We welcome contributions to Fess Crawler! Please follow these guidelines:

1. **Fork** the repository
2. **Create** a feature branch (`git checkout -b feature/amazing-feature`)
3. **Commit** your changes (`git commit -m 'Add amazing feature'`)
4. **Push** to the branch (`git push origin feature/amazing-feature`)
5. **Open** a Pull Request

### Development Setup

```bash
# Clone the repository

      - [kube-apiserver:](#kube-apiserver-2)
      - [kube-scheduler:](#kube-scheduler-1)
      - [kube-proxy:](#kube-proxy-1)
      - [Features graduated to beta:](#features-graduated-to-beta)
      - [Features graduated to GA:](#features-graduated-to-ga)
    - [Feature](#feature-5)
      - [Metrics:](#metrics)
    - [Other (Bug, Cleanup or Flake)](#other-bug-cleanup-or-flake-1)
  - [Dependencies](#dependencies-19)

        client.setChatResponse("{\"intent\":\"faq\",\"query\":\"Fess features\",\"reasoning\":\"FAQ question\"}");

        // Call the original single-arg method
        final IntentDetectionResult result = client.detectIntent("What are Fess features?");

        assertEquals(ChatIntent.FAQ, result.getIntent());
        assertEquals("Fess features", result.getQuery());

### SIG-instrumentation

No feature work, but a large refactoring of metrics-server as well as a number of bug fixes.

### SIG-node

SIG-node graduated the PodShareProcessNamespace feature from alpha to beta.  This feature allows a pod spec to request that all containers in a pod share a common process namespaces.

Two alpha features were also added in this release.

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import jcifs.smb.SmbException;

/**
 * Validator for SMB server responses to prevent buffer overflow and injection attacks.
 *
 * Features:
 * - Buffer bounds checking
 * - Integer overflow prevention
 * - Size validation
 * - Protocol compliance checking
 * - Malformed response detection
 */
public class ServerResponseValidator {

The same way as with Pydantic models, you declare class attributes with type annotations, and possibly default values.

You can use all the same validation features and tools you use for Pydantic models, like different data types and additional validations with `Field()`.

{* ../../docs_src/settings/tutorial001_py310.py hl[2,5:8,11] *}

/// tip

        "@platforms//cpu:x86_64",
    ],
    visibility = ["//visibility:public"],
)

# Features that are default ON are handled differently below.
#
config_setting(
    name = "no_gcp_support",
    define_values = {"no_gcp_support": "true"},
    visibility = ["//visibility:public"],
)

# Experimental features
config_setting(
    name = "stackdriver_support",
    define_values = {"stackdriver_support": "true"},

   []

 * phase 2, with optional plugin processing

   ** Build up a raw model by re-reading the file and enriching it based on information available in the reactor. Some features:

      *** Resolve version of versionless parents based on relativePath (including ci-friendly versions)

      *** Resolve version of versionless dependencies that are part of the reactor

   []

 *       doesn't offer a way to wait for multiple producers to all report that they're "ready," nor
 *       does it offer a way to batch multiple events from a single producer together.
 *   <li>It doesn't support backpressure and other features needed for resilience.
 *   <li>It doesn't provide much control of threading.
 *   <li>It doesn't offer much monitoring.
 *   <li>It doesn't propagate exceptions, so apps don't have a way to react to them.

### Feature

- Add cloud-controller-manager feature gate CloudControllerManagerWatchBasedRoutesReconciliation ([#131220](https://github.com/kubernetes/kubernetes/pull/131220), [@lukasmetzner](https://github.com/lukasmetzner)) [SIG API Machinery and Cloud Provider]