.build();
```

### Request Parameters

```java
SuggestResponse response = suggester.suggest()
    .setQuery("search term")
    .setSize(10)                           // max results
    .setTags(new String[]{"category"})      // filter by tags
    .setRoles(new String[]{"user"})         // filter by roles  
    .setLanguages(new String[]{"en", "ja"}) // language preference

        List<Map<String, Object>> logs = JsonPath.from(response).getList("response.logs");

        logger.info("Filtered logs by job name: {}", logs);

        // Verify all returned logs contain the search term in job name
        for (Map<String, Object> log : logs) {
            String jobName = log.get("job_name").toString();
            assertTrue(jobName.contains(NAME_PREFIX), "Job name should contain '" + NAME_PREFIX + "'");

    public void test_convertWithFieldCheck_addsToContext() {
        FessConfig fessConfig = ComponentUtil.getFessConfig();
        QueryContext context = new QueryContext("test", true);

        String queryText = "search term";
        queryCommand.convertWithFieldCheck(fessConfig, context, "title", queryText, 1.0f,
                (field, boost) -> QueryBuilders.matchQuery(field, queryText).boost(boost),

        List<Map<String, Object>> logs = JsonPath.from(response).getList("response.logs");

        logger.info("Filtered logs by URL: {}", logs);

        // Verify all returned logs contain the search term in URL
        for (Map<String, Object> log : logs) {
            String url = log.get("url").toString();
            assertTrue(url.contains("failure"), "URL should contain 'failure'");
        }

covering security practices for the entirety of the TensorFlow ecosystem.

## TensorFlow models are programs

TensorFlow
[**models**](https://developers.google.com/machine-learning/glossary/#model) (to
use a term commonly used by machine learning practitioners) are expressed as
programs that TensorFlow executes. TensorFlow programs are encoded as
computation
[**graphs**](https://developers.google.com/machine-learning/glossary/#graph).

For "synchronous" (contrary to "asynchronous") they commonly also use the term "sequential", because the computer / program follows all the steps in sequence before switching to a different task, even if those steps involve waiting.

### Concurrency and Burgers { #concurrency-and-burgers }

    result of warranty, support, indemnity or liability terms You offer.

    3.5. Distribution of Executable Versions.

    You may distribute the Executable form of the Covered Software under
    the terms of this License or under the terms of a license of Your
    choice, which may contain terms different from this License,
    provided that You are in compliance with the terms of this License

This is a not complete and not normative list of (mostly) technical terms seen in the docs. It may be helpful for the prompt designer to figure out for which terms the LLM needs a helping hand. For example when it keeps reverting a good translation to a suboptimal translation. Or when it has problems conjugating/declinating a term in your language.

See e.g. section `### List of English terms and their preferred German translations` in `docs/de/llm-prompt.md`.

    /** The key of the message: Label */
    public static final String LABELS_TARGET_LABEL = "{labels.targetLabel}";

    /** The key of the message: Term */
    public static final String LABELS_TERM = "{labels.term}";

    /** The key of the message: Fields */
    public static final String LABELS_FIELDS = "{labels.fields}";

    /** The key of the message: Extended Query */

pkg go/types, method (*TypeList) Types() iter.Seq[Type] #66626
pkg go/types, method (*TypeParamList) TypeParams() iter.Seq[*TypeParam] #66626
pkg go/types, method (*Union) Terms() iter.Seq[*Term] #66626
pkg hash/maphash, func Comparable[$0 comparable](Seed, $0) uint64 #54670
pkg hash/maphash, func WriteComparable[$0 comparable](*Hash, $0) #54670