fix multimodal input bug
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@@ -232,8 +232,11 @@ class AIAgent(BaseAIAgent):
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elif llm_result.state == LLMResultStates.IGNORE:
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return None
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else: # OK
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if llm_result.raw_result is not None:
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resp_msg = llm_result.raw_result.get("_resp_msg")
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return resp_msg
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else:
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return msg.create_resp_msg(llm_result.resp)
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async def _process_msg(self,msg:AgentMsg,workspace = None) -> AgentMsg:
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return await self.llm_process_msg(msg)
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@@ -2,6 +2,7 @@
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# pylint:disable=E0402
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import os.path
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from .chatsession import AIChatSession
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from ..utils import video_utils,image_utils
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from ..proto.compute_task import LLMPrompt,LLMResult,ComputeTaskResult,ComputeTaskResultCode
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@@ -165,7 +166,7 @@ class BaseLLMProcess(ABC):
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# Action define in prompt, will be execute after llm compute
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prompt = await self.prepare_prompt(input)
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max_result_token = self.max_token - ComputeKernel.llm_num_tokens(prompt,self.model_name)
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max_result_token = self.max_token - ComputeKernel.llm_num_tokens(prompt,self.get_llm_model_name())
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#if max_result_token < MIN_PREDICT_TOKEN_LEN:
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# return LLMResult.from_error_str(f"prompt too long,can not predict")
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@@ -196,7 +197,11 @@ class BaseLLMProcess(ABC):
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# parse task_result to LLM Result
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if self.enable_json_resp:
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try:
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llm_result = LLMResult.from_json_str(task_result.result_str)
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except Exception as e:
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logger.error(f"parse llm result error:{e}")
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llm_result = LLMResult.from_str(task_result.result_str)
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else:
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llm_result = LLMResult.from_str(task_result.result_str)
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@@ -402,14 +407,18 @@ class AgentMessageProcess(LLMAgentBaseProcess):
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if self.enable_media2text:
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logger.error(f"enable_media2text is not supported yet")
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else:
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audio_file = msg.body
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prompt, audio_file = msg.get_audio_body()
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resp = await (ComputeKernel.get_instance().do_speech_to_text(audio_file, model=self.asr_model, prompt=None, response_format="text"))
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if resp.result_code != ComputeTaskResultCode.OK:
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error_resp = msg.create_error_resp(resp.error_str)
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return error_resp
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else:
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if prompt == "":
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msg.body = resp.result_str
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msg_prompt.messages = [{"role":"user","content":resp.result_str}]
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else:
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msg.body = f"{prompt}\nVoice content:{resp.result_str}"
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msg_prompt.messages = [{"role":"user","content": prompt}, {"role": "user", "content": f"Voice content:{resp.result_str}"}]
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else:
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msg_prompt.messages = [{"role":"user","content":msg.body}]
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@@ -495,6 +504,7 @@ class AgentMessageProcess(LLMAgentBaseProcess):
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else:
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resp_msg = msg.create_resp_msg(llm_result.resp)
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if llm_result.raw_result is not None:
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llm_result.raw_result["_resp_msg"] = resp_msg
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action_params = {}
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@@ -210,9 +210,15 @@ class LLMResult:
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r.state = LLMResultStates.IGNORE
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return r
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try:
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if llm_result_str[0] == "{":
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return LLMResult.from_json_str(llm_result_str)
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if llm_result_str.lstrip().rstrip().startswith("```json"):
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return LLMResult.from_json_str(llm_result_str[7:-3])
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except:
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pass
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lines = llm_result_str.splitlines()
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is_need_wait = False
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@@ -255,6 +261,8 @@ class LLMResult:
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r.resp += current_action.dumps()
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else:
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r.action_list.append(current_action)
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r.state = LLMResultStates.OK
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return r
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class ComputeTask:
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@@ -206,7 +206,7 @@ class OpenAI_ComputeNode(ComputeNode):
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if mode_name == "gpt-4-vision-preview":
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response_format = NOT_GIVEN
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llm_inner_functions = None
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if max_token_size > 4096:
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if max_token_size > 4096 or max_token_size < 50:
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result_token = 4096
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else:
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result_token = -1
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