Tests added here will be seen by all designers of language specific prompts.

Use as follows:

* Have a language specific prompt - `docs/{language code}/llm-prompt.md`.

   * |---------|
   * }
   */
  private static final SuccessorsFunction<Character> TWO_CYCLES_GRAPH =
      createDirectedGraph("ab", "ac", "bc", "cd", "da");

  /**
   * A tree-shaped graph that looks as follows (all edges are directed facing downwards):
   *
   * {@snippet :
   *        h
   *       /|\
   *      / | \
   *     /  |  \
   *    d   e   g
   *   /|\      |
   *  / | \     |

        bb.putShort((short) 1); // version
        bb.putShort((short) 24); // size
        bb.putShort((short) 1); // serverType
        bb.putShort((short) 0); // rflags

        // Node string immediately follows header
        String node = "\\\\SERVER\\SHARE";
        bb.put(node.getBytes(StandardCharsets.UTF_16LE));
        bb.putShort((short) 0);

        // Decode

 * For other types, the conversion uses the string representation of the source object.
 * </p>
 * <p>
 * If no pattern is specified, the pattern used for conversion depends on the locale as follows:
 * </p>
 * <table border="1">
 * <caption>Conversion Patterns</caption>
 * <tr>
 * <th>Category</th>
 * <th>Pattern</th>
 * <th>Example for {@link Locale#JAPANESE}</th>
 * </tr>
 * <tr>

 * For other types, the converted object is created from the string representation of the source object.
 * </p>
 * <p>
 * If no pattern is specified, the pattern used for conversion depends on the locale as follows:
 * </p>
 * <table border="1">
 * <caption>Conversion Patterns</caption>
 * <tr>
 * <th>Category</th>
 * <th>Pattern</th>
 * <th>Example for {@link Locale#JAPANESE}</th>
 * </tr>
 * <tr>

### HTML abbr elements

Translate HTML abbr elements (`<abbr title="description">text</abbr>`) as follows:

- The text inside abbr tag may be surrounded by further HTML or Markdown markup or quotes, for example <code>text</code> or `text` or "text". Preserve markup and only translate visible text inside the abbr element.

## Introduction

MinIO provides a custom STS API that allows integration with LDAP based corporate environments including Microsoft Active Directory. The MinIO server uses a separate LDAP service account to lookup user information. The login flow for a user is as follows:

- User provides their AD/LDAP username and password to the STS API.

    ```bash
    docker run -it --rm -v $PWD:/tmp -w /tmp tensorflow/build:2.15-python3.10
    ```

    Once you have the packages installed, you can run a specific unit test in
    bazel by doing as follows:

    ```bash
    export flags="--config=linux -k"
    ```

    If the tests are to be run on the GPU:

    *   For TensorFlow versions starting from v.2.18.0: Add the `cuda` option
        flag.

      },
      "SourceSelectionCriteria": {
        "ReplicaModifications": {
          "Status": "Enabled"
        }
      }
    }
  ]
}
```

        }

        // Increment rotation counter for tracking and key derivation
        rotationCount++;

        // SMB3-compliant key rotation: Use rotation counter as per SMB3 specification
        // This follows Microsoft's approach for predictable but unique key derivation
        byte[] modifiedSessionKey = new byte[sessionKey.length + 8];
        System.arraycopy(sessionKey, 0, modifiedSessionKey, 0, sessionKey.length);