MaximApis

Maxim_Apis utilities for api client utilities for interacting with maxim services.

View module source on GitHub

ConnectionPool

class ConnectionPool()

Manages HTTP session pooling for efficient network requests.

This class provides a reusable session with retry logic for handling transient network errors.

__init__

def __init__()

Initialize a new session with retry configuration.

get_session

@contextlib.contextmanager
def get_session()

Context manager that yields the session and ensures it’s closed after use.

Yields:

• requests.Session - The HTTP session object

MaximAPI

class MaximAPI()

Client for interacting with the Maxim API.

This class provides methods for all available Maxim API endpoints, handling authentication, request formatting, and error handling.

__init__

def __init__(base_url: str, api_key: str)

Initialize a new Maxim API client.

Arguments:

Name	Description
base_url	The base URL for the Maxim API
api_key	The API key for authentication

get_prompt

def get_prompt(id: str) -> VersionAndRulesWithPromptId

Get a prompt by ID.

Arguments:

Name	Description
id	The prompt ID

Returns:

Name	Description
[VersionAndRulesWithPromptId](/sdk/python/references/models/prompt)	The prompt details

Raises:

• Exception - If the request fails

get_prompts

def get_prompts() -> List[VersionAndRulesWithPromptId]

Get all prompts.

Returns:

Name	Description
List[[VersionAndRulesWithPromptId](/sdk/python/references/models/prompt)]	List of all prompts

Raises:

• Exception - If the request fails

getPromptChain

def getPromptChain(id: str) -> VersionAndRulesWithPromptChainId

Get a prompt chain by ID.

Arguments:

Name	Description
id	The prompt chain ID

Returns:

Name	Description
[VersionAndRulesWithPromptChainId](/sdk/python/references/models/prompt_chain)	The prompt chain details

Raises:

• Exception - If the request fails

get_prompt_chains

def get_prompt_chains() -> List[VersionAndRulesWithPromptChainId]

Get all prompt chains.

Returns:

Name	Description
List[[VersionAndRulesWithPromptChainId](/sdk/python/references/models/prompt_chain)]	List of all prompt chains

Raises:

• Exception - If the request fails

run_prompt

def run_prompt(model: str,
               messages: List[ChatCompletionMessage],
               tools: Optional[List[Tool]] = None,
               **kwargs)

Run a custom prompt with the specified model and messages.

Arguments:

Name	Description
model	The model to use
messages	List of chat messages
tools	Optional list of tools to use
**kwargs	Additional parameters to pass to the API

Returns:

Name	Description
[PromptResponse](/sdk/python/references/models/prompt)	The response from the model

Raises:

• Exception - If the request fails

run_prompt_version

def run_prompt_version(
        prompt_version_id: str, input: str,
        image_urls: Optional[List[ImageUrls]],
        variables: Optional[dict[str, str]]) -> Optional[PromptResponse]

Run a specific prompt version with the given input.

Arguments:

Name	Description
prompt_version_id	The ID of the prompt version to run
input	The input text for the prompt
image_urls	Optional list of image URLs to include
variables	Optional dictionary of variables to use

Returns:

Name	Description
Optional[[PromptResponse](/sdk/python/references/models/prompt)]	The response from the prompt

Raises:

• Exception - If the request fails

run_prompt_chain_version

def run_prompt_chain_version(
        prompt_chain_version_id: str, input: str,
        variables: Optional[dict[str, str]]) -> Optional[AgentResponse]

Run a specific prompt chain version with the given input.

Arguments:

Name	Description
prompt_chain_version_id	The ID of the prompt chain version to run
input	The input text for the prompt chain
variables	Optional dictionary of variables to use

Returns:

Name	Description
Optional[[AgentResponse](/sdk/python/references/models/prompt_chain)]	The response from the prompt chain

Raises:

• Exception - If the request fails

get_folder

def get_folder(id: str) -> Folder

Get a folder by ID.

Arguments:

Name	Description
id	The folder ID

Returns:

Name	Description
[Folder](/sdk/python/references/models/folder)	The folder details

Raises:

• Exception - If the request fails

get_folders

def get_folders() -> List[Folder]

Get all folders.

Returns:

Name	Description
List[[Folder](/sdk/python/references/models/folder)]	List of all folders

Raises:

• Exception - If the request fails

add_dataset_entries

def add_dataset_entries(dataset_id: str,
                        dataset_entries: List[DatasetEntry]) -> dict[str, Any]

Add entries to a dataset.

Arguments:

Name	Description
dataset_id	The ID of the dataset
dataset_entries	List of dataset entries to add

Returns:

dict[str, Any]: Response from the API

Raises:

• Exception - If the request fails

get_dataset_total_rows

def get_dataset_total_rows(dataset_id: str) -> int

Get the total number of rows in a dataset.

Arguments:

Name	Description
dataset_id	The ID of the dataset

Returns:

Name	Description
int	The total number of rows

Raises:

• Exception - If the request fails

get_dataset_row

def get_dataset_row(dataset_id: str, row_index: int) -> Optional[DatasetRow]

Get a specific row from a dataset.

Arguments:

Name	Description
dataset_id	The ID of the dataset
row_index	The index of the row to retrieve

Returns:

Name	Description
Optional[[DatasetRow](/sdk/python/references/models/dataset)]	The dataset row, or None if not found

Raises:

• Exception - If the request fails

get_dataset_structure

def get_dataset_structure(dataset_id: str) -> Dict[str, str]

Get the structure of a dataset.

Arguments:

Name	Description
dataset_id	The ID of the dataset

Returns:

Dict[str, str]: The dataset structure

Raises:

• Exception - If the request fails

does_log_repository_exist

def does_log_repository_exist(logger_id: str) -> bool

Check if a log repository exists.

Arguments:

Name	Description
logger_id	The ID of the logger

Returns:

Name	Description
bool	True if the repository exists, False otherwise

push_logs

def push_logs(repository_id: str, logs: str) -> None

Push logs to a repository.

Arguments:

Name	Description
repository_id	The ID of the repository
logs	The logs to push

Raises:

• Exception - If the request fails

fetch_platform_evaluator

def fetch_platform_evaluator(name: str, in_workspace_id: str) -> Evaluator

Fetch a platform evaluator by name.

Arguments:

Name	Description
name	The name of the evaluator
in_workspace_id	The workspace ID

Returns:

Name	Description
[Evaluator](/sdk/python/references/models/evaluator)	The evaluator details

Raises:

• Exception - If the request fails

create_test_run

def create_test_run(
    name: str,
    workspace_id: str,
    workflow_id: Optional[str],
    prompt_version_id: Optional[str],
    prompt_chain_version_id: Optional[str],
    run_type: RunType,
    evaluator_config: list[Evaluator],
    requires_local_run: bool,
    human_evaluation_config: Optional[HumanEvaluationConfig] = None
) -> TestRun

Create a new test run.

Arguments:

Name	Description
name	The name of the test run
workspace_id	The workspace ID
workflow_id	Optional workflow ID
prompt_version_id	Optional prompt version ID
prompt_chain_version_id	Optional prompt chain version ID
run_type	The type of run
evaluator_config	List of evaluators to use
requires_local_run	Whether the test run requires local execution
human_evaluation_config	Optional human evaluation configuration

Returns:

Name	Description
[TestRun](/sdk/python/references/models/test_run)	The created test run

Raises:

• Exception - If the request fails

attach_dataset_to_test_run

def attach_dataset_to_test_run(test_run_id: str, dataset_id: str) -> None

Attach a dataset to a test run.

Arguments:

Name	Description
test_run_id	The ID of the test run
dataset_id	The ID of the dataset

Raises:

• Exception - If the request fails

push_test_run_entry

def push_test_run_entry(test_run: Union[TestRun, TestRunWithDatasetEntry],
                        entry: TestRunEntry,
                        run_config: Optional[Dict[str, Any]] = None) -> None

Push an entry to a test run.

Arguments:

Name	Description
test_run	The test run
entry	The test run entry to push
run_config	Optional run configuration

Raises:

• Exception - If the request fails

mark_test_run_processed

def mark_test_run_processed(test_run_id: str) -> None

Mark a test run as processed.

Arguments:

Name	Description
test_run_id	The ID of the test run

Raises:

• Exception - If the request fails

mark_test_run_failed

def mark_test_run_failed(test_run_id: str) -> None

Mark a test run as failed.

Arguments:

Name	Description
test_run_id	The ID of the test run

Raises:

• Exception - If the request fails

get_test_run_status

def get_test_run_status(test_run_id: str) -> TestRunStatus

Get the status of a test run.

Arguments:

Name	Description
test_run_id	The ID of the test run

Returns:

Name	Description
[TestRunStatus](/sdk/python/references/models/test_run)	The status of the test run

Raises:

• Exception - If the request fails

get_test_run_final_result

def get_test_run_final_result(test_run_id: str) -> TestRunResult

Get the final result of a test run.

Arguments:

Name	Description
test_run_id	The ID of the test run

Returns:

Name	Description
[TestRunResult](/sdk/python/references/models/test_run)	The final result of the test run

Raises:

• Exception - If the request fails

get_upload_url

def get_upload_url(key: str, mime_type: str, size: int) -> SignedURLResponse

Get a signed URL for uploading a file.

Arguments:

Name	Description
key	The key (filename) for the upload
mime_type	The MIME type of the file
size	The size of the file in bytes

Returns:

Name	Description
[SignedURLResponse](/sdk/python/references/models/attachment)	A dictionary containing the signed URL for upload

Raises:

• Exception - If the request fails

upload_to_signed_url

def upload_to_signed_url(url: str, data: bytes, mime_type: str) -> bool

Upload data to a signed URL using multipart form data with retry logic.

Arguments:

Name	Description
url	The signed URL to upload to
data	The binary data to upload
mime_type	The MIME type of the data

Returns:

Name	Description
bool	True if upload was successful, False otherwise