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curl -L -o ChatWithDemonstrationsFlow.py https://huggingface.co/aiflows/ChatWithDemonstrationsFlowModule/resolve/210a49bd651e3e47ad837888e4e466cfef5bce58/ChatWithDemonstrationsFlow.py
4.36 kB
| from aiflows.base_flows import CompositeFlow | |
| from aiflows.utils import logging | |
| from aiflows.interfaces import KeyInterface | |
| logging.set_verbosity_debug() | |
| from aiflows.messages import FlowMessage | |
| log = logging.get_logger(__name__) | |
| class ChatWithDemonstrationsFlow(CompositeFlow): | |
| """ 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 | |
| :param \**kwargs: Arguments to be passed to the parent class SequentialFlow constructor. | |
| """ | |
| def __init__(self,**kwargs): | |
| super().__init__(**kwargs) | |
| self.output_interface = KeyInterface( | |
| keys_to_rename={"api_output": "answer"} | |
| ) | |
| def set_up_flow_state(self): | |
| """ Set up the flow state. It sets the last state of the flow to None. | |
| """ | |
| super().set_up_flow_state() | |
| self.flow_state["last_state"] = None | |
| def run(self,input_message): | |
| """ Runs the flow. | |
| :param input_message: The input message of the flow. | |
| :type input_message: FlowMessage | |
| """ | |
| # #~~~~~~~~~~~Solution 1 - Blocking ~~~~~~~ | |
| # future = self.subflows["demonstration_flow"].get_reply_future(input_message) | |
| # answer = self.subflows["chat_flow"].get_reply_future(future.get_message()) | |
| #reply = self.package_output_message(input_message, self.output_interface(answer.get_data())) | |
| # self.send_message(reply) | |
| # #~~~~~~~~~~~Solution 2 - Non-Blocking ~~~~~~~ | |
| if self.flow_state["last_state"] is None: | |
| self.flow_state["initial_message"] = input_message | |
| msg = self.package_input_message( | |
| input_message.data | |
| ) | |
| self.subflows["demonstration_flow"].get_reply( | |
| msg, | |
| ) | |
| self.flow_state["last_state"] = "demonstration_flow" | |
| elif self.flow_state["last_state"] == "demonstration_flow": | |
| msg = self.package_input_message( | |
| input_message.data | |
| ) | |
| self.subflows["chat_flow"].get_reply( | |
| msg, | |
| ) | |
| self.flow_state["last_state"] = "chat_flow" | |
| else: | |
| self.flow_state["last_state"] = None | |
| reply = self.package_output_message( | |
| self.flow_state["initial_message"], | |
| response = self.output_interface(input_message).data | |
| ) | |
| self.send_message( | |
| reply | |
| ) | |