Added in FastAPI 0.134.0.

///

## Use Cases { #use-cases }

You could use this if you want to stream pure strings, for example directly from the output of an **AI LLM** service.

You could also use it to stream **large binary files**, where you stream each chunk of data as you read it, without having to read it all in memory at once.

You could also stream **video** or **audio** this way, it could even be generated as you process and send it.

- All aggregation, conditional, type-conversion and string functions are supported.
- JSON path expressions such as `FROM S3Object[*].path` are not yet evaluated.
- Large numbers (outside of the signed 64-bit range) are not yet supported.

                                                   TF_Status* status);

// Returns the shape of the Tensor referenced by `output` in `graph`
// into `dims`. `dims` must be an array large enough to hold `num_dims`
// entries (e.g., the return value of TF_GraphGetTensorNumDims).
//
// If the number of dimensions in the shape is unknown or the shape is

        assertEquals("value", targetMap.get("new.param"));
        assertEquals("true", targetMap.get("config.setting"));
    }

    @Test
    public void test_performanceAndBoundary() {
        // Test with large input
        StringBuilder largeInput = new StringBuilder();
        for (int i = 0; i < 1000; i++) {
            largeInput.append("key").append(i).append("=value").append(i).append("\n");
        }

			return fmt.Errorf("Default retention period too large for 'Days' %d", *retention.Days)
		}
	} else if *retention.Years == 0 {
		return fmt.Errorf("Default retention period must be a positive integer value for 'Years'")
	} else if *retention.Years > maximumRetentionYears {
		return fmt.Errorf("Default retention period too large for 'Years' %d", *retention.Years)
	}

	*dr = DefaultRetention(retention)

 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.llm;

import java.util.List;
import java.util.Map;

/**
 * Interface for LLM (Large Language Model) clients.
 * Implementations provide integration with different LLM providers
 * such as Ollama, OpenAI, and Google Gemini.
 *
 * In addition to low-level chat operations, this interface defines

                if (params != null && params.size() > 100) {
                    return createMockRescorerBuilder();
                }
                return null;
            }
        };

        // Test with large number of parameters
        Map<String, Object> largeParams = new HashMap<>();
        for (int i = 0; i < 150; i++) {
            largeParams.put("key" + i, "value" + i);
        }

 *     process(part.headers, part.body)
 *   }
 * }
 * ```
 *
 * Note that [nextPart] will skip any unprocessed data from the preceding part. If the preceding
 * part is particularly large or if the underlying source is particularly slow, the [nextPart] call
 * may be slow!
 *
 * Closing a part **does not** close this multipart reader; callers must explicitly close this with
 * [close].
 *

        // Prepare test data
        ByteBuffer bb = ByteBuffer.wrap(testBuffer).order(ByteOrder.LITTLE_ENDIAN);

        // Header
        bb.putShort((short) 3); // version
        bb.putShort((short) 100); // size (large enough for all strings)
        bb.putShort((short) 1); // serverType
        bb.putShort((short) 0); // rflags (no name list)
        bb.putShort((short) 5); // proximity
        bb.putShort((short) 300); // ttl

 * particular example can be written as just:
 *
 * {@snippet :
 * ContiguousSet.closed(5, 42)
 * }
 *
 * <p><b>Warning:</b> Be extremely careful what you do with conceptually large instances (such as
 * {@code ContiguousSet.create(Range.greaterThan(0), DiscreteDomain.integers()}). Certain operations
 * on such a set can be performed efficiently, but others (such as {@link Set#hashCode} or {@link