Package com.braintrustdata.api.models

Class InsertDatasetEvent

    • Constructor Detail

    • Method Detail

      • id

         final Optional<String> id()

        A unique identifier for the dataset event. If you don't provide one, BrainTrust will generate one for you

      • _isMerge

         final Optional<Boolean> _isMerge()

        The _is_merge field controls how the row is merged with any existing row with the same id in the DB. By default (or when set to false), the existing row is completely replaced by the new row. When set to true, the new row is deep-merged into the existing row, if one is found. If no existing row is found, the new row is inserted as is.

        For example, say there is an existing row in the DB {"id": "foo", "input": {"a": 5, "b": 10}}. If we merge a new row as {"_is_merge": true, "id": "foo", "input": {"b": 11, "c": 20}}, the new row will be {"id": "foo", "input": {"a": 5, "b": 11, "c": 20}}. If we replace the new row as {"id": "foo", "input": {"b": 11, "c": 20}}, the new row will be {"id": "foo", "input": {"b": 11, "c": 20}}

      • _mergePaths

         final Optional<List<List<String>>> _mergePaths()

        The _merge_paths field allows controlling the depth of the merge, when _is_merge=true. _merge_paths is a list of paths, where each path is a list of field names. The deep merge will not descend below any of the specified merge paths.

        For example, say there is an existing row in the DB {"id": "foo", "input": {"a": {"b": 10}, "c": {"d": 20}}, "output": {"a": 20}}. If we merge a new row as {"_is_merge": true, "_merge_paths": [["input", "a"], ["output"]], "input": {"a": {"q": 30}, "c": {"e": 30}, "bar": "baz"}, "output": {"d": 40}}, the new row will be {"id": "foo": "input": {"a": {"q": 30}, "c": {"d": 20, "e": 30}, "bar": "baz"}, "output": {"d": 40}}. In this case, due to the merge paths, we have replaced input.a and output, but have still deep-merged input and input.c.

      • _objectDelete

         final Optional<Boolean> _objectDelete()

        Pass _object_delete=true to mark the dataset event deleted. Deleted events will not show up in subsequent fetches for this dataset

      • _parentId

         final Optional<String> _parentId()

        DEPRECATED: The _parent_id field is deprecated and should not be used. Support for _parent_id will be dropped in a future version of Braintrust. Log span_id, root_span_id, and span_parents explicitly instead.

        Use the _parent_id field to create this row as a subspan of an existing row. Tracking hierarchical relationships are important for tracing (see the guide for full details).

        For example, say we have logged a row {"id": "abc", "input": "foo", "output": "bar", "expected": "boo", "scores": {"correctness": 0.33}}. We can create a sub-span of the parent row by logging {"_parent_id": "abc", "id": "llm_call", "input": {"prompt": "What comes after foo?"}, "output": "bar", "metrics": {"tokens": 1}}. In the webapp, only the root span row "abc" will show up in the summary view. You can view the full trace hierarchy (in this case, the "llm_call" row) by clicking on the "abc" row.

        If the row is being merged into an existing row, this field will be ignored.

      • _expected

         final JsonValue _expected()

        The output of your application, including post-processing (an arbitrary, JSON serializable object)

      • _input

         final JsonValue _input()

        The argument that uniquely define an input case (an arbitrary, JSON serializable object)

      • metadata

         final Optional<InsertDatasetEvent.Metadata> metadata()

        A dictionary with additional data about the test example, model outputs, or just about anything else that's relevant, that you can use to help find and analyze examples later. For example, you could log the prompt, example's id, or anything else that would be useful to slice/dice later. The values in metadata can be any JSON-serializable type, but its keys must be strings

      • rootSpanId

         final Optional<String> rootSpanId()

        Use span_id, root_span_id, and span_parents instead of _parent_id, which is now deprecated. The span_id is a unique identifier describing the row's place in the a trace, and the root_span_id is a unique identifier for the whole trace. See the guide for full details.

        For example, say we have logged a row {"id": "abc", "span_id": "span0", "root_span_id": "root_span0", "input": "foo", "output": "bar", "expected": "boo", "scores": {"correctness": 0.33}}. We can create a sub-span of the parent row by logging {"id": "llm_call", "span_id": "span1", "root_span_id": "root_span0", "span_parents": ["span0"], "input": {"prompt": "What comes after foo?"}, "output": "bar", "metrics": {"tokens": 1}}. In the webapp, only the root span row "abc" will show up in the summary view. You can view the full trace hierarchy (in this case, the "llm_call" row) by clicking on the "abc" row.

        If the row is being merged into an existing row, this field will be ignored.

      • spanId

         final Optional<String> spanId()

        Use span_id, root_span_id, and span_parents instead of _parent_id, which is now deprecated. The span_id is a unique identifier describing the row's place in the a trace, and the root_span_id is a unique identifier for the whole trace. See the guide for full details.

        For example, say we have logged a row {"id": "abc", "span_id": "span0", "root_span_id": "root_span0", "input": "foo", "output": "bar", "expected": "boo", "scores": {"correctness": 0.33}}. We can create a sub-span of the parent row by logging {"id": "llm_call", "span_id": "span1", "root_span_id": "root_span0", "span_parents": ["span0"], "input": {"prompt": "What comes after foo?"}, "output": "bar", "metrics": {"tokens": 1}}. In the webapp, only the root span row "abc" will show up in the summary view. You can view the full trace hierarchy (in this case, the "llm_call" row) by clicking on the "abc" row.

        If the row is being merged into an existing row, this field will be ignored.

      • spanParents

         final Optional<List<String>> spanParents()

        Use span_id, root_span_id, and span_parents instead of _parent_id, which is now deprecated. The span_id is a unique identifier describing the row's place in the a trace, and the root_span_id is a unique identifier for the whole trace. See the guide for full details.

        For example, say we have logged a row {"id": "abc", "span_id": "span0", "root_span_id": "root_span0", "input": "foo", "output": "bar", "expected": "boo", "scores": {"correctness": 0.33}}. We can create a sub-span of the parent row by logging {"id": "llm_call", "span_id": "span1", "root_span_id": "root_span0", "span_parents": ["span0"], "input": {"prompt": "What comes after foo?"}, "output": "bar", "metrics": {"tokens": 1}}. In the webapp, only the root span row "abc" will show up in the summary view. You can view the full trace hierarchy (in this case, the "llm_call" row) by clicking on the "abc" row.

        If the row is being merged into an existing row, this field will be ignored.

      • _id

         final JsonField<String> _id()

        Returns the raw JSON value of id.

        Unlike id, this method doesn't throw if the JSON field has an unexpected type.

      • _tags

         final JsonField<List<String>> _tags()

        Returns the raw JSON value of tags.

        Unlike tags, this method doesn't throw if the JSON field has an unexpected type.