Add comprehensive frontend UI and distributed infrastructure

Frontend Enhancements:
- Complete React TypeScript frontend with modern UI components
- Distributed workflows management interface with real-time updates
- Socket.IO integration for live agent status monitoring
- Agent management dashboard with cluster visualization
- Project management interface with metrics and task tracking
- Responsive design with proper error handling and loading states

Backend Infrastructure:
- Distributed coordinator for multi-agent workflow orchestration
- Cluster management API with comprehensive agent operations
- Enhanced database models for agents and projects
- Project service for filesystem-based project discovery
- Performance monitoring and metrics collection
- Comprehensive API documentation and error handling

Documentation:
- Complete distributed development guide (README_DISTRIBUTED.md)
- Comprehensive development report with architecture insights
- System configuration templates and deployment guides

The platform now provides a complete web interface for managing the distributed AI cluster
with real-time monitoring, workflow orchestration, and agent coordination capabilities.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

frontend/node_modules/d3-array/src/bin.js

@@ -0,0 +1,125 @@
+import {slice} from "./array.js";
+import bisect from "./bisect.js";
+import constant from "./constant.js";
+import extent from "./extent.js";
+import identity from "./identity.js";
+import nice from "./nice.js";
+import ticks, {tickIncrement} from "./ticks.js";
+import sturges from "./threshold/sturges.js";
+
+export default function bin() {
+  var value = identity,
+      domain = extent,
+      threshold = sturges;
+
+  function histogram(data) {
+    if (!Array.isArray(data)) data = Array.from(data);
+
+    var i,
+        n = data.length,
+        x,
+        step,
+        values = new Array(n);
+
+    for (i = 0; i < n; ++i) {
+      values[i] = value(data[i], i, data);
+    }
+
+    var xz = domain(values),
+        x0 = xz[0],
+        x1 = xz[1],
+        tz = threshold(values, x0, x1);
+
+    // Convert number of thresholds into uniform thresholds, and nice the
+    // default domain accordingly.
+    if (!Array.isArray(tz)) {
+      const max = x1, tn = +tz;
+      if (domain === extent) [x0, x1] = nice(x0, x1, tn);
+      tz = ticks(x0, x1, tn);
+
+      // If the domain is aligned with the first tick (which it will by
+      // default), then we can use quantization rather than bisection to bin
+      // values, which is substantially faster.
+      if (tz[0] <= x0) step = tickIncrement(x0, x1, tn);
+
+      // If the last threshold is coincident with the domain’s upper bound, the
+      // last bin will be zero-width. If the default domain is used, and this
+      // last threshold is coincident with the maximum input value, we can
+      // extend the niced upper bound by one tick to ensure uniform bin widths;
+      // otherwise, we simply remove the last threshold. Note that we don’t
+      // coerce values or the domain to numbers, and thus must be careful to
+      // compare order (>=) rather than strict equality (===)!
+      if (tz[tz.length - 1] >= x1) {
+        if (max >= x1 && domain === extent) {
+          const step = tickIncrement(x0, x1, tn);
+          if (isFinite(step)) {
+            if (step > 0) {
+              x1 = (Math.floor(x1 / step) + 1) * step;
+            } else if (step < 0) {
+              x1 = (Math.ceil(x1 * -step) + 1) / -step;
+            }
+          }
+        } else {
+          tz.pop();
+        }
+      }
+    }
+
+    // Remove any thresholds outside the domain.
+    // Be careful not to mutate an array owned by the user!
+    var m = tz.length, a = 0, b = m;
+    while (tz[a] <= x0) ++a;
+    while (tz[b - 1] > x1) --b;
+    if (a || b < m) tz = tz.slice(a, b), m = b - a;
+
+    var bins = new Array(m + 1),
+        bin;
+
+    // Initialize bins.
+    for (i = 0; i <= m; ++i) {
+      bin = bins[i] = [];
+      bin.x0 = i > 0 ? tz[i - 1] : x0;
+      bin.x1 = i < m ? tz[i] : x1;
+    }
+
+    // Assign data to bins by value, ignoring any outside the domain.
+    if (isFinite(step)) {
+      if (step > 0) {
+        for (i = 0; i < n; ++i) {
+          if ((x = values[i]) != null && x0 <= x && x <= x1) {
+            bins[Math.min(m, Math.floor((x - x0) / step))].push(data[i]);
+          }
+        }
+      } else if (step < 0) {
+        for (i = 0; i < n; ++i) {
+          if ((x = values[i]) != null && x0 <= x && x <= x1) {
+            const j = Math.floor((x0 - x) * step);
+            bins[Math.min(m, j + (tz[j] <= x))].push(data[i]); // handle off-by-one due to rounding
+          }
+        }
+      }
+    } else {
+      for (i = 0; i < n; ++i) {
+        if ((x = values[i]) != null && x0 <= x && x <= x1) {
+          bins[bisect(tz, x, 0, m)].push(data[i]);
+        }
+      }
+    }
+
+    return bins;
+  }
+
+  histogram.value = function(_) {
+    return arguments.length ? (value = typeof _ === "function" ? _ : constant(_), histogram) : value;
+  };
+
+  histogram.domain = function(_) {
+    return arguments.length ? (domain = typeof _ === "function" ? _ : constant([_[0], _[1]]), histogram) : domain;
+  };
+
+  histogram.thresholds = function(_) {
+    return arguments.length ? (threshold = typeof _ === "function" ? _ : constant(Array.isArray(_) ? slice.call(_) : _), histogram) : threshold;
+  };
+
+  return histogram;
+}