feat:注释大模型数据控制台打印
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@@ -122,7 +122,7 @@ def _call_with_custom_config(messages: list[dict], stream: bool, model_config: d
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if full_reply_content is None:
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raise Exception(f"API returned None content for model {api_model}")
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print(colored(full_reply_content, "blue", "on_white"), end="")
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#print(colored(full_reply_content, "blue", "on_white"), end="")
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return full_reply_content
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except Exception as e:
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print_colored(f"Custom API error for model {api_model} :{str(e)}","red")
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@@ -151,9 +151,9 @@ async def _achat_completion_stream_custom(messages:list[dict], temp_async_client
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chunk_message = choices[0].delta
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if chunk_message is not None:
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collected_messages.append(chunk_message)
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if chunk_message.content:
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print(colored(chunk_message.content, "blue", "on_white"), end="")
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print()
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# if chunk_message.content:
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# print(colored(chunk_message.content, "blue", "on_white"), end="")
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# print()
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full_reply_content = "".join(
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[m.content or "" for m in collected_messages if m is not None]
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)
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@@ -209,8 +209,8 @@ async def _achat_completion_stream_groq(messages: list[dict]) -> str:
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if full_reply_content is None:
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raise Exception("Groq API returned None content")
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print(colored(full_reply_content, "blue", "on_white"), end="")
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print()
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# print(colored(full_reply_content, "blue", "on_white"), end="")
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# print()
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return full_reply_content
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@@ -251,8 +251,8 @@ async def _achat_completion_stream_mixtral(messages: list[dict]) -> str:
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if full_reply_content is None:
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raise Exception("Mistral API returned None content")
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print(colored(full_reply_content, "blue", "on_white"), end="")
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print()
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# print(colored(full_reply_content, "blue", "on_white"), end="")
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# print()
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return full_reply_content
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@@ -277,12 +277,12 @@ async def _achat_completion_stream_gpt35(messages: list[dict]) -> str:
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chunk_message = choices[0].delta
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if chunk_message is not None:
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collected_messages.append(chunk_message) # save the message
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if chunk_message.content:
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print(
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colored(chunk_message.content, "blue", "on_white"),
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end="",
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)
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print()
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# if chunk_message.content:
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# print(
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# colored(chunk_message.content, "blue", "on_white"),
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# end="",
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# )
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# print()
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full_reply_content = "".join(
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[m.content or "" for m in collected_messages if m is not None]
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@@ -324,8 +324,8 @@ def _achat_completion_json(messages: list[dict] ) -> str:
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if full_reply_content is None:
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raise Exception("OpenAI API returned None content")
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print(colored(full_reply_content, "blue", "on_white"), end="")
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print()
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# print(colored(full_reply_content, "blue", "on_white"), end="")
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# print()
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return full_reply_content
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@@ -346,12 +346,12 @@ async def _achat_completion_stream(messages: list[dict]) -> str:
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chunk_message = choices[0].delta
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if chunk_message is not None:
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collected_messages.append(chunk_message) # save the message
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if chunk_message.content:
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print(
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colored(chunk_message.content, "blue", "on_white"),
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end="",
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)
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print()
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# if chunk_message.content:
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# print(
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# colored(chunk_message.content, "blue", "on_white"),
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# end="",
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# )
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# print()
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full_reply_content = "".join(
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[m.content or "" for m in collected_messages if m is not None]
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@@ -104,7 +104,7 @@ def agentAbilityScoring(Agent_Board, Ability_Requirement_List):
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),
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},
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]
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print(messages[1]["content"])
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#print(messages[1]["content"])
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scoreTable[Ability_Requirement] = read_LLM_Completion(messages)
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return scoreTable
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@@ -100,7 +100,7 @@ def generate_AgentSelection(General_Goal, Current_Task, Agent_Board):
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),
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},
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]
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print(messages[1]["content"])
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#print(messages[1]["content"])
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agentboard_set = {agent["Name"] for agent in Agent_Board}
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@@ -87,7 +87,7 @@ def branch_PlanOutline(
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InitialObject_List=str(InitialObject_List),
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General_Goal=General_Goal,
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)
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print(prompt)
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#print(prompt)
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branch_List = []
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for _ in range(branch_Number):
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messages = [
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@@ -155,7 +155,7 @@ def branch_TaskProcess(
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General_Goal=General_Goal,
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Act_Set=ACT_SET,
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)
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print(prompt)
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#print(prompt)
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branch_List = []
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for i in range(branch_Number):
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messages = [
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@@ -124,7 +124,7 @@ def generate_TaskProcess(General_Goal, Current_Task_Description):
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),
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},
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]
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print(messages[1]["content"])
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#print(messages[1]["content"])
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# write a callback function, if read_LLM_Completion(messages)["Task_Process_Plan"] dont have the right format, call this function again
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while True:
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@@ -107,7 +107,7 @@ class BaseAction():
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Action_Description = self.info["Description"],
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Action_Custom_Note = self.Action_Custom_Note
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)
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print_colored(text = prompt, text_color="red")
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#print_colored(text = prompt, text_color="red")
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messages = [{"role":"system", "content": prompt}]
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ActionResult = LLM_Completion(messages,True,False,model_config=model_config)
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ActionInfo_with_Result = copy.deepcopy(self.info)
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