Clean Versions

ChatHumanFlowModule.py

@@ -47,7 +47,6 @@ class ChatHumanFlowModule(CompositeFlow):
     :type \**kwargs: Dict[str, Any]
     """
     
-
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
         
@@ -65,7 +64,7 @@ class ChatHumanFlowModule(CompositeFlow):
     def set_up_flow_state(self):
         """ This method sets up the flow state. It is called when the flow is executed."""
         super().set_up_flow_state()
-        self.flow_state["last_flow_called"] = None
+        self.flow_state["last_state"] = None
         self.flow_state["current_round"] = 0
         self.flow_state["user_inputs"] = []
         self.flow_state["assistant_outputs"] = []
@@ -78,10 +77,14 @@ class ChatHumanFlowModule(CompositeFlow):
         return "OpenAIChatHumanFlowModule"
     
     def max_rounds_reached(self):
+        """ This method checks if the maximum number of rounds has been reached. If the maximum number of rounds has been reached, it returns True. Otherwise, it returns False."""
         return self.flow_config["max_rounds"] is not None and self.flow_state["current_round"] >= self.flow_config["max_rounds"]
     
     def generate_reply(self):
-        
+        """ This method generates the reply message. It is called when the interaction is finished.
+        :param input_message: The input message to the flow.
+        :type input_message: FlowMessage
+        """
         reply = self.package_output_message(
             input_message = self.flow_state["input_message"],
             response = {
@@ -98,7 +101,11 @@ class ChatHumanFlowModule(CompositeFlow):
             
     
     def call_to_user(self,input_message):
+        """ This method calls the User Flow. (Human)
         
+        :param input_message: The input message to the flow.
+        :type input_message: FlowMessage
+        """
         self.flow_state["assistant_outputs"].append(input_message.data["api_output"])
 
         if self.max_rounds_reached():
@@ -108,16 +115,21 @@ class ChatHumanFlowModule(CompositeFlow):
                 input_message,
                 self.get_instance_id(),
             )
-            self.flow_state["last_flow_called"] = "User"
+            self.flow_state["last_state"] = "User"
         
         self.flow_state["current_round"] += 1
         
         
             
     def call_to_assistant(self,input_message):
+        """ This method calls the Assistant Flow.
+
+        :param input_message: The input message to the flow.
+        :type input_message: FlowMessage
+        """
         message = self.input_interface_assistant(input_message)
         
-        if  self.flow_state["last_flow_called"] is None:
+        if  self.flow_state["last_state"] is None:
             self.flow_state["input_message"] = input_message
         
         else:
@@ -132,7 +144,7 @@ class ChatHumanFlowModule(CompositeFlow):
                 message,
                 self.get_instance_id()
             )
-            self.flow_state["last_flow_called"] = "Assistant"    
+            self.flow_state["last_state"] = "Assistant"    
     
     def run(self,input_message: FlowMessage):
         """ This method runs the flow. It is the main method of the flow and it is called when the flow is executed.
@@ -140,13 +152,13 @@ class ChatHumanFlowModule(CompositeFlow):
         :param input_message: The input message to the flow.
         :type input_message: FlowMessage
         """
-        last_flow_called = self.flow_state["last_flow_called"]
+        last_state = self.flow_state["last_state"]
         
-        if last_flow_called is None or last_flow_called == "User":
+        if last_state is None or last_state == "User":
             self.call_to_assistant(input_message=input_message)
             
             
-        elif last_flow_called == "Assistant":
+        elif last_state == "Assistant":
             self.call_to_user(input_message=input_message)
             
             

ChatHumanFlowModule.yaml

@@ -1,6 +1,6 @@
 name: "ChatInteractiveFlow"
 description: "Flow that enables chatting between a ChatAtomicFlow and a user providing the input."
-
+_target_: flow_modules.aiflows.ChatInteractiveFlowModule.ChatHumanFlowModule.instantiate_from_default_config
 max_rounds: null # Run until early exit is detected
 
 input_interface:
@@ -26,8 +26,14 @@ end_of_interaction:
 subflows_config:
   Assistant:
     _target_: flow_modules.aiflows.ChatFlowModule.ChatAtomicFlow.instantiate_from_default_config
+    flow_class_name: flow_modules.aiflows.ChatFlowModule.ChatAtomicFlow
+    flow_endpoint: Assistant
+    user_id: local
   User:
     _target_: flow_modules.aiflows.HumanStandardInputFlowModule.HumanStandardInputFlow.instantiate_from_default_config
+    flow_class_name: flow_modules.aiflows.HumanStandardInputFlowModule.HumanStandardInputFlow
+    flow_endpoint: User
+    user_id: local
 
 
 

demo.yaml

@@ -3,7 +3,11 @@ max_rounds: 2
 _target_: flow_modules.aiflows.ChatInteractiveFlowModule.ChatHumanFlowModule.instantiate_from_default_config
 subflows_config:
   Assistant:
-    _target_: flow_modules.aiflows.ChatFlowModule.ChatAtomicFlow.instantiate_from_default_config
+    name: "Assistantflow"
+    description: "A flow that represents the assistant."
+    _target_: aiflows.base_flows.AtomicFlow.instantiate_from_default_config
+    user_id: local
+    flow_endpoint: Assistant
     backend:
       _target_: aiflows.backends.llm_lite.LiteLLMBackend
       api_infos: ???
@@ -13,7 +17,11 @@ subflows_config:
     input_interface_non_initialized: []
     
   User:
-    _target_: flow_modules.aiflows.HumanStandardInputFlowModule.HumanStandardInputFlow.instantiate_from_default_config
+    _target_: aiflows.base_flows.AtomicFlow.instantiate_from_default_config
+    user_id: local
+    flow_endpoint: User
+    name: "User"
+    description: "A flow that represents the user."
     request_multi_line_input_flag: False
     query_message_prompt_template: 
       _target_: aiflows.prompt_template.JinjaPrompt

run.py

@@ -57,25 +57,22 @@ if __name__ == "__main__":
     
     #3. ~~~~ Serve The Flow ~~~~
     serve_utils.recursive_serve_flow(
-        cl = cl,
-        flow_type="ChatInteractiveFlowModule",
-        default_config=cfg,
-        default_state=None,
-        default_dispatch_point="coflows_dispatch"
+        cl=cl,
+        flow_class_name="flow_modules.aiflows.ChatInteractiveFlowModule.ChatHumanFlowModule",
+        flow_endpoint="ChatHumanFlowModule",
     )
     
+    
     #4. ~~~~~Start A Worker Thread~~~~~
-    run_dispatch_worker_thread(cl, dispatch_point="coflows_dispatch", flow_modules_base_path=FLOW_MODULES_PATH)
+    run_dispatch_worker_thread(cl)
 
     #5. ~~~~~Mount the flow and get its proxy~~~~~~
-    proxy_flow = serve_utils.recursive_mount(
+    proxy_flow= serve_utils.get_flow_instance(
         cl=cl,
-        client_id="local",
-        flow_type="ChatInteractiveFlowModule",
-        config_overrides=None,
-        initial_state=None,
-        dispatch_point_override=None,
-    )   
+        flow_endpoint="ChatHumanFlowModule",
+        user_id="local",
+        config_overrides= cfg
+    )  
     
     #6. ~~~ Get the data ~~~
     data = {"id": 0, "query": "I want to ask you a few questions"}  # This can be a list of samples