Clients

datapizza.core.clients.client.Client

Bases: ChainableProducer

Represents the base class for all clients. Concrete implementations must implement the abstract methods to handle the actual inference.

a_embed async

a_embed(text, model_name=None, **kwargs)

Embed a text using the model

Parameters:

Name	Type	Description	Default
text	str | list[str]	The text to embed	required
model_name	str	The name of the model to use. Defaults to None.	None
**kwargs		Additional keyword arguments to pass to the model's embedding method	{}

Returns:

Type	Description
list[float] | list[list[float]]	list[float]: The embedding vector for the text

a_invoke async

a_invoke(
    input,
    tools=None,
    memory=None,
    tool_choice="auto",
    temperature=None,
    max_tokens=None,
    system_prompt=None,
    **kwargs,
)

Performs a single inference request to the model.

Parameters:

Name	Type	Description	Default
input	str	The input text/prompt to send to the model	required
tools	List[Tool]	List of tools available for the model to use. Defaults to [].	None
memory	Memory	Memory object containing conversation history. Defaults to None.	None
tool_choice	str	Controls which tool to use. Defaults to "auto".	'auto'
temperature	float	Controls randomness in responses. Defaults to None.	None
max_tokens	int	Maximum number of tokens in the response. Defaults to None.	None
system_prompt	str	System-level instructions for the model. Defaults to None.	None
**kwargs		Additional keyword arguments to pass to the model's inference method	{}

Returns:

Type	Description
ClientResponse	A ClientResponse object containing the model's response

a_stream_invoke async

a_stream_invoke(
    input,
    tools=None,
    memory=None,
    tool_choice="auto",
    temperature=None,
    max_tokens=None,
    system_prompt=None,
    **kwargs,
)

Streams the model's response token by token asynchronously.

Parameters:

Name	Type	Description	Default
input	str	The input text/prompt to send to the model	required
tools	List[Tool]	List of tools available for the model to use. Defaults to [].	None
memory	Memory	Memory object containing conversation history. Defaults to None.	None
tool_choice	str	Controls which tool to use. Defaults to "auto".	'auto'
temperature	float	Controls randomness in responses. Defaults to None.	None
max_tokens	int	Maximum number of tokens in the response. Defaults to None.	None
system_prompt	str	System-level instructions for the model. Defaults to None.	None
**kwargs		Additional keyword arguments to pass to the model's inference method	{}

Returns:

Type	Description
AsyncIterator[ClientResponse]	An async iterator yielding ClientResponse objects containing the model's response

a_structured_response async

a_structured_response(
    *,
    input,
    output_cls,
    memory=None,
    temperature=None,
    max_tokens=None,
    system_prompt=None,
    tools=None,
    tool_choice="auto",
    **kwargs,
)

Structures the model's response according to a specified output class.

Parameters:

Name	Type	Description	Default
input	str	The input text/prompt to send to the model	required
output_cls	Type[Model]	The class type to structure the response into	required
memory	Memory	Memory object containing conversation history. Defaults to None.	None
temperature	float	Controls randomness in responses. Defaults to None.	None
max_tokens	int	Maximum number of tokens in the response. Defaults to None.	None
system_prompt	str	System-level instructions for the model. Defaults to None.	None
tools	List[Tool]	List of tools available for the model to use. Defaults to [].	None
tool_choice	Literal['auto', 'required', 'none'] | list[str]	Controls which tool to use ("auto" by default). Defaults to "auto".	'auto'
**kwargs		Additional keyword arguments to pass to the model's inference method	{}

Returns:

Type	Description
ClientResponse	A ClientResponse object containing the structured response

embed

embed(text, model_name=None, **kwargs)

Embed a text using the model

Parameters:

Name	Type	Description	Default
text	str | list[str]	The text to embed	required
model_name	str	The name of the model to use. Defaults to None.	None
**kwargs		Additional keyword arguments to pass to the model's embedding method	{}

Returns:

Type	Description
list[float]	list[float]: The embedding vector for the text

invoke

invoke(
    input,
    tools=None,
    memory=None,
    tool_choice="auto",
    temperature=None,
    max_tokens=None,
    system_prompt=None,
    **kwargs,
)

Performs a single inference request to the model.

Parameters:

Name	Type	Description	Default
input	str	The input text/prompt to send to the model	required
tools	List[Tool]	List of tools available for the model to use. Defaults to [].	None
memory	Memory	Memory object containing conversation history. Defaults to None.	None
tool_choice	str	Controls which tool to use. Defaults to "auto".	'auto'
temperature	float	Controls randomness in responses. Defaults to None.	None
max_tokens	int	Maximum number of tokens in the response. Defaults to None.	None
system_prompt	str	System-level instructions for the model. Defaults to None.	None
**kwargs		Additional keyword arguments to pass to the model's inference method	{}

Returns:

Type	Description
ClientResponse	A ClientResponse object containing the model's response

stream_invoke

stream_invoke(
    input,
    tools=None,
    memory=None,
    tool_choice="auto",
    temperature=None,
    max_tokens=None,
    system_prompt=None,
    **kwargs,
)

Streams the model's response token by token.

Parameters:

Name	Type	Description	Default
input	str	The input text/prompt to send to the model	required
tools	List[Tool]	List of tools available for the model to use. Defaults to [].	None
memory	Memory	Memory object containing conversation history. Defaults to None.	None
tool_choice	str	Controls which tool to use. Defaults to "auto".	'auto'
temperature	float	Controls randomness in responses. Defaults to None.	None
max_tokens	int	Maximum number of tokens in the response. Defaults to None.	None
system_prompt	str	System-level instructions for the model. Defaults to None.	None
**kwargs		Additional keyword arguments to pass to the model's inference method	{}

Returns:

Type	Description
Iterator[ClientResponse]	An iterator yielding ClientResponse objects containing the model's response

structured_response

structured_response(
    *,
    input,
    output_cls,
    memory=None,
    temperature=None,
    max_tokens=None,
    system_prompt=None,
    tools=None,
    tool_choice="auto",
    **kwargs,
)

Structures the model's response according to a specified output class.

Parameters:

Name	Type	Description	Default
input	str	The input text/prompt to send to the model	required
output_cls	Type[Model]	The class type to structure the response into	required
memory	Memory	Memory object containing conversation history. Defaults to None.	None
temperature	float	Controls randomness in responses. Defaults to None.	None
max_tokens	int	Maximum number of tokens in the response. Defaults to None.	None
system_prompt	str	System-level instructions for the model. Defaults to None.	None
tools	List[Tool]	List of tools available for the model to use. Defaults to [].	None
tool_choice	Literal['auto', 'required', 'none'] | list[str]	Controls which tool to use ("auto" by default). Defaults to "auto".	'auto'
**kwargs		Additional keyword arguments to pass to the model's inference method	{}

Returns:

Type	Description
ClientResponse	A ClientResponse object containing the structured response