Add more exmaples and fix CI

examples/06_watchdog/main.cpp

@@ -1,3 +1,90 @@
+// Example 06 — Watchdog & Diagnostics (+ optional web debug UI)
+//
+// A four-stage pipeline with deliberately uneven node speeds:
+//
+//  [source] --int--> [fast_filter] --int--> [slow_transform] --int--> [sink]
+//
+// The watchdog fires every second and prints a full diagnostics report:
+//   - frames processed, throughput fps, exec time, blocked time per node
+//   - channel fill %, peak fill %, pushes, overflows, bandwidth
+//   - bottleneck hint (node with highest avg exec time)
+//
+// "slow_transform" sleeps 30 ms per item, making it the obvious bottleneck.
+// Watch the channel upstream of it saturate and the fps converge to ~33.
+//
+// Build with -DKPN_WEB_DEBUG=ON to also get a live D3 graph at localhost:9090.
+
 #include <kpn/kpn.hpp>
-// TODO: implement example
-int main() { return 0; }
+#include <chrono>
+#include <cmath>
+#include <iostream>
+#include <thread>
+
+// ── Node functions ────────────────────────────────────────────────────────────
+
+static int source() {
+    // Produces at ~50 fps — faster than slow_transform (33 fps) so the
+    // channel between filter and slow gradually fills, but not catastrophically
+    std::this_thread::sleep_for(std::chrono::milliseconds(20));
+    static int n = 0;
+    return ++n;
+}
+
+static int fast_filter(int x) {
+    // Trivial work: ~0.1 ms
+    return (x % 2 == 0) ? x : x + 1;
+}
+
+static int slow_transform(int x) {
+    // Simulates expensive processing (e.g. a neural net inference step)
+    std::this_thread::sleep_for(std::chrono::milliseconds(30));
+    return x * x;
+}
+
+static void sink(int x) {
+    // Print every 10th result to avoid flooding the terminal
+    if (x % 100 < 4)
+        std::cout << "[sink] " << x << '\n';
+}
+
+// ── main ──────────────────────────────────────────────────────────────────────
+
+int main() {
+    using namespace kpn;
+
+    // Larger capacity buffers so the fast nodes don't immediately overflow
+    auto src   = make_node<source>         (out<"v">{},    16);
+    auto filt  = make_node<fast_filter>    (in<"v">{}, out<"v">{}, 16);
+    auto slow  = make_node<slow_transform> (in<"v">{}, out<"v">{}, 8);
+    auto snk   = make_node<sink>           (in<"v">{},     8);
+
+    Network net;
+
+    // Watchdog fires every 1 second — prints the built-in diagnostics table
+    // including the "Bottleneck hint" line
+    net.set_watchdog_interval(std::chrono::milliseconds(1000));
+
+    net.add("source", src)
+       .add("filter", filt)
+       .add("slow",   slow)
+       .add("sink",   snk)
+       .connect("source", src.template output<"v">(),  "filter", filt.template input<"v">())
+       .connect("filter", filt.template output<"v">(), "slow",   slow.template input<"v">())
+       .connect("slow",   slow.template output<"v">(), "sink",   snk.template input<"v">())
+       .build();
+
+    std::cout << "Running for 30 seconds — watch 'slow' become the bottleneck.\n"
+              << "Watchdog diagnostics print every 1 second.\n";
+#ifdef KPN_WEB_DEBUG
+    net.set_web_debug_port(9090);
+    std::cout << "Web debug UI: http://localhost:9090  (live graph, auto-updates every 500 ms)\n";
+#endif
+    std::cout << '\n';
+
+    net.start();
+    std::this_thread::sleep_for(std::chrono::seconds(30));
+    net.stop();
+
+    std::cout << "\n=== Final diagnostics ===\n";
+    net.print_diagnostics();
+}