Maxim

Core Maxim Python SDK functionality and main entry point.

View module source on GitHub

ConfigDict

class ConfigDict(TypedDict)

A class representing the configuration for the Maxim SDK.

Attributes:

Name	Type	Description
api_key	Optional[str], optional	The API key for the Maxim instance. Defaults to None.
base_url	Optional[str], optional	The base URL for the Maxim instance. Defaults to None.
cache	Optional[MaximCache], optional	The cache to use for the Maxim instance. Defaults to None.
debug	Optional[bool], optional	Whether to enable debug logging. Defaults to False.
raise_exceptions	Optional[bool], optional	Whether to raise exceptions during logging operations. Defaults to False.
prompt_management	Optional[bool], optional	Whether to enable prompt management. Defaults to False.

Config

@deprecated(
    "This class will be removed in a future version. Use {} which is TypedDict."
)

@dataclass
class Config()

A class representing the configuration for the Maxim SDK.

Attributes:

Name	Type	Description
api_key	str	The API key for the Maxim instance.
base_url	Optional[str], optional	The base URL for the Maxim instance. Defaults to “https://app.getmaxim.ai”.
cache	Optional[MaximCache], optional	The cache to use for the Maxim instance. Defaults to None.
debug	Optional[bool], optional	Whether to enable debug logging. Defaults to False.
raise_exceptions	Optional[bool], optional	Whether to raise exceptions during logging operations. Defaults to False.
prompt_management	Optional[bool], optional	Whether to enable prompt management. Defaults to False.

get_config_dict

def get_config_dict(config: Union[Config, ConfigDict]) -> dict[str, Any]

Converts a Config or ConfigDict to a dictionary with default values.

Arguments:

Name	Type	Description
config	Union[Config, ConfigDict]	The configuration object to convert.

Returns:

dict[str, Any]: A dictionary containing the configuration parameters with defaults applied.

Maxim

class Maxim()

__init__

def __init__(config: Union[Config, ConfigDict, None] = None)

Initializes a new instance of the Maxim class.

Arguments:

Name	Type	Description
config	Config	The configuration for the Maxim instance.

enable_prompt_management

def enable_prompt_management(cache: Optional[MaximCache] = None) -> "Maxim"

Enables prompt management functionality with optional cache configuration.

Arguments:

Name	Type	Description
cache	Optional[MaximCache], optional	Custom cache implementation to use.

Defaults to None (uses existing cache).

Returns:

Name	Description
[Maxim](/sdk/python/references/maxim)	The current Maxim instance for method chaining.

enable_exceptions

def enable_exceptions(val: bool) -> "Maxim"

Enables or disables exception raising during logging operations.

Arguments:

Name	Type	Description
val	bool	True to enable exception raising, False to disable.

Returns:

Name	Description
[Maxim](/sdk/python/references/maxim)	The current Maxim instance for method chaining.

get_prompt

def get_prompt(id: str, rule: QueryRule) -> Optional[RunnablePrompt]

Retrieves a prompt based on the provided id and rule.

Arguments:

Name	Type	Description
id	str	The id of the prompt.
rule	QueryRule	The rule to match the prompt against.

Returns:

Name	Description
Optional[[Prompt](/sdk/python/references/models/prompt)]	The prompt object if found, otherwise None.

get_prompts

def get_prompts(rule: QueryRule) -> List[RunnablePrompt]

Retrieves all prompts that match the given rule.

Arguments:

Name	Type	Description
rule	QueryRule	The rule to match the prompts against.

Returns:

Name	Description
List[[Prompt](/sdk/python/references/models/prompt)]	A list of prompts that match the given rule.

get_prompt_chain

def get_prompt_chain(id: str,
                     rule: QueryRule) -> Optional[RunnablePromptChain]

Retrieves a prompt chain based on the provided id and rule.

Arguments:

Name	Type	Description
id	str	The id of the prompt chain.
rule	QueryRule	The rule to match the prompt chain against.

Returns:

Name	Description
Optional[[PromptChain](/sdk/python/references/models/prompt_chain)]	The prompt chain object if found, otherwise None.

get_folder_by_id

def get_folder_by_id(id: str) -> Optional[Folder]

Retrieves a folder based on the provided id.

Arguments:

Name	Type	Description
id	str	The id of the folder.

Returns:

Name	Description
Optional[[Folder](/sdk/python/references/models/folder)]	The folder object if found, otherwise None.

get_folders

def get_folders(rule: QueryRule) -> List[Folder]

Retrieves all folders that match the given rule.

Arguments:

Name	Type	Description
rule	QueryRule	The rule to match the folders against.

Returns:

Name	Description
List[[Folder](/sdk/python/references/models/folder)]	A list of folders that match the given rule.

logger

def logger(
        config: Optional[Union[LoggerConfig,
                               LoggerConfigDict]] = None) -> Logger

Creates a logger based on the provided configuration.

Arguments:

Name	Type	Description
config	LoggerConfig	The configuration for the logger.

Returns:

Name	Description
[Logger](/sdk/python/references/logger/logger)	The logger object.

create_test_run

def create_test_run(name: str, in_workspace_id: str) -> TestRunBuilder

Creates a test run builder based on the provided name and workspace id.

Arguments:

Name	Type	Description
name	str	The name of the test run.
in_workspace_id	str	The workspace id to create the test run in.

Returns:

Name	Description
[TestRunBuilder](/sdk/python/references/test_runs/test_run_builder)	The test run builder object.

chat_completion

def chat_completion(model: str,
                    messages: List[ChatCompletionMessage],
                    tools: Optional[List[Tool]] = None,
                    **kwargs) -> Optional[PromptResponse]

Performs a chat completion request using the specified model and messages.

Arguments:

Name	Type	Description
model	str	The model name to use for completion. The expected format is “provider/model_name”. Example “openai/gpt-3.5-turbo”.
messages	List[ChatCompletionMessage]	List of chat messages in the conversation
tools	Optional[List[Tool]], optional	List of tools available to the model. Defaults to None.
**kwargs		Additional model parameters to pass to the completion request

Returns:

Name	Description
Optional[[PromptResponse](/sdk/python/references/models/prompt)]	The completion response if successful, None otherwise

cleanup

def cleanup()

Cleans up the Maxim sync thread.