | |
| user_message <- list(role = "user", content = input$chat_input) | |
| history <- append(history, list(user_message)) | |
| # Update the UI | |
| conversation_history(history) | |
| # Read and prepare the system message | |
| r_code <- input$r_code_input | |
| console_output <- paste(console_output_value(), collapse = "\n") | |
| system_message <- glue(paste(readLines("system_message.txt"), collapse = "\n")) | |
| tryCatch({ | |
| # Call send_chat_completion and get the response | |
| response_data <- send_chat_completion( | |
| api_key = api_key, | |
| system_message = system_message, | |
| model = model, | |
| messages = history | |
| ) | |
| # Now extract the assistant's message | |
| response_json <- response_data$response_json | |
| # Display the request and response in the LLM API tab | |
| last_request(response_data$request_body) | |
| # Re-serialize the response JSON with pretty formatting | |
| last_response( | |
| toJSON(response_data$response_json, auto_unbox = TRUE, pretty = TRUE) | |
| ) | |
| # Debugging statements | |
| # print("Structure of response_json:") | |
| # print(str(response_json)) | |
| # Access the assistant's message | |
| if (!is.null(response_json$choices)) { | |
| choices <- response_json$choices | |
| assistant_message <- response_json$choices[[1]]$message$content | |
| # print("Assistant's message content:") | |
| # print(assistant_message) | |
| # Append the assistant's response to the conversation history | |
| history <- append(history, list( | |
| list(role = "assistant", content = assistant_message) | |
| )) | |
| conversation_history(history) | |
| # Update the chat output | |
| output$chat_output <- renderUI({ | |
| msgs <- lapply(conversation_history(), function(msg) { | |
| # Convert the Markdown content to HTML | |
| content_html <- commonmark::markdown_html(msg$content) | |
| # Create a div for each message | |
| tags$div( | |
| tags$p(tags$b(paste0(msg$role, ":"))), # Display the role in bold | |
| HTML(content_html) # Render the converted HTML content | |
| ) | |
| }) | |
| do.call(tagList, msgs) | |
| }) | |
| # Clear the chat input field | |
| updateTextInput(session, "chat_input", value = "") | |
| } else if (!is.null(response_json$error)) { | |
| # Handle API error response | |
| showNotification(paste("API Error:", response_json$error$message), type = "error") | |
| } else { | |
| # Unexpected response structure | |
| showNotification("Unexpected response from the API.", type = "error") | |
| } | |
| }, error = function(e) { | |
| showNotification(paste("Error:", e$message), type = "error") | |
| }) | |
| } | |
| observeEvent(input$chat_submit, { | |
| submit_chat() | |
| }) | |
| # Existing code for running R code and updating the console and display pane remains unchanged | |
| observeEvent(input$run_r_code, { | |
| code <- input$r_code_input | |
| result <- tryCatch({ | |
| output_text <- capture.output(eval(parse(text = code))) | |
| output_text | |
| }, error = function(e) { | |
| e$message | |
| }) | |
| console_output_value(result) | |
| output$console_output <- renderUI({ | |
| HTML(paste(result, collapse = "<br>")) | |
| }) | |
| }) | |
| output$display_plot <- renderPlot({ | |
| input$run_r_code | |
| code <- isolate(input$r_code_input) | |
| tryCatch({ | |
| eval(parse(text = code)) | |
| }, error = function(e) { | |
| plot.new() | |
| text(0.5, 0.5, paste("Error:", e$message), cex = 1.5) | |
| }) | |
| }) | |
| output$llm_api_output <- renderPrint({ | |
| cat("Last Request:\n") | |
| cat(last_request(), "\n\n") | |
| cat("Last Response:\n") | |
| cat(last_response()) | |
| }) | |
| } | |
| shinyApp(ui = ui, server = server) | |