Documentation Index
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Module
Experiment result wrapper for easy status access and monitoring.
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
is_complete
def is_complete(self) -> bool
is_failed
def is_failed(self) -> bool
is_in_progress
def is_in_progress(self) -> bool
is_pending
def is_pending(self) -> bool
to_dict
def to_dict(self) -> dict[str, Any]
phase_dict = status.log_generation.to_dict()
print(phase_dict["progress_percent"])
print(phase_dict["is_complete"])
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"])
from_result
def from_result(cls, result: dict[str, Any]) -> ExperimentStatusInfo
result: Dictionary returned from Experiment.run().
is_complete
def is_complete(self) -> bool
is_failed
def is_failed(self) -> bool
is_in_progress
def is_in_progress(self) -> bool
is_pending
def is_pending(self) -> bool
overall_progress
def overall_progress(self) -> float
Returns
float: Progress percentage from 0.0 to 100.0.
to_dict
def to_dict(self) -> dict[str, Any]
status = experiment.get_status()
status_dict = status.to_dict()
print(status_dict["overall_progress"])
print(status_dict["log_generation"]["is_complete"])
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"])
dataset_info
def dataset_info(self) -> dict[str, str | None] | None
result = experiment.run()
if result.dataset_info:
print(f"Dataset: {result.dataset_info['name']}")
print(f"Version: {result.dataset_info['version']}")
experiment
def experiment(self) -> ExperimentResponse
Returns
ExperimentResponse: The raw API response object.
prompt_info
def prompt_info(self) -> dict[str, str | None] | None
result = experiment.run()
if result.prompt_info:
print(f"Prompt: {result.prompt_info['name']}")
print(f"ID: {result.prompt_info['id']}")
to_dict
def to_dict(self) -> dict[str, Any]
result = experiment.run()
result_dict = result.to_dict()
print(result_dict["link"])
print(result_dict["status"]["overall_progress"])
