Check if object is already a DICT before it is passed to JSON5.loads for parsing

XAgent/agent/base_agent.py

@@ -126,7 +126,9 @@ def generate(self,
                     *args,**kwargs)
 
                 message = {}
-                function_call_args:dict = json5.loads(response["choices"][0]["message"]["function_call"]['arguments'])
+                function_call_args:dict = response["choices"][0]["message"]["function_call"]['arguments']
+                if isinstance(function_call_args, (str, bytes)):
+                    function_call_args = json5.loads(function_call_args)
 
                 if arguments is not None:
                     message['arguments'] = {
@@ -147,7 +149,9 @@ def generate(self,
                     function_call=function_call,
                     stop=stop,
                     *args,**kwargs)
-                message = json5.loads(response["choices"][0]["message"]['content'])
+                message = response["choices"][0]["message"]['content']
+                if isinstance(message, (str, bytes)):
+                    message = json5.loads(message)
             case _:
                 raise NotImplementedError(f"Request type {CONFIG.default_request_type} not implemented")
 

XAgent/ai_functions/function_manager.py

@@ -115,15 +115,20 @@ def execute(self,function_name:str,return_generation_usage:bool=False,function_c
                     function_call={'name':function_cfg['function']['name']},
                     **completions_kwargs
                 )
-                returns = json5.loads(response['choices'][0]['message']['function_call']['arguments'])
+                returns = response['choices'][0]['message']['function_call']['arguments']
+                if isinstance(returns, (str, bytes)):
+                    returns = json5.loads(returns)
             case 'xagent':
                 arguments = function_cfg['function']['parameters']
                 response = objgenerator.chatcompletion(
                     messages=messages,
                     arguments=arguments,
                     **completions_kwargs
                 )
-                returns = json5.loads(response['choices'][0]['message']['content'])['arguments']
+                content = response['choices'][0]['message']['content']
+                if isinstance(content, (str, bytes)):
+                    returns = json5.loads(content)
+                returns = content['arguments']
 
         if return_generation_usage:
             return returns, response['usage']

XAgent/ai_functions/request/openai.py

@@ -1,5 +1,6 @@
 import json
 import openai
+import datetime as dt
 from XAgent.logs import logger
 from XAgent.config import CONFIG, get_apiconfig_by_model, get_model_name
 
@@ -60,6 +61,8 @@ def chatcompletion_request(**kwargs):
             chatcompletion_kwargs.update({"api_base": api_base})
         chatcompletion_kwargs.update(kwargs)
 
+        print(f"[{dt.datetime.now()}] chatcompletion:", chatcompletion_kwargs)
+
         try:
             response = openai.ChatCompletion.create(**chatcompletion_kwargs)
             response = json.loads(str(response))

XAgent/workflow/plan_exec.py

@@ -175,7 +175,11 @@ def initial_plan_generation(self, agent_dispatcher):
             functions=[split_functions], 
         )
 
-        subtasks = json5.loads(new_message["function_call"]["arguments"])
+        subtasks = new_message["function_call"]["arguments"] 
+
+        # To preserve the original flow in case `subtasks` is a string or bytes
+        if isinstance(subtasks, (str, bytes)):
+            subtasks = json5.loads(subtasks)
 
         for subtask_item in subtasks["subtasks"]:
             subplan = plan_function_output_parser(subtask_item)
@@ -270,7 +274,11 @@ def plan_refine_mode(self, now_dealing_task: Plan, toolserver_interface, agent_d
                 additional_insert_index=-1,
             )
             function_name = new_message["function_call"]["name"]
-            function_input = json5.loads(new_message["function_call"]["arguments"])
+            function_input = new_message["function_call"]["arguments"]
+
+            if isinstance(function_input, (str, bytes)):
+                function_input = json5.loads(function_input)
+
 
             if function_input['operation'] == 'split':
                 # modify function_input here

XAgent/workflow/reflection.py

@@ -57,6 +57,10 @@ def get_posterior_knowledge(all_plan: Plan,
         arguments=function_manager.get_function_schema('generate_posterior_knowledge')['parameters']
     )
 
-    data = json5.loads(new_message["arguments"])
+    data = new_message["arguments"]
+
+    # To preserve the original flow in case `data` is a string or bytes
+    if isinstance(data, (str, bytes)):
+        data = json5.loads(data)
 
     return data