Listing jobs
Returns: list: A list of job details.
Getting job status
Parameters:
job_id(str): The ID of the job to retrieve the status for.
Returns: dict: The status of the job.
Getting job results
Parameters:
job_id(str): The ID of the job to retrieve the results for.include_inputs(bool, optional): Whether to include the inputs in the results. Defaults to False.include_cumulative_logprobs(bool, optional): Whether to include the cumulative logprobs in the results. Defaults to False.with_original_df(Union[pl.DataFrame, pd.DataFrame], optional): Original DataFrame to join results with. Defaults to None.output_column(str, optional): Name of the column containing results. Defaults to “inference_result”.disable_cache(bool, optional): Whether to disable reading from or writing to the local job results cache. Defaults to False.unpack_json(bool, optional): If the output_column is formatted as a JSON string, decides whether to unpack the top level JSON fields in the results into separate columns. Defaults to True.
Returns: Union[pl.DataFrame, pd.DataFrame]: Results as a DataFrame.
- If
with_original_dfis provided: Returns the same type as the input DataFrame with results added as a new column - If
with_original_dfis None: Returns a polars DataFrame by default
The DataFrame will contain:
inputscolumn (ifinclude_inputs=True). Each cell contains the input string given to the model.inference_resultcolumn (or custom name viaoutput_column)cumulative_logprobscolumn (ifinclude_cumulative_logprobs=True)
Example:
Cancelling jobs
Parameters:
job_id(str): The ID of the job to cancel.
Returns: dict: The status of the job cancellation.