Search Analytics Dashboard

Setup

Mix.install([
  {:meilisearch, "~> 0.8"},
  {:vega_lite, "~> 0.1.6"},
  {:kino, "~> 0.8.0"}
])

alias VegaLite, as: Vl

Connect to Meilisearch

meilisearch_host = System.get_env("MEILISEARCH_HOST", "http://localhost:7700")
meilisearch_key = System.get_env("MEILISEARCH_KEY", "")

{:ok, client} = Meilisearch.Client.new(meilisearch_host, meilisearch_key)

Search Analytics Visualization

# Sample data - in a real app, this would come from your analytics storage
search_data = [
  %{term: "example", count: 45},
  %{term: "search", count: 30},
  %{term: "analytics", count: 25},
  %{term: "elixir", count: 20}
]

Vl.new(width: 600, height: 400)
|> Vl.data_from_values(search_data)
|> Vl.mark(:bar)
|> Vl.encode_field(:x, "term", type: :nominal, title: "Search Term")
|> Vl.encode_field(:y, "count", type: :quantitative, title: "Number of Searches")
|> Vl.config(view: [stroke: nil])
|> Vl.config(axis: [grid: false])

Real-time Search Monitor

Kino.VegaLite.periodically(
  %{data: [], timestamp: nil},
  100,
  fn state ->
    # Simulate real-time data - replace with actual metrics in production
    new_count = :rand.uniform(100)
    timestamp = DateTime.utc_now()
    
    new_data =
      [%{time: timestamp, searches: new_count} | state.data]
      |> Enum.take(50)

    spec =
      Vl.new(width: 600, height: 300)
      |> Vl.data_from_values(new_data)
      |> Vl.mark(:line)
      |> Vl.encode_field(:x, "time", type: :temporal, title: "Time")
      |> Vl.encode_field(:y, "searches", type: :quantitative, title: "Searches/Second")

    {spec, %{state | data: new_data, timestamp: timestamp}}
  end
)