license: mit
Table of Contents
__init__
DemonstrationsAtomicFlow
DemonstrationsAtomicFlow Objects
class DemonstrationsAtomicFlow(AtomicFlow)
This class implements a Demonstrations Atomic Flow. It is a flow which is usually used to pass demonstrations (of user assistant interactions)
to the ChatAtomicFlow.
Configuration Parameters:
name
(str): The name of the flow. Default: "DemonstrationsAtomicFlow"description
(str): A description of the flow. This description is used to generate the help message of the flow. Default: "A flow that passes demonstrations to the ChatFlow"data
(List[Dict[str, Any]]): The data of the demonstrations. If data is None, the data is loaded from the file specified in the params["data_dir"]. Default: No default value this field must be set.params
(Dict[str, Any]): The parameters specific to the dataset of the demonstrations. Its default parameters are:data_dir
(str): The directory where the demonstrations are stored. If the data is not directly passed to the flow throughdata
then the data is loaded from this directory. Default: No default value this field must be set.demonstrations_id
(str): The id of the demonstrations (name of the data file). If the data is not directly passed to the flow throughdata
then the data is loaded from this file. Default: No default value this field must be set.demonstrations_k
(int): The number of demonstrations to pass to the ChatFlow. If None, all the demonstrations are passed to the ChatFlow. Default: None
query_prompt_template
(Dict[str, Any]): The prompt template used to generate the query of the demonstrations. By default its of type aiflows.prompt_template.JinjaPrompt. None of the parameters of the prompt are defined by default and therefore need to be defined if one wants to use the query_prompt_template. Default parameters are defined in aiflows.prompt_template.jinja2_prompts.JinjaPrompt.response_prompt_template
(Dict[str, Any]): The prompt template used to generate the response of the demonstrations. By default its of type aiflows.prompt_template.JinjaPrompt. None of the parameters of the prompt are defined by default and therefore need to be defined if one wants to use the response_prompt_template. Default parameters are defined in aiflows.prompt_template.jinja2_prompts.JinjaPrompt.
Input Interface:
- The input interface expected by its successor flow (e.g. typically ChatAtomicFlow so the input interface is the one expected by ChatAtomicFlow)
Output Interface:
- The input interface expected by its successor flow (e.g. typically ChatAtomicFlow so the input interface expected by ChatAtomicFlow))
demonstrations
(List[Dict[str, Any]]): A list of demonstrations. Each demonstration is a dictionary with the following keys: - idx (int): The index of the demonstration - query (str): The query of the demonstration - response (str): The response of the demonstration
Arguments:
params
(Dict[str, Any]
): The parameters specific to the dataset of the demonstrations. It must sould contain the following keys:- 'data_dir' (str): The directory where the demonstrations are stored. This field is used if the data is not directly passed to the flow through the 'data' field.
- 'demonstrations_id' (str): The id of the demonstrations (name of the data file). This field is used if the data is not directly passed to the flow through the 'data' field.
- 'demonstrations_k' (int): The number of demonstrations to pass to the ChatFlow. If None, all the demonstrations are passed to the ChatFlow.
- 'ids_to_keep' (Optional[Union[str, List[str]]]): The ids of the demonstrations to keep. If None, all the demonstrations are kept.
query_prompt_template
(JinjaPrompt
): The prompt template used to generate the query of the demonstrations.response_prompt_template
(JinjaPrompt
): The prompt template used to generate the response of the demonstrations.data
(Optional[List[Dict[str, Any]]]
): The data of the demonstrations. If None, the data is loaded from the file specified in the params.
instantiate_from_config
@classmethod
def instantiate_from_config(cls, config)
This method instantiates the flow from a config file.
Arguments:
config
(Dict[str, Any]
): The configuration of the flow.
Returns:
Flow
: The instantiated flow.
run
def run(input_data: Dict[str, Any]) -> Dict[str, Any]
This method runs the flow. It returns the input data of the flow with the demonstrations added to it.
Arguments:
input_data
(Dict[str, Any]
): The input data of the flow.
Returns:
Dict[str, Any]
: The input data of the flow with the demonstrations added to it.
ChatWithDemonstrationsFlow
ChatWithDemonstrationsFlow Objects
class ChatWithDemonstrationsFlow(SequentialFlow)
A Chat with Demonstrations Flow. It is a flow that consists of multiple sub-flows that are executed sequentially.
It's parent class is SequentialFlow.
It Contains the following subflows:
- A Demonstration Flow: It is a flow that passes demonstrations to the ChatFlow
- A Chat Flow: It is a flow that uses the demonstrations to answer queries asked by the user/human.
An illustration of the flow is as follows:
-------> Demonstration Flow -------> Chat Flow ------->
Configuration Parameters:
name
(str): The name of the flow. Default: "ChatAtomic_Flow_with_Demonstrations"description
(str): A description of the flow. This description is used to generate the help message of the flow. Default: "A sequential flow that answers questions with demonstrations"subflows_config
(Dict[str,Any]): A dictionary of subflows configurations of the sequential Flow. Default:Demonstration Flow
: The configuration of the Demonstration Flow. By default, it a DemonstrationsAtomicFlow. Its default parmaters are defined in DemonstrationsAtomicFlow).Chat Flow
: The configuration of the Chat Flow. By default, its a ChatAtomicFlow. Its default parmaters are defined in ChatAtomicFlowModule (see Flowcard, i.e. README.md, of ChatAtomicFlowModule).
topology
(str): The topology of the flow which is "sequential". By default, the topology is the one shown in the illustration above (the topology is also described in ChatWithDemonstrationsFlow.yaml).
Input Interface:
query
(str): A query asked to the flow (e.g. "What is the capital of France?")
Output Interface:
answer
(str): The answer of the flow to the query
Arguments:
\**kwargs
: Arguments to be passed to the parent class SequentialFlow constructor.