Getting ready for merge

ChatHumanFlowModule.py

@@ -61,6 +61,8 @@ class ChatHumanFlowModule(CompositeFlow):
             additional_transformations = [self.regex_extractor, self.end_of_interaction]
         )
         
+        self.input_interface_user = KeyInterface()
+        
     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()
@@ -106,8 +108,9 @@ class ChatHumanFlowModule(CompositeFlow):
         :param input_message: The input message to the flow.
         :type input_message: FlowMessage
         """
-        self.flow_state["assistant_outputs"].append(input_message.data["api_output"])
-        message = self.package_input_message(data=input_message.data)
+        msg = self.input_interface_user(input_message)###I ADDED THIS
+        self.flow_state["assistant_outputs"].append(msg.data["api_output"])###I
+        message = self.package_input_message(data=msg.data)
 
         if self.max_rounds_reached():
             self.generate_reply()

run.py

@@ -31,7 +31,6 @@ flow_verse.sync_dependencies(dependencies)
 if __name__ == "__main__":
     
     #1. ~~~~~ Set up a colink server ~~~~
-    FLOW_MODULES_PATH = "./"
     
     cl = start_colink_server()
 
@@ -78,13 +77,7 @@ if __name__ == "__main__":
     data = {"id": 0, "query": "I want to ask you a few questions"}  # This can be a list of samples
     # data = {"id": 0, "question": "Who was the NBA champion in 2023?"}  # This can be a list of samples
     
-    #option1: use the FlowMessage class
-    input_message = FlowMessage(
-        data=data,
-    )
-
-    #option2: use the proxy_flow
-    #input_message = proxy_flow.package_input_message(data = data)
+    input_message = proxy_flow.package_input_message(data = data)
     
     #7. ~~~ Run inference ~~~
     future = proxy_flow.get_reply_future(input_message)