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This page provides a complete, auto-generated reference for the Braintrust Python SDK. For usage guidance on important APIs, see the API Reference. Also see the Braintrust Python SDK on GitHub.

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Requirements

  • Python 3.10 or higher

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Installation

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Functions

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Eval

A function you can use to define an evaluator. This is a convenience wrapper around the Evaluator class.
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str
The name of the evaluator. This corresponds to a project name in Braintrust.
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EvalData[Input, Output]
Returns an iterator over the evaluation dataset. Each element of the iterator should be a EvalCase.
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EvalTask[Input, Output]
Runs the evaluation task on a single input. The hooks object can be used to add metadata to the evaluation.
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Sequence[EvalScorer[Input, Output]]
A list of scorers to evaluate the results of the task. Each scorer can be a Scorer object or a function
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Optional[str]
(Optional) Experiment name. If not specified, a name will be generated automatically.
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int
The number of times to run the evaluator per input. This is useful for evaluating applications that
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Optional[Metadata]
(Optional) A dictionary with additional data about the test example, model outputs, or just about
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bool
(Optional) Whether the experiment should be public. Defaults to false.
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bool
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Optional[ReporterDef[Input, Output, EvalReport]]
(Optional) A reporter that takes an evaluator and its result and returns a report.
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Optional[float]
(Optional) The duration, in seconds, after which to time out the evaluation.
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Optional[int]
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Optional[str]
(Optional) If specified, uses the given project ID instead of the evaluator’s name to identify the project.
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Optional[str]
An optional experiment name to use as a base. If specified, the new experiment will be
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Optional[str]
An optional experiment id to use as a base. If specified, the new experiment will be
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Optional[GitMetadataSettings]
Optional settings for collecting git metadata. By default, will collect all git metadata fields allowed in org-level settings.
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Literal['all', 'none', 'some']
required
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NotRequired[Sequence[Literal['commit', 'branch', 'tag', 'dirty', 'author_name', 'author_email', 'commit_message', 'commit_time', 'git_diff']]]
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Optional[RepoInfo]
Optionally explicitly specify the git metadata for this experiment. This takes precedence over git_metadata_settings if specified.
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NotRequired[Optional[str]]
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NotRequired[Optional[str]]
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NotRequired[Optional[str]]
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NotRequired[Optional[bool]]
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NotRequired[Optional[str]]
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NotRequired[Optional[str]]
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NotRequired[Optional[str]]
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NotRequired[Optional[str]]
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NotRequired[Optional[str]]
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Optional[ErrorScoreHandler]
Optionally supply a custom function to specifically handle score values when tasks or scoring functions have errored.
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Optional[str]
An optional description for the experiment.
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bool
Whether to summarize the scores of the experiment after it has run.
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bool
Do not send logs to Braintrust. When True, the evaluation runs locally
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Optional[EvalParameters]
A set of parameters that will be passed to the evaluator.
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Optional[Callable[[ExperimentSummary], None]]
An optional callback that will be called when the evaluation starts. It receives the
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Optional[Callable[[SSEProgressEvent], None]]
A function that will be called with progress events, which can be used to
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Optional[str]
If specified, instead of creating a new experiment object, the Eval() will populate
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Optional[BraintrustState]
Optional BraintrustState to use for the evaluation. If not specified, the global login state will be used.

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Reporter

A function you can use to define a reporter. This is a convenience wrapper around the ReporterDef class.
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str
The name of the reporter.
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Callable[[Evaluator[Input, Output], EvalResultWithSummary[Input, Output], bool, bool], Union[EvalReport, Awaitable[EvalReport]]]
return str(result.summary)
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Callable[[List[EvalReport], bool, bool], Union[bool, Awaitable[bool]]]
return True

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current_experiment

Returns the currently-active experiment (set by braintrust.init(...)). Returns None if no current experiment has been set.

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current_logger

Returns the currently-active logger (set by braintrust.init_logger(...)). Returns None if no current logger has been set.

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current_span

Return the currently-active span for logging (set by running a span under a context manager). If there is no active span, returns a no-op span object, which supports the same interface as spans but does no logging.

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flush

Flush any pending rows to the server.

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get_prompt_versions

Get the versions for a specific prompt.
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str
The ID of the project to query
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str
The ID of the prompt to get versions for

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get_span_parent_object

Mainly for internal use. Return the parent object for starting a span in a global context. Applies precedence: current span > propagated parent string > experiment > logger.
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Optional[str]
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Optional[BraintrustState]

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init

Log in, and then initialize a new experiment in a specified project. If the project does not exist, it will be created.
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Optional[str]
The name of the project to create the experiment in. Must specify at least one of project or project_id.
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Optional[str]
The name of the experiment to create. If not specified, a name will be generated automatically.
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Optional[str]
(Optional) An optional description of the experiment.
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Optional['Dataset']
(Optional) A dataset to associate with the experiment. The dataset must be initialized with braintrust.init_dataset before passing
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bool
If the experiment already exists, open it in read-only mode. Throws an error if the experiment does not already exist.
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Optional[str]
An optional experiment name to use as a base. If specified, the new experiment will be summarized and compared to this experiment. Otherwise, it will pick an experiment by finding the closest ancestor on the default (e.g. main) branch.
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bool
An optional parameter to control whether the experiment is publicly visible to anybody with the link or privately visible to only members of the organization. Defaults to private.
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Optional[str]
The URL of the Braintrust App. Defaults to https://www.braintrust.dev.
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Optional[str]
The API key to use. If the parameter is not specified, will try to use the BRAINTRUST_API_KEY environment variable. If no API
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Optional[str]
(Optional) The name of a specific organization to connect to. This is useful if you belong to multiple.
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Optional[Metadata]
(Optional) 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.
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Optional[GitMetadataSettings]
(Optional) Settings for collecting git metadata. By default, will collect all git metadata fields allowed in org-level settings.
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Literal['all', 'none', 'some']
required
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NotRequired[Sequence[Literal['commit', 'branch', 'tag', 'dirty', 'author_name', 'author_email', 'commit_message', 'commit_time', 'git_diff']]]
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bool
If true (the default), set the global current-experiment to the newly-created one.
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Optional[bool]
If the experiment already exists, continue logging to it. If it does not exist, creates the experiment with the specified arguments.
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Optional[str]
The id of the project to create the experiment in. This takes precedence over project if specified.
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Optional[str]
An optional experiment id to use as a base. If specified, the new experiment will be summarized and compared to this. This takes precedence over base_experiment if specified.
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Optional[RepoInfo]
(Optional) Explicitly specify the git metadata for this experiment. This takes precedence over git_metadata_settings if specified.
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NotRequired[Optional[str]]
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NotRequired[Optional[str]]
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NotRequired[Optional[str]]
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NotRequired[Optional[bool]]
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NotRequired[Optional[str]]
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NotRequired[Optional[str]]
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NotRequired[Optional[str]]
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NotRequired[Optional[str]]
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NotRequired[Optional[str]]
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Optional[BraintrustState]
(Optional) A BraintrustState object to use. If not specified, will use the global state. This is for advanced use only.

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init_dataset

Create a new dataset in a specified project. If the project does not exist, it will be created.
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Optional[str]
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Optional[str]
The name of the dataset to create. If not specified, a name will be generated automatically.
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Optional[str]
An optional description of the dataset.
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Optional[Union[str, int]]
An optional version of the dataset (to read). If not specified, the latest version will be used.
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Optional[str]
The URL of the Braintrust App. Defaults to https://www.braintrust.dev.
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Optional[str]
The API key to use. If the parameter is not specified, will try to use the BRAINTRUST_API_KEY environment variable. If no API
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Optional[str]
(Optional) The name of a specific organization to connect to. This is useful if you belong to multiple.
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Optional[str]
The id of the project to create the dataset in. This takes precedence over project if specified.
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Optional[Metadata]
(Optional) a dictionary with additional data about the dataset. The values in metadata can be any JSON-serializable type, but its keys must be strings.
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bool
(Deprecated) If True, records will be fetched from this dataset in the legacy format, with the “expected” field renamed to “output”. This option will be removed in a future version of Braintrust.
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Optional[Dict[str, Any]]
(Internal) If specified, the dataset will be created with the given BTQL filters.
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Optional[BraintrustState]
(Internal) The Braintrust state to use. If not specified, will use the global state. For advanced use only.

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init_experiment

Alias for init
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Any
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Any

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init_function

Creates a function that can be used as either a task or scorer in the Eval framework. When used as a task, it will invoke the specified Braintrust function with the input. When used as a scorer, it will invoke the function with the scorer arguments.
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str
The name of the project containing the function.
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str
The slug of the function to invoke.
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Optional[str]
Optional version of the function to use. Defaults to latest.

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init_logger

Create a new logger in a specified project. If the project does not exist, it will be created.
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Optional[str]
The name of the project to log into. If unspecified, will default to the Global project.
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Optional[str]
The id of the project to log into. This takes precedence over project if specified.
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bool
If true (the default), log events will be batched and sent asynchronously in a background thread. If false, log events will be sent synchronously. Set to false in serverless environments.
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Optional[str]
The URL of the Braintrust API. Defaults to https://www.braintrust.dev.
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Optional[str]
The API key to use. If the parameter is not specified, will try to use the BRAINTRUST_API_KEY environment variable. If no API
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Optional[str]
(Optional) The name of a specific organization to connect to. This is useful if you belong to multiple.
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bool
Login again, even if you have already logged in (by default, the logger will not login if you are already logged in)
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bool
If true (the default), set the global current-experiment to the newly-created one.
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Optional[BraintrustState]

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invoke

Invoke a Braintrust function, returning a BraintrustStream or the value as a plain Python object.
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Optional[str]
The ID of the function to invoke.
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Optional[str]
The version of the function to invoke.
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Optional[str]
The ID of the prompt session to invoke the function from.
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Optional[str]
The ID of the function in the prompt session to invoke.
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Optional[str]
The name of the project containing the function to invoke.
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Optional[str]
The ID of the project to use for execution context (API keys, project defaults, etc.).
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Optional[str]
The slug of the function to invoke.
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Optional[str]
The name of the global function to invoke.
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Any
The input to the function. This will be logged as the input field in the span.
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Optional[List[Any]]
Additional OpenAI-style messages to add to the prompt (only works for llm functions).
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Optional[InvokeContext]
Context for functions that operate on spans/traces (e.g., facets). Should contain
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Literal['project_logs', 'experiment', 'dataset', 'playground_logs']
required
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str
required
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InvokeScope
required
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Optional[Dict[str, Any]]
Additional metadata to add to the span. This will be logged as the metadata field in the span.
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Optional[List[str]]
Tags to add to the span. This will be logged as the tags field in the span.
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Optional[Union[Exportable, str]]
The parent of the function. This can be an existing span, logger, or experiment, or
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bool
Whether to stream the function’s output. If True, the function will return a
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Optional[ModeType]
The response shape of the function if returning tool calls. If “auto”, will return
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Optional[bool]
Whether to use strict mode for the function. If true, the function will throw an
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Optional[str]
The name of the Braintrust organization to use.
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Optional[str]
The API key to use for authentication.
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Optional[str]
The URL of the Braintrust application.
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bool
Whether to force a new login even if already logged in.

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load_prompt

Loads a prompt from the specified project.
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Optional[str]
The name of the project to load the prompt from. Must specify at least one of project or project_id.
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Optional[str]
The slug of the prompt to load.
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Optional[Union[str, int]]
An optional version of the prompt (to read). If not specified, the latest version will be used.
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Optional[str]
The id of the project to load the prompt from. This takes precedence over project if specified.
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Optional[str]
The id of a specific prompt to load. If specified, this takes precedence over all other parameters (project, slug, version).
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Optional[Mapping[str, Any]]
(Optional) A dictionary of default values to use when rendering the prompt. Prompt values will override these defaults.
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bool
If true, do not include logging metadata for this prompt when build() is called.
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Optional[str]
The environment to load the prompt from. Cannot be used together with version.
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Optional[str]
The URL of the Braintrust App. Defaults to https://www.braintrust.dev.
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Optional[str]
The API key to use. If the parameter is not specified, will try to use the BRAINTRUST_API_KEY environment variable. If no API
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Optional[str]
(Optional) The name of a specific organization to connect to. This is useful if you belong to multiple.

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log

Log a single event to the current experiment. The event will be batched and uploaded behind the scenes.
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Any

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login

Log into Braintrust. This will prompt you for your API token, which you can find at https://www.braintrust.dev/app/token. This method is called automatically by init().
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Optional[str]
The URL of the Braintrust App. Defaults to https://www.braintrust.dev.
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Optional[str]
The API key to use. If the parameter is not specified, will try to use the BRAINTRUST_API_KEY environment variable. If no API
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Optional[str]
(Optional) The name of a specific organization to connect to. This is useful if you belong to multiple.
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bool
Login again, even if you have already logged in (by default, this function will exit quickly if you have already logged in)

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parent_context

Context manager to temporarily set the parent context for spans.
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Optional[str]
The parent string to set during the context
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Optional[BraintrustState]
Optional BraintrustState to use. If not provided, uses the global state.

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parse_stream

Parse a BraintrustStream into its final value.
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BraintrustStream
The BraintrustStream to parse.

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patch_litellm

Patch LiteLLM to add Braintrust tracing. Format a permalink to the Braintrust application for viewing the span represented by the provided slug.
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str
The identifier generated from Span.export.
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Optional[str]
The org name to use. If not provided, the org name will be inferred from the global login state.
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Optional[str]
The app URL to use. If not provided, the app URL will be inferred from the global login state.

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prettify_params

Clean up parameters by filtering out NOT_GIVEN values and serializing response_format.
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dict[str, Any]

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serialize_response_format

Serialize response format for logging.
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Any

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set_http_adapter

Specify a custom HTTP adapter to use for all network requests. This is useful for setting custom retry policies, timeouts, etc. Braintrust uses the requests library, so the adapter should be an instance of requests.adapters.HTTPAdapter. Alternatively, consider sub-classing our RetryRequestExceptionsAdapter to get automatic retries on network-related exceptions.
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HTTPAdapter
The adapter to use.

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set_masking_function

Set a global masking function that will be applied to all logged data before sending to Braintrust. The masking function will be applied after records are merged but before they are sent to the backend.
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Optional[Callable[[Any], Any]]
A function that takes a JSON-serializable object and returns a masked version.

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set_thread_pool_max_workers

Set the maximum number of threads to use for running evaluators. By default, this is the number of CPUs on the machine.
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Any

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span_components_to_object_id

Utility function to resolve the object ID of a SpanComponentsV4 object. This function may trigger a login to braintrust if the object ID is encoded lazily.
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SpanComponentsV4

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start_span

Lower-level alternative to @traced for starting a span at the toplevel. It creates a span under the first active object (using the same precedence order as @traced), or if parent is specified, under the specified parent row, or returns a no-op span object.
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Optional[str]
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Optional[SpanTypeAttribute]
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Optional[Union[SpanAttributes, Mapping[str, Any]]]
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Optional[float]
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Optional[bool]
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Optional[str]
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Optional[Dict[str, Any]]
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Optional[BraintrustState]
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Any

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summarize

Summarize the current experiment, including the scores (compared to the closest reference experiment) and metadata.
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bool
Whether to summarize the scores. If False, only the metadata will be returned.
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Optional[str]
The experiment to compare against. If None, the most recent experiment on the comparison_commit will be used.

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traced

Decorator to trace the wrapped function when used without parentheses.
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F

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update_span

Update a span using the output of span.export(). It is important that you only resume updating to a span once the original span has been fully written and flushed, since otherwise updates to the span may conflict with the original span.
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str
The output of span.export().
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Any

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wrap_anthropic

Wrap an Anthropic object (or AsyncAnthropic) to add tracing. If Braintrust is not configured, this is a no-op. If this is not an Anthropic object, this function is a no-op.
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Any

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wrap_litellm

Wrap the litellm module to add tracing. If Braintrust is not configured, nothing will be traced.
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Any
The litellm module

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wrap_openai

Wrap the openai module (pre v1) or OpenAI instance (post v1) to add tracing. If Braintrust is not configured, nothing will be traced. If this is not an OpenAI object, this function is a no-op.
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Any
The openai module or OpenAI object

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Classes

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AsyncResponseWrapper

Wrapper that properly preserves async context manager behavior for OpenAI responses. Methods __init__()

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AsyncScorerLike

Protocol for asynchronous scorers that implement the eval_async interface. The framework will prefer this interface if available.

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Attachment

Represents an attachment to be uploaded and the associated metadata. Methods __init__(), reference(), data(), upload(), debug_info()

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BaseExperiment

Use this to specify that the dataset should actually be the data from a previous (base) experiment. If you do not specify a name, Braintrust will automatically figure out the best base experiment to use based on your git history (or fall back to timestamps). Properties
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Optional[str]

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BraintrustConsoleChunk

A console chunk from a Braintrust stream. Properties
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str
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Literal['stderr', 'stdout']
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Literal['console']

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BraintrustErrorChunk

An error chunk from a Braintrust stream. Properties
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str
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Literal['error']

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BraintrustInvokeError

An error that occurs during a Braintrust stream.

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BraintrustJsonChunk

A chunk of JSON data from a Braintrust stream. Properties
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str
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Literal['json_delta']

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BraintrustProgressChunk

A progress chunk from a Braintrust stream. Properties
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str
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str
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str
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str
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str
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str
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Literal['json_delta', 'text_delta', 'reasoning_delta']
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Literal['progress']

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BraintrustStream

A Braintrust stream. This is a wrapper around a generator of BraintrustStreamChunk, with utility methods to make them easy to log and convert into various formats. Methods __init__(), copy(), final_value()

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BraintrustTextChunk

A chunk of text data from a Braintrust stream. Properties
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str
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Literal['text_delta']

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CodeFunction

A generic callable, with metadata. Properties
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'Project'
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Callable[..., Any]
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str
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str
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str
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Optional[str]
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Any
​
Any
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Optional[IfExists]
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Optional[Dict[str, Any]]

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CodePrompt

A prompt defined in code, with metadata. Properties
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'Project'
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str
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str
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PromptData
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List[Union[CodeFunction, SavedFunctionId]]
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Optional[str]
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Optional[str]
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Optional[str]
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Optional[IfExists]
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Optional[Dict[str, Any]]
Methods to_function_definition()

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CompletionWrapper

Wrapper for LiteLLM completion functions with tracing support. Methods __init__(), completion()

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DataSummary

Summary of a dataset’s data. Properties
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int
​
int

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Dataset

A dataset is a collection of records, such as model inputs and outputs, which represent data you can use to evaluate and fine-tune models. You can log production data to datasets, curate them with interesting examples, edit/delete records, and run evaluations against them. Methods __init__(), id(), name(), data(), project(), logging_state(), insert(), update(), delete(), summarize(), close(), flush()

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DatasetSummary

Summary of a dataset’s scores and metadata. Properties
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str
​
str
​
str
​
str
​
Optional[DataSummary]

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EmbeddingWrapper

Wrapper for LiteLLM embedding functions. Methods __init__(), embedding()

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EvalCase

An evaluation case. This is a single input to the evaluation task, along with an optional expected output, metadata, and tags. Properties
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Input
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Optional[Output]
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Optional[Metadata]
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Optional[Sequence[str]]
​
Optional[str]
​
Optional[str]

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EvalHooks

An object that can be used to add metadata to an evaluation. This is passed to the task function. Methods metadata(), expected(), span(), trial_index(), tags(), report_progress(), meta(), parameters()

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EvalResult

The result of an evaluation. This includes the input, expected output, actual output, and metadata. Properties
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Input
​
Output
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Dict[str, Optional[float]]
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Optional[Output]
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Optional[Metadata]
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Optional[List[str]]
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Optional[Exception]
​
Optional[str]

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EvalScorerArgs

Arguments passed to an evaluator scorer. This includes the input, expected output, actual output, and metadata. Properties
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Input
​
Output
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Optional[Output]
​
Optional[Metadata]

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Evaluator

An evaluator is an abstraction that defines an evaluation dataset, a task to run on the dataset, and a set of scorers to evaluate the results of the task. Each method attribute can be synchronous or asynchronous (for optimal performance, it is recommended to provide asynchronous implementations). Properties
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str
​
str
​
EvalData[Input, Output]
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EvalTask[Input, Output]
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List[EvalScorer[Input, Output]]
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Optional[str]
​
Optional[Metadata]
​
int
​
bool
​
bool
​
Optional[float]
​
Optional[int]
​
Optional[str]
​
Optional[str]
​
Optional[str]
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Optional[GitMetadataSettings]
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Optional[RepoInfo]
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Optional[ErrorScoreHandler]
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Optional[str]
​
bool
​
Optional[EvalParameters]

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Experiment

An experiment is a collection of logged events, such as model inputs and outputs, which represent a snapshot of your application at a particular point in time. An experiment is meant to capture more than just the model you use, and includes the data you use to test, pre- and post- processing code, comparison metrics (scores), and any other metadata you want to include. Methods __init__(), id(), name(), data(), project(), logging_state(), log(), log_feedback(), start_span(), update_span(), fetch_base_experiment(), summarize(), export(), close(), flush()

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ExperimentSummary

Summary of an experiment’s scores and metadata. Properties
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str
​
Optional[str]
​
Optional[str]
​
str
​
Optional[str]
​
Optional[str]
​
Optional[str]
​
Dict[str, ScoreSummary]
​
Dict[str, MetricSummary]

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ExternalAttachment

Represents an attachment that resides in an external object store and the associated metadata. Methods __init__(), reference(), data(), upload(), debug_info()

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JSONAttachment

A convenience class for creating attachments from JSON-serializable objects. Methods __init__()

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LiteLLMWrapper

Main wrapper for the LiteLLM module. Methods __init__(), completion(), responses(), embedding(), moderation()

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MetricSummary

Summary of a metric’s performance. Properties
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str
​
Union[float, int]
​
str
​
Optional[int]
​
Optional[int]
​
Optional[float]

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ModerationWrapper

Wrapper for LiteLLM moderation functions. Methods __init__(), moderation()

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NamedWrapper

Wrapper that preserves access to the original wrapped object’s attributes. Methods __init__()

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Project

A handle to a Braintrust project. Methods __init__(), add_code_function(), add_prompt(), publish()

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ProjectBuilder

Creates handles to Braintrust projects. Methods create()

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Prompt

A prompt object consists of prompt text, a model, and model parameters (such as temperature), which can be used to generate completions or chat messages. The prompt object supports calling .build() which uses mustache templating to build the prompt with the given formatting options and returns a plain dictionary that includes the built prompt and arguments. The dictionary can be passed as kwargs to the OpenAI client or modified as you see fit. Methods __init__(), from_prompt_data(), id(), name(), slug(), prompt(), version(), options(), build()

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PromptBuilder

Builder to create a prompt in Braintrust. Methods __init__(), create(), create(), create()

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ReadonlyAttachment

A readonly alternative to Attachment, which can be used for fetching already-uploaded Attachments. Methods __init__(), data(), metadata(), status()

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ReadonlyExperiment

A read-only view of an experiment, initialized by passing open=True to init(). Methods __init__(), id(), logging_state(), as_dataset()

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RepoInfo

Information about the current HEAD of the repo. Properties
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Optional[str]
​
Optional[str]
​
Optional[str]
​
Optional[bool]
​
Optional[str]
​
Optional[str]
​
Optional[str]
​
Optional[str]
​
Optional[str]

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ReporterDef

A reporter takes an evaluator and its result and returns a report. Properties
​
str
​
Callable[[Evaluator[Input, Output], EvalResultWithSummary[Input, Output], bool, bool], Union[EvalReport, Awaitable[EvalReport]]]
​
Callable[[List[EvalReport], bool, bool], Union[bool, Awaitable[bool]]]

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ResponsesWrapper

Wrapper for LiteLLM responses functions with tracing support. Methods __init__(), responses()

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RetryRequestExceptionsAdapter

An HTTP adapter that automatically retries requests on connection exceptions. Methods __init__(), send()

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SSEProgressEvent

A progress event that can be reported during task execution, specifically for SSE (Server-Sent Events) streams. This is a subclass of TaskProgressEvent with additional fields for SSE-specific metadata. Properties
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str
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str
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ObjectReference
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str

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ScoreSummary

Summary of a score’s performance. Properties
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str
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float
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Optional[int]
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Optional[int]
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Optional[float]

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ScorerBuilder

Builder to create a scorer in Braintrust. Methods __init__(), create(), create(), create(), create()

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Span

A Span encapsulates logged data and metrics for a unit of work. This interface is shared by all span implementations. Methods id(), log(), log_feedback(), start_span(), export(), link(), permalink(), end(), flush(), close(), set_attributes(), set_current(), unset_current()

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SpanIds

The three IDs that define a span’s position in the trace tree. Properties
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str
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str
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Optional[List[str]]

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SpanImpl

Primary implementation of the Span interface. See the Span interface for full details on each method. Properties
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bool
Methods __init__(), id(), set_attributes(), log(), log_internal(), log_feedback(), start_span(), end(), export(), link(), permalink(), close(), flush(), set_current(), unset_current()

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SpanScope

Scope for operating on a single span. Properties
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Literal['span']
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str
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str

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SyncScorerLike

Protocol for synchronous scorers that implement the callable interface. This is the most common interface and is used when no async version is available. Methods __call__()

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TaskProgressEvent

Progress event that can be reported during task execution. Properties
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FunctionFormat
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FunctionOutputType
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Literal['reasoning_delta', 'text_delta', 'json_delta', 'error', 'console', 'start', 'done', 'progress']
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str

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ToolBuilder

Builder to create a tool in Braintrust. Methods __init__(), create()

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TraceScope

Scope for operating on an entire trace. Properties
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Literal['trace']
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str

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TracedMessageStream

TracedMessageStream wraps both sync and async message streams. Obviously only one makes sense at a time Methods __init__()