# MCAT API - Adaptive Mental Health Assessment
# RESTful API for adaptive testing using IRT (mirt package)

library(plumber)
library(mirt)
library(mirtCAT)
library(jsonlite)

# ==============================================================================
# LOAD MODEL AND SETUP
# ==============================================================================

# Load the fitted IRT model
mod <- readRDS("Fullmodel.rds")

# Item ranges for each domain
item_ranges <- list(
  Distress = 1:10,
  Psychosis = 11:26,
  Mania = 27:31,
  Suicidality = 32:36,
  Alcohol = 37:39,
  Functioning = 40:44,
  Anxiety = 45:49
)

# Maximum scores for each domain
max_scores <- c(
  Distress = 50,
  Psychosis = 16,
  Mania = 20,
  Suicidality = 50,
  Alcohol = 12,
  Functioning = 40,
  Anxiety = 20
)

# Domain scoring bands for interpretation
domain_cuts <- list(
  Distress   = list(breaks = c(-Inf, 15, 21, 29, Inf),
                    labels = c("Low", "Moderate", "High", "Very high")),
  Psychosis  = list(breaks = c(-Inf, 4, 8, Inf),
                    labels = c("Low", "Possible concern", "Probable concern")),
  Mania      = list(breaks = c(-Inf, 5, 9, 14, Inf),
                    labels = c("No concern", "Mild", "Moderate", "Severe")),
  Suicidality= list(breaks = c(-Inf, 20, 30, 40, Inf),
                    labels = c("Low", "Moderate", "High", "Very high")),
  Alcohol    = list(breaks = c(-Inf, 0, 2, 4, 7, Inf),
                    labels = c("Abstinent", "Low", "Moderate", "High", "Very high")),
  Functioning= list(breaks = c(-Inf, 9, 20, 30, Inf),
                    labels = c("None", "Mild impairment", "Moderate impairment", "Severe impairment")),
  Anxiety    = list(breaks = c(-Inf, 4, 9, 14, Inf),
                    labels = c("Minimal", "Mild", "Moderate", "Severe"))
)

# Extract model parameters
K     <- extract.mirt(mod, "K")
mins  <- mod@Data$mins
items <- colnames(mod@Data$data)
nfact <- extract.mirt(mod, "nfact")

# ==============================================================================
# ITEM LABELS (Question Text)
# ==============================================================================

item_labels <- c(
  # K10
  K10_1 = "In the past four (4) weeks, about how often did you feel tired out for no good reason?",
  K10_2 = "In the past four (4) weeks, about how often did you feel nervous?",
  K10_3 = "In the past four (4) weeks, about how often did you feel so nervous that nothing could calm you down?",
  K10_4 = "In the past four (4) weeks, about how often did you feel hopeless?",
  K10_5 = "In the past four (4) weeks, about how often did you feel restless or fidgety?",
  K10_6 = "In the past four (4) weeks, about how often did you feel so restless you could not sit still?",
  K10_7 = "In the past four (4) weeks, about how often did you feel depressed?",
  K10_8 = "In the past four (4) weeks, about how often did you feel that everything was an effort?",
  K10_9 = "In the past four (4) weeks, about how often did you feel so sad that nothing could cheer you up?",
  K10_10 = "In the past four (4) weeks, about how often did you feel worthless?",

  # OASIS
  OASIS_1 = "In the past week, how often have you felt anxious?",
  OASIS_2 = "In the past week, how intense or severe was your anxiety when it occurred?",
  OASIS_3 = "In the past week, how often did you avoid things due to anxiety or fear?",
  OASIS_4 = "In the past week, how much did anxiety interfere with work, school, or home responsibilities?",
  OASIS_5 = "In the past week, how much did anxiety interfere with your social life and relationships?",

  # SIDAS
  SIDAS_1 = "In the past month, how often have you had thoughts about suicide?",
  SIDAS_2 = "In the past month, how much control have you had over these thoughts?",
  SIDAS_3 = "In the past month, how close have you come to making a suicide attempt?",
  SIDAS_4 = "In the past month, to what extent have you felt tormented by thoughts about suicide?",
  SIDAS_5 = "In the past month, how much have thoughts about suicide interfered with daily activities?",

  # PQ16
  PQ16_1 = "I feel uninterested in the things I used to enjoy.",
  PQ16_2 = "I often seem to live through events exactly as they happened before (deja vu).",
  PQ16_3 = "I sometimes smell or taste things that others can't.",
  PQ16_4 = "I often hear unusual sounds like banging, clicking, or ringing in my ears.",
  PQ16_5 = "I've been confused about whether something was real or imaginary.",
  PQ16_6 = "I've seen my own or others' faces change in strange ways.",
  PQ16_7 = "I get extremely anxious when meeting people for the first time.",
  PQ16_8 = "I have seen things others apparently can't see.",
  PQ16_9 = "My thoughts are so strong I can almost hear them.",
  PQ16_10 = "I see special meanings in ordinary things.",
  PQ16_11 = "Sometimes I feel I'm not in control of my thoughts.",
  PQ16_12 = "I get distracted by distant sounds I normally wouldn't notice.",
  PQ16_13 = "I hear voices or whispers that others can't.",
  PQ16_14 = "I often feel others have it in for me.",
  PQ16_15 = "I sense a presence around me when no one's there.",
  PQ16_16 = "I feel parts of my body have changed or work differently.",

  # ASRM
  ASRM_1 = "In the past week, how cheerful have you felt?",
  ASRM_2 = "In the past week, how confident have you felt?",
  ASRM_3 = "In the past week, how much sleep have you needed?",
  ASRM_4 = "In the past week, how fast or pressured has your speech been?",
  ASRM_5 = "In the past week, how active have you been?",

  # WSAS
  WSAS_1 = "Because of my mental health, my ability to work is impaired.",
  WSAS_2 = "Because of my mental health, my home management is impaired.",
  WSAS_3 = "Because of my mental health, my social leisure activities are impaired.",
  WSAS_4 = "Because of my mental health, my private leisure activities are impaired.",
  WSAS_5 = "Because of my mental health, my ability to form and maintain close relationships is impaired.",

  # AUDIT-C
  AUDITC_MOD_1 = "How often do you have a drink containing alcohol?",
  AUDITC_MOD_2 = "How many drinks do you have on a typical drinking day?",
  AUDITC_MOD_3 = "How often do you have six or more drinks on one occasion?",
  AUDITC_MOD_4 = "In the past 3 months, how often has alcohol led to health, social, legal or financial problems?"
)

# Function to get option labels for an item
get_option_labels <- function(item_name, item_k, item_min) {
  # Default: just use numeric values
  option_labels <- as.character(item_min + 0:(item_k - 1))

  # K10 items (5-point scale)
  if (grepl("^K10_", item_name)) {
    option_labels <- c("None of the time",
                      "A little of the time",
                      "Some of the time",
                      "Most of the time",
                      "All of the time")
  }

  # SIDAS items (11-point scales)
  else if (item_name == "SIDAS_1") {
    option_labels <- c("Never", "1","2","3","4","5","6","7","8","9","Always")
  }
  else if (item_name == "SIDAS_2") {
    option_labels <- c("Total control", "1","2","3","4","5","6","7","8","9","No control")
  }
  else if (item_name == "SIDAS_3") {
    option_labels <- c("Not at all", "1","2","3","4","5","6","7","8","9","Made an attempt")
  }
  else if (item_name == "SIDAS_4") {
    option_labels <- c("Not at all", "1","2","3","4","5","6","7","8","9","Extremely")
  }
  else if (item_name == "SIDAS_5") {
    option_labels <- c("Not at all", "1","2","3","4","5","6","7","8","9","Extremely")
  }

  # PQ16 items (binary)
  else if (grepl("^PQ16_", item_name)) {
    option_labels <- c("No", "Yes")
  }

  # OASIS items
  else if (item_name == "OASIS_1") {
    option_labels <- c(
      "0 - No anxiety in the past week.",
      "1 - Infrequent anxiety. Felt anxious a few times.",
      "2 - Occasional anxiety. Felt anxious as much of the time as not. It was hard to relax.",
      "3 - Frequent anxiety. Felt anxious most of the time. It was very difficult to relax.",
      "4 - Constant anxiety. Felt anxious all of the time and never really relaxed."
    )
  }
  else if (item_name == "OASIS_2") {
    option_labels <- c(
      "0 - Little or None: Anxiety was absent or barely noticeable.",
      "1 - Mild: Anxiety was at a low level. It was possible to relax when I tried. Physical symptoms were only slightly uncomfortable.",
      "2 - Moderate: Anxiety was distressing at times. It was hard to relax or concentrate, but I could do it if I tried. Physical symptoms were uncomfortable.",
      "3 - Severe: Anxiety was intense much of the time. It was very difficult to relax or focus on anything else. Physical symptoms were extremely uncomfortable.",
      "4 - Extreme: Anxiety was overwhelming. It was impossible to relax at all. Physical symptoms were unbearable."
    )
  }
  else if (item_name == "OASIS_3") {
    option_labels <- c(
      "0 - None: I do not avoid places, situations, activities, or things because of fear.",
      "1 - Infrequent: I avoid something once in a while, but will usually face the situation or object. My lifestyle is not affected.",
      "2 - Occasional: I have some fear of certain situations, places, or objects, but it is still manageable. My lifestyle has only changed in minor ways. I always or almost always avoid the things I fear when I'm alone, but can handle them if someone comes with me.",
      "3 - Frequent: I have considerable fear and really try to avoid the things that frighten me. I have made significant changes in my lifestyle to avoid the object, situation, activity, or place.",
      "4 - All the Time: Avoiding objects, situations, activities, or places has taken over my life. My lifestyle has been extensively affected and I no longer do things that I used to enjoy."
    )
  }
  else if (item_name == "OASIS_4") {
    option_labels <- c(
      "0 - None: No interference at work/home/school from anxiety.",
      "1 - Mild: My anxiety has caused some interference at work/home/school. Things are more difficult, but everything that needs to be done is still getting done.",
      "2 - Moderate: My anxiety definitely interferes with tasks. Most things are still getting done, but few things are being done as well as in the past.",
      "3 - Severe: My anxiety has really changed my ability to get things done. Some tasks are still being done, but many things are not. My performance has definitely suffered.",
      "4 - Extreme: My anxiety has become incapacitating. I am unable to complete tasks and have faced serious consequences (e.g., eviction, job loss, unpaid bills)."
    )
  }
  else if (item_name == "OASIS_5") {
    option_labels <- c(
      "0 - None: My anxiety doesn't affect my relationships.",
      "1 - Mild: My anxiety slightly interferes with my relationships. Some of my friendships and other relationships have suffered, but overall my social life is still fulfilling.",
      "2 - Moderate: I have experienced some interference with my social life, but I still have a few close relationships. I don't spend as much time with others as in the past, but I still socialize sometimes.",
      "3 - Severe: My friendships and other relationships have suffered a lot because of anxiety. I do not enjoy social activities and socialize very little.",
      "4 - Extreme: My anxiety has completely disrupted my social activities. All of my relationships have suffered or ended, and my family life is extremely strained."
    )
  }

  # WSAS items (9-point scale)
  else if (grepl("^WSAS_", item_name)) {
    option_labels <- c(
      "0 - Not at all",
      "1",
      "2 - Slightly",
      "3",
      "4 - Definitely",
      "5",
      "6 - Markedly",
      "7",
      "8 - Very severely"
    )
  }

  # ASRM items
  else if (item_name == "ASRM_1") {
    option_labels <- c(
      "0 - I do not feel happier or more cheerful than usual.",
      "1 - I occasionally feel happier or more cheerful than usual.",
      "2 - I often feel happier or more cheerful than usual.",
      "3 - I feel happier or more cheerful than usual most of the time.",
      "4 - I feel happier or more cheerful than usual all of the time."
    )
  }
  else if (item_name == "ASRM_2") {
    option_labels <- c(
      "0 - I do not feel more self-confident than usual.",
      "1 - I occasionally feel more self-confident than usual.",
      "2 - I often feel more self-confident than usual.",
      "3 - I feel more self-confident than usual.",
      "4 - I feel extremely self-confident all of the time."
    )
  }
  else if (item_name == "ASRM_3") {
    option_labels <- c(
      "0 - I do not need less sleep than usual.",
      "1 - I occasionally need less sleep than usual.",
      "2 - I often need less sleep than usual.",
      "3 - I frequently need less sleep than usual.",
      "4 - I can go all day and night without any sleep and still not feel tired."
    )
  }
  else if (item_name == "ASRM_4") {
    option_labels <- c(
      "0 - I do not talk more than usual.",
      "1 - I occasionally talk more than usual.",
      "2 - I often talk more than usual.",
      "3 - I frequently talk more than usual.",
      "4 - I talk constantly and cannot be interrupted."
    )
  }
  else if (item_name == "ASRM_5") {
    option_labels <- c(
      "0 - I have not been more active (either socially, sexually, at work, home or school) than usual.",
      "1 - I have occasionally been more active than usual.",
      "2 - I have often been more active than usual.",
      "3 - I have frequently been more active than usual.",
      "4 - I am constantly active or on the go all the time."
    )
  }

  # AUDIT-C items
  else if (item_name == "AUDITC_MOD_1") {
    option_labels <- c(
      "0 - Never",
      "1 - Monthly or less",
      "2 - 2-4 times a month",
      "3 - 2-3 times a week",
      "4 - 4 or more times a week"
    )
  }
  else if (item_name == "AUDITC_MOD_2") {
    option_labels <- c(
      "0 - 1 or 2",
      "1 - 3 or 4",
      "2 - 5 or 6",
      "3 - 7-9",
      "4 - 10 or more"
    )
  }
  else if (item_name == "AUDITC_MOD_3") {
    option_labels <- c(
      "0 - Never",
      "1 - Less than monthly",
      "2 - Monthly",
      "3 - Weekly",
      "4 - Daily or almost daily"
    )
  }

  return(option_labels)
}

# Adaptive testing parameters
delta_thetas <- c(0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05)
min_items <- 7
max_items <- 25

# ==============================================================================
# SESSION MANAGEMENT
# ==============================================================================

# In-memory session storage (use Redis in production)
sessions <- new.env()

# Create a new session
create_session <- function() {
  session_id <- paste0("sess_", as.integer(Sys.time()), "_", sample(1000:9999, 1))

  sessions[[session_id]] <- list(
    created_at = Sys.time(),
    theta = rep(0, nfact),  # Initial ability estimates
    SE_theta = rep(1, nfact),  # Initial standard errors
    responses = rep(NA, length(items)),  # Response vector
    items_administered = integer(0),  # Items already shown
    completed = FALSE
  )

  return(session_id)
}

# Get session data
get_session <- function(session_id) {
  if (!exists(session_id, envir = sessions)) {
    stop("Invalid session ID")
  }
  return(sessions[[session_id]])
}

# Update session data
update_session <- function(session_id, data) {
  sessions[[session_id]] <- data
}

# ==============================================================================
# ADAPTIVE ITEM SELECTION - Using mirtCAT helper script
# ==============================================================================

# Select next item by calling the mirtCAT helper script
# This ensures exact matching with app.R's algorithm
select_next_item <- function(session) {
  items_administered <- session$items_administered
  responses <- session$responses

  # Build JSON object with responses
  # Format: {"responses": {"item_index": response_value, ...}}
  if (length(items_administered) == 0) {
    input_data <- list(responses = list())
  } else {
    response_list <- list()
    for (i in seq_along(items_administered)) {
      item_idx <- items_administered[i]
      response_list[[as.character(item_idx)]] <- responses[item_idx]
    }
    input_data <- list(responses = response_list)
  }
  responses_json <- toJSON(input_data, auto_unbox = TRUE)

  # Call the helper script
  result <- tryCatch({
    output <- system2(
      "Rscript",
      args = c("mirtcat_helper.R", shQuote(responses_json)),
      stdout = TRUE,
      stderr = FALSE  # Don't capture stderr to keep JSON clean
    )

    # Parse the JSON output (should be clean JSON now)
    json_output <- paste(output, collapse = "")

    # Handle empty output
    if (nchar(trimws(json_output)) == 0) {
      return(list(error = "Empty output from helper script"))
    }

    fromJSON(json_output)
  }, error = function(e) {
    # Log error and return NULL
    message("Error calling mirtcat_helper.R: ", e$message)
    list(error = e$message)
  })

  # Check for errors
  if (!is.null(result$error)) {
    message("mirtcat_helper.R error: ", result$error)
    return(NULL)
  }

  # Check if assessment is complete
  if (isTRUE(result$is_complete)) {
    return(NULL)
  }

  # Return the next item index
  return(result$next_item_index)
}

# ==============================================================================
# ABILITY ESTIMATION
# ==============================================================================

# Update theta estimates after response
update_theta <- function(session, item_idx, response) {
  # Update response vector
  session$responses[item_idx] <- response
  session$items_administered <- c(session$items_administered, item_idx)

  # Re-estimate theta using Maximum A Posteriori (MAP)
  administered_items <- session$items_administered

  # Use full response pattern (with NAs for non-administered items)
  response_pattern <- session$responses

  # Use fscores for estimation with SE
  theta_est <- tryCatch({
    fscores(mod,
            response.pattern = matrix(response_pattern, nrow = 1),
            method = "MAP",
            QMC = TRUE,
            full.scores.SE = TRUE,
            theta_lim = c(-6, 6))
  }, error = function(e) {
    # Fallback to EAP if MAP fails
    fscores(mod,
            response.pattern = matrix(response_pattern, nrow = 1),
            method = "EAP",
            QMC = TRUE,
            full.scores.SE = TRUE)
  })

  # Extract theta (first nfact columns)
  session$theta <- as.numeric(theta_est[1, 1:nfact])

  # Extract SE (next nfact columns if available, otherwise use default)
  if (ncol(theta_est) >= 2 * nfact) {
    session$SE_theta <- as.numeric(theta_est[1, (nfact + 1):(2 * nfact)])
  } else {
    # Fallback: use default SE values
    session$SE_theta <- rep(1, nfact)
  }

  return(session)
}

# ==============================================================================
# RESULTS CALCULATION
# ==============================================================================

# Calculate domain scores with confidence intervals
calculate_results <- function(session) {
  theta <- session$theta
  SE_theta <- session$SE_theta
  responses <- session$responses

  z <- 1.96  # 95% CI

  results <- lapply(names(item_ranges), function(domain_name) {
    idx <- which(names(item_ranges) == domain_name)
    item_indices <- item_ranges[[domain_name]]

    # Point estimate
    theta_mat <- matrix(theta, nrow = 1, ncol = nfact)
    mean_score <- expected.test(mod, Theta = theta_mat, which.items = item_indices)

    # Upper bound (theta + SE)
    theta_plus <- theta
    theta_plus[idx] <- theta_plus[idx] + z * SE_theta[idx]
    theta_plus_mat <- matrix(theta_plus, nrow = 1, ncol = nfact)
    upper_score <- expected.test(mod, Theta = theta_plus_mat, which.items = item_indices)

    # Lower bound (theta - SE)
    theta_minus <- theta
    theta_minus[idx] <- theta_minus[idx] - z * SE_theta[idx]
    theta_minus_mat <- matrix(theta_minus, nrow = 1, ncol = nfact)
    lower_score <- expected.test(mod, Theta = theta_minus_mat, which.items = item_indices)

    # Ensure monotonicity
    l95 <- min(lower_score, upper_score)
    u95 <- max(lower_score, upper_score)

    # Clip to valid range
    max_score <- max_scores[[domain_name]]
    mean_score <- min(mean_score, max_score)
    l95 <- max(0, min(l95, max_score))
    u95 <- max(0, min(u95, max_score))

    # Get severity category
    cuts <- domain_cuts[[domain_name]]
    category <- as.character(cut(mean_score,
                                  breaks = cuts$breaks,
                                  labels = cuts$labels,
                                  include.lowest = TRUE,
                                  right = TRUE))

    # Count items answered in this domain
    items_answered <- sum(!is.na(responses[item_indices]))

    list(
      domain = domain_name,
      score = round(mean_score, 1),
      lower_95 = round(l95, 1),
      upper_95 = round(u95, 1),
      max_score = max_score,
      category = category,
      items_answered = items_answered
    )
  })

  return(results)
}

# ==============================================================================
# API ENDPOINTS
# ==============================================================================

#* @apiTitle MCAT Adaptive Assessment API
#* @apiDescription RESTful API for adaptive mental health assessment

#* Enable CORS
#* @filter cors
function(req, res) {
  res$setHeader("Access-Control-Allow-Origin", "*")
  res$setHeader("Access-Control-Allow-Methods", "GET, POST, OPTIONS")
  res$setHeader("Access-Control-Allow-Headers", "Content-Type")

  if (req$REQUEST_METHOD == "OPTIONS") {
    res$status <- 200
    return(list())
  }

  plumber::forward()
}

#* Start a new assessment session
#* @post /start
function() {
  session_id <- create_session()

  list(
    session_id = session_id,
    message = "Assessment started",
    total_items = length(items),
    min_items = min_items,
    max_items = max_items
  )
}

#* Get the next question
#* @get /next-question
function(req, res, session_id = NULL) {
  # Extract session_id from query parameters if not provided
  if (is.null(session_id)) {
    session_id <- req$args$session_id
  }

  session <- get_session(session_id)

  if (session$completed) {
    return(list(
      completed = TRUE,
      message = "Assessment already completed"
    ))
  }

  # Select next item
  next_item_idx <- select_next_item(session)

  if (is.null(next_item_idx)) {
    # Assessment complete
    session$completed <- TRUE
    update_session(session_id, session)

    return(list(
      completed = TRUE,
      items_administered = length(session$items_administered),
      message = "Assessment complete"
    ))
  }

  # Get item details
  item_name <- items[next_item_idx]
  item_k <- K[next_item_idx]
  item_min <- mins[next_item_idx]

  # Get actual question text
  question_text <- if (item_name %in% names(item_labels)) {
    item_labels[[item_name]]
  } else {
    item_name  # Fallback to item name if no label found
  }

  # Get option labels for this item
  option_labels <- get_option_labels(item_name, item_k, item_min)

  # Create response options with actual labels
  options <- list()
  for (j in 0:(item_k - 1)) {
    options[[j + 1]] <- list(
      label = option_labels[j + 1],
      value = item_min + j
    )
  }

  list(
    completed = FALSE,
    item_index = next_item_idx,
    item_name = item_name,
    question_text = question_text,
    progress = length(session$items_administered) / max_items,
    items_completed = length(session$items_administered),
    options = options
  )
}

#* Submit an answer
#* @parser json
#* @post /submit-answer
function(req, res) {
  # Manually parse the JSON body to avoid parameter naming conflicts
  body_text <- if (is.raw(req$postBody)) {
    rawToChar(req$postBody)
  } else {
    as.character(req$postBody)
  }

  body <- jsonlite::fromJSON(body_text)

  session_id <- as.character(body$session_id)
  item_index <- as.integer(body$item_index)
  response_val <- as.numeric(body$response)

  session <- get_session(session_id)

  # Update theta estimates
  session <- update_theta(session, item_index, response_val)
  update_session(session_id, session)

  list(
    success = TRUE,
    items_completed = length(session$items_administered),
    message = "Response recorded"
  )
}

#* Undo last answer (go back to previous question)
#* @parser json
#* @post /undo-last
function(req, res) {
  body_text <- if (is.raw(req$postBody)) {
    rawToChar(req$postBody)
  } else {
    as.character(req$postBody)
  }

  body <- jsonlite::fromJSON(body_text)
  session_id <- as.character(body$session_id)
  session <- get_session(session_id)

  n_administered <- length(session$items_administered)
  if (n_administered == 0) {
    return(list(
      success = FALSE,
      message = "No items to undo"
    ))
  }

  # Remove the last administered item and clear its response
  last_item <- session$items_administered[n_administered]
  session$responses[last_item] <- NA
  session$items_administered <- session$items_administered[-n_administered]
  session$completed <- FALSE

  # Re-estimate theta if there are remaining items, otherwise reset
  if (length(session$items_administered) > 0) {
    response_pattern <- session$responses
    theta_est <- tryCatch({
      fscores(mod,
              response.pattern = matrix(response_pattern, nrow = 1),
              method = "MAP",
              QMC = TRUE,
              full.scores.SE = TRUE,
              theta_lim = c(-6, 6))
    }, error = function(e) {
      fscores(mod,
              response.pattern = matrix(response_pattern, nrow = 1),
              method = "EAP",
              QMC = TRUE,
              full.scores.SE = TRUE)
    })
    session$theta <- as.numeric(theta_est[1, 1:nfact])
    if (ncol(theta_est) >= 2 * nfact) {
      session$SE_theta <- as.numeric(theta_est[1, (nfact + 1):(2 * nfact)])
    }
  } else {
    session$theta <- rep(0, nfact)
    session$SE_theta <- rep(1, nfact)
  }

  update_session(session_id, session)

  list(
    success = TRUE,
    items_completed = length(session$items_administered),
    message = "Last response removed"
  )
}

#* Get assessment results
#* @get /results
function(req, res, session_id = NULL) {
  # Extract session_id from query parameters if not provided
  if (is.null(session_id)) {
    session_id <- req$args$session_id
  }

  session <- get_session(session_id)

  if (!session$completed) {
    return(list(
      error = "Assessment not yet completed",
      items_completed = length(session$items_administered),
      min_items = min_items
    ))
  }

  results <- calculate_results(session)

  list(
    session_id = session_id,
    items_completed = length(session$items_administered),
    domains = results,
    timestamp = Sys.time()
  )
}

#* Health check endpoint
#* @get /health
function() {
  list(
    status = "healthy",
    timestamp = Sys.time(),
    model_loaded = !is.null(mod),
    total_items = length(items)
  )
}