working async

salesgpt/agents.py

@@ -270,28 +270,70 @@ async def astep(self, stream: bool = False):
             Generator: A streaming generator object if stream is set to True. Otherwise, it returns None.
         """
         if not stream:
-            self._acall(inputs={})
+            return await self.acall(inputs={})
         else:
             return await self._astreaming_generator()
 
     @time_logger
-    def acall(self, *args, **kwargs):
+    async def acall(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
+
         """
-        This method is currently not implemented.
+        Executes one step of the sales agent.
+
+        This function overrides the input temporarily with the current state of the conversation,
+        generates the agent's utterance using either the sales agent executor or the sales conversation utterance chain,
+        adds the agent's response to the conversation history, and returns the AI message.
 
         Parameters
         ----------
-        \*args : tuple
-            Variable length argument list.
-        \*\*kwargs : dict
-            Arbitrary keyword arguments.
+        inputs : Dict[str, Any]
+            The initial inputs for the sales agent.
+
+        Returns
+        -------
+        Dict[str, Any]
+            The AI message generated by the sales agent.
 
-        Raises
-        ------
-        NotImplementedError
-            Indicates that this method has not been implemented yet.
         """
-        raise NotImplementedError("This method has not been implemented yet.")
+        # override inputs temporarily
+        inputs = {
+            "input": "",
+            "conversation_stage": self.current_conversation_stage,
+            "conversation_history": "\n".join(self.conversation_history),
+            "salesperson_name": self.salesperson_name,
+            "salesperson_role": self.salesperson_role,
+            "company_name": self.company_name,
+            "company_business": self.company_business,
+            "company_values": self.company_values,
+            "conversation_purpose": self.conversation_purpose,
+            "conversation_type": self.conversation_type,
+        }
+
+        # Generate agent's utterance
+        if self.use_tools:
+            ai_message = await self.sales_agent_executor.ainvoke(inputs)
+            output = ai_message["output"]
+        else:
+            ai_message = await self.sales_conversation_utterance_chain.ainvoke(
+                inputs, return_intermediate_steps=True
+            )
+            output = ai_message["text"]
+
+        # Add agent's response to conversation history
+        agent_name = self.salesperson_name
+        output = agent_name + ": " + output
+        if "<END_OF_TURN>" not in output:
+            output += " <END_OF_TURN>"
+        self.conversation_history.append(output)
+
+        if self.verbose:
+            tool_status = "USE TOOLS INVOKE:" if self.use_tools else "WITHOUT TOOLS:"
+            print(f"{tool_status}\n#\n#\n#\n#\n------------------")
+            print(f"AI Message: {ai_message}")
+            print()
+            print(f"Output: {output.replace('<END_OF_TURN>', '')}")
+
+        return ai_message
 
     @time_logger
     def _prep_messages(self):

salesgpt/salesgptapi.py

@@ -100,17 +100,17 @@ async def do(self, human_input=None):
             if self.sales_agent.conversation_history
             else ""
         )
+        print("AI LOG INTERMEDIATE STEPS: ", ai_log["intermediate_steps"])
 
         if (
-            self.use_tools
-            and ai_log["intermediate_steps"][1]["outputs"]["intermediate_steps"]
-            is not []
+            self.use_tools and 
+            "intermediate_steps" in ai_log and 
+            len(ai_log["intermediate_steps"]) > 0
         ):
+
             try:
-                res_str = ai_log["intermediate_steps"][1]["outputs"][
-                    "intermediate_steps"
-                ][0]
-                tool_search_result = res_str[0]
+                res_str = ai_log["intermediate_steps"][0]
+                print("RES STR: ", res_str)
                 agent_action = res_str[0]
                 tool, tool_input, log = (
                     agent_action.tool,
@@ -119,10 +119,9 @@ async def do(self, human_input=None):
                 )
                 actions = re.search(r"Action: (.*?)[\n]*Action Input: (.*)", log)
                 action_input = actions.group(2)
-                action_output = ai_log["intermediate_steps"][1]["outputs"][
-                    "intermediate_steps"
-                ][0][1]
-            except:
+                action_output =  res_str[1]
+            except Exception as e:
+                print("ERROR: ", e)
                 tool, tool_input, action, action_input, action_output = (
                     "",
                     "",