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Module

Experiment result wrapper for easy status access and monitoring.

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ExperimentPhaseInfo

Wrapper for experiment phase status information. Provides easy access to phase-level progress and status information for an experiment. Examples 
# Access phase information from experiment status
experiment = Experiment.get(name="ml-eval", project_name="My Project")
status = experiment.get_status()

log_gen = status.log_generation
if log_gen.is_complete:
    print("Log generation phase completed!")
elif log_gen.is_in_progress:
    print(f"Log generation at {log_gen.progress_percent:.1f}%")

# Check phase status
print(f"Phase status: {log_gen}")  # Human-readable string

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is_complete

def is_complete(self) -> bool
Whether this phase is complete (progress >= 100%).

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is_failed

def is_failed(self) -> bool
Whether this phase failed. Currently always returns False.

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is_in_progress

def is_in_progress(self) -> bool
Whether this phase is in progress (0% < progress < 100%).

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is_pending

def is_pending(self) -> bool
Whether this phase hasn’t started yet (progress = 0%).

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to_dict

def to_dict(self) -> dict[str, Any]
Convert the phase info to a dictionary. Examples 
phase_dict = status.log_generation.to_dict()
print(phase_dict["progress_percent"])
print(phase_dict["is_complete"])

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ExperimentStatusInfo

Wrapper for experiment status information. Provides human-readable access to experiment execution status, including progress tracking and phase-level information. Examples 
# Get status information
experiment = Experiment.get(name="ml-eval", project_name="My Project")
status = experiment.get_status()

# Human-readable output
print(status)  # "Experiment Running (45.2%)"
print(f"Log Generation: {status.log_generation}")  # "In Progress (45.2%)"

# Check status
if status.is_complete:
    print("Experiment completed!")
elif status.is_in_progress:
    print(f"Progress: {status.overall_progress:.1f}%")
elif status.is_pending:
    print("Experiment hasn't started yet")

# Convert to dictionary
status_dict = status.to_dict()
print(status_dict["overall_progress"])

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from_result

def from_result(cls, result: dict[str, Any]) -> ExperimentStatusInfo
Create from experiment.run() result dictionary. Arguments
  • result: Dictionary returned from Experiment.run().

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is_complete

def is_complete(self) -> bool
Whether the experiment is complete (all phases at 100%).

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is_failed

def is_failed(self) -> bool
Whether the experiment has failed. Currently always returns False.

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is_in_progress

def is_in_progress(self) -> bool
Whether the experiment is currently running (0% < progress < 100%).

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is_pending

def is_pending(self) -> bool
Whether the experiment hasn’t started yet (progress = 0%).

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overall_progress

def overall_progress(self) -> float
Overall progress percentage across all phases. Currently uses log_generation progress. In the future, this may average multiple phase progress values.

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Returns

float: Progress percentage from 0.0 to 100.0.

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to_dict

def to_dict(self) -> dict[str, Any]
Convert the status info to a dictionary. Examples 
status = experiment.get_status()
status_dict = status.to_dict()
print(status_dict["overall_progress"])
print(status_dict["log_generation"]["is_complete"])

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ExperimentRunResult

Wrapper for experiment.run() result with human-readable access. Provides easy access to experiment run information including the link, status, and underlying experiment response. This wrapper makes it simple to work with experiment run results by exposing commonly needed information through intuitive properties and methods. Examples 
# Run an experiment and access the result
experiment = Experiment(
    name="ml-evaluation",
    dataset_name="ml-dataset",
    prompt_name="ml-prompt",
    project_name="My AI Project"
).create()

result = experiment.run()

# Access basic information
print(result)  # Human-readable summary
print(f"View results: {result.link}")
print(f"Experiment ID: {result.experiment_id}")

# Check status
if result.status.is_in_progress:
    print(f"Progress: {result.status.overall_progress:.1f}%")
elif result.status.is_complete:
    print("Experiment completed!")

# Get dataset and prompt information
if result.dataset_info:
    print(f"Dataset: {result.dataset_info['name']}")
if result.prompt_info:
    print(f"Prompt: {result.prompt_info['name']}")

# Convert to dictionary
result_dict = result.to_dict()
print(result_dict["link"])

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dataset_info

def dataset_info(self) -> dict[str, str | None] | None
Get dataset information if available. Examples 
result = experiment.run()
if result.dataset_info:
    print(f"Dataset: {result.dataset_info['name']}")
    print(f"Version: {result.dataset_info['version']}")

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experiment

def experiment(self) -> ExperimentResponse
Get the underlying ExperimentResponse object.

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Returns

ExperimentResponse: The raw API response object.

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prompt_info

def prompt_info(self) -> dict[str, str | None] | None
Get prompt information if available. Examples 
result = experiment.run()
if result.prompt_info:
    print(f"Prompt: {result.prompt_info['name']}")
    print(f"ID: {result.prompt_info['id']}")

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to_dict

def to_dict(self) -> dict[str, Any]
Convert the result to a dictionary. Examples 
result = experiment.run()
result_dict = result.to_dict()
print(result_dict["link"])
print(result_dict["status"]["overall_progress"])