Open fengyunzaidushi opened 6 months ago
{ "name": "BadRequestError", "message": "Error code: 400 - {'error': {'message': '\\'\\\ Use this tool to load data from the following function. It must then be read from\\\ the corresponding read_search_and_retrieve_documents function.\\\ \\\ search_and_retrieve_documents(query: str, num_results: Union[int, NoneType] = 10, include_domains: Union[List[str], NoneType] = None, exclude_domains: Union[List[str], NoneType] = None, start_published_date: Union[str, NoneType] = None, end_published_date: Union[str, NoneType] = None) -> List[llama_index.schema.Document]\\\ \\\ Combines the functionality of `search` and `retrieve_documents`\\\ \\\ Args:\\\ query (str): the natural language query\\\ num_results (Optional[int]): Number of results. Defaults to 10.\\\ include_domains (Optional[List(str)]): A list of top level domains to search, like [\"wsj.com\"]\\\ exclude_domains (Optional[List(str)]): Top level domains to exclude.\\\ start_published_date (Optional[str]): A date string like \"2020-06-15\".\\\ end_published_date (Optional[str]): End date string\\\ \\\ \\' is too long - \\'tools.0.function.description\\'', 'type': 'invalid_request_error', 'param': None, 'code': None}}", "stack": "--------------------------------------------------------------------------- BadRequestError Traceback (most recent call last) /mnt/sda/github/01yue/llama-hub/llama_hub/tools/notebooks/exa.ipynb 单元格 26 line 2 <a href='vscode-notebook-cell:/mnt/sda/github/01yue/llama-hub/llama_hub/tools/notebooks/exa.ipynb#Y113sZmlsZQ%3D%3D?line=0'>1</a> print( ----> <a href='vscode-notebook-cell:/mnt/sda/github/01yue/llama-hub/llama_hub/tools/notebooks/exa.ipynb#Y113sZmlsZQ%3D%3D?line=1'>2</a> agent.chat( <a href='vscode-notebook-cell:/mnt/sda/github/01yue/llama-hub/llama_hub/tools/notebooks/exa.ipynb#Y113sZmlsZQ%3D%3D?line=2'>3</a> \"Can you summarize everything published in the last month regarding news on\" <a href='vscode-notebook-cell:/mnt/sda/github/01yue/llama-hub/llama_hub/tools/notebooks/exa.ipynb#Y113sZmlsZQ%3D%3D?line=3'>4</a> \" research augment generation\" <a href='vscode-notebook-cell:/mnt/sda/github/01yue/llama-hub/llama_hub/tools/notebooks/exa.ipynb#Y113sZmlsZQ%3D%3D?line=4'>5</a> ) <a href='vscode-notebook-cell:/mnt/sda/github/01yue/llama-hub/llama_hub/tools/notebooks/exa.ipynb#Y113sZmlsZQ%3D%3D?line=5'>6</a> ) File /mnt/sda/github/12yue/llama_index/llama_index/callbacks/utils.py:41, in trace_method.<locals>.decorator.<locals>.wrapper(self, *args, **kwargs) 39 callback_manager = cast(CallbackManager, callback_manager) 40 with callback_manager.as_trace(trace_id): ---> 41 return func(self, *args, **kwargs) File /mnt/sda/github/12yue/llama_index/llama_index/agent/runner/base.py:497, in AgentRunner.chat(self, message, chat_history, tool_choice) 492 tool_choice = self.default_tool_choice 493 with self.callback_manager.event( 494 CBEventType.AGENT_STEP, 495 payload={EventPayload.MESSAGES: [message]}, 496 ) as e: --> 497 chat_response = self._chat( 498 message, chat_history, tool_choice, mode=ChatResponseMode.WAIT 499 ) 500 assert isinstance(chat_response, AgentChatResponse) 501 e.on_end(payload={EventPayload.RESPONSE: chat_response}) File /mnt/sda/github/12yue/llama_index/llama_index/agent/runner/base.py:442, in AgentRunner._chat(self, message, chat_history, tool_choice, mode) 439 result_output = None 440 while True: 441 # pass step queue in as argument, assume step executor is stateless --> 442 cur_step_output = self._run_step( 443 task.task_id, mode=mode, tool_choice=tool_choice 444 ) 446 if cur_step_output.is_last: 447 result_output = cur_step_output File /mnt/sda/github/12yue/llama_index/llama_index/agent/runner/base.py:304, in AgentRunner._run_step(self, task_id, step, mode, **kwargs) 300 # TODO: figure out if you can dynamically swap in different step executors 301 # not clear when you would do that by theoretically possible 303 if mode == ChatResponseMode.WAIT: --> 304 cur_step_output = self.agent_worker.run_step(step, task, **kwargs) 305 elif mode == ChatResponseMode.STREAM: 306 cur_step_output = self.agent_worker.stream_step(step, task, **kwargs) File /mnt/sda/github/12yue/llama_index/llama_index/callbacks/utils.py:41, in trace_method.<locals>.decorator.<locals>.wrapper(self, *args, **kwargs) 39 callback_manager = cast(CallbackManager, callback_manager) 40 with callback_manager.as_trace(trace_id): ---> 41 return func(self, *args, **kwargs) File /mnt/sda/github/12yue/llama_index/llama_index/agent/openai/step.py:573, in OpenAIAgentWorker.run_step(self, step, task, **kwargs) 571 \"\"\"Run step.\"\"\" 572 tool_choice = kwargs.get(\"tool_choice\", \"auto\") --> 573 return self._run_step( 574 step, task, mode=ChatResponseMode.WAIT, tool_choice=tool_choice 575 ) File /mnt/sda/github/12yue/llama_index/llama_index/agent/openai/step.py:448, in OpenAIAgentWorker._run_step(self, step, task, mode, tool_choice) 444 openai_tools = [tool.metadata.to_openai_tool() for tool in tools] 446 llm_chat_kwargs = self._get_llm_chat_kwargs(task, openai_tools, tool_choice) --> 448 agent_chat_response = self._get_agent_response( 449 task, mode=mode, **llm_chat_kwargs 450 ) 452 # TODO: implement _should_continue 453 latest_tool_calls = self.get_latest_tool_calls(task) or [] File /mnt/sda/github/12yue/llama_index/llama_index/agent/openai/step.py:322, in OpenAIAgentWorker._get_agent_response(self, task, mode, **llm_chat_kwargs) 318 def _get_agent_response( 319 self, task: Task, mode: ChatResponseMode, **llm_chat_kwargs: Any 320 ) -> AGENT_CHAT_RESPONSE_TYPE: 321 if mode == ChatResponseMode.WAIT: --> 322 chat_response: ChatResponse = self._llm.chat(**llm_chat_kwargs) 323 return self._process_message(task, chat_response) 324 elif mode == ChatResponseMode.STREAM: File /mnt/sda/github/12yue/llama_index/llama_index/llms/base.py:100, in llm_chat_callback.<locals>.wrap.<locals>.wrapped_llm_chat(_self, messages, **kwargs) 91 with wrapper_logic(_self) as callback_manager: 92 event_id = callback_manager.on_event_start( 93 CBEventType.LLM, 94 payload={ (...) 98 }, 99 ) --> 100 f_return_val = f(_self, messages, **kwargs) 102 if isinstance(f_return_val, Generator): 103 # intercept the generator and add a callback to the end 104 def wrapped_gen() -> ChatResponseGen: File /mnt/sda/github/12yue/llama_index/llama_index/llms/openai.py:237, in OpenAI.chat(self, messages, **kwargs) 235 else: 236 chat_fn = completion_to_chat_decorator(self._complete) --> 237 return chat_fn(messages, **kwargs) File /mnt/sda/github/12yue/llama_index/llama_index/llms/openai.py:296, in OpenAI._chat(self, messages, **kwargs) 294 client = self._get_client() 295 message_dicts = to_openai_message_dicts(messages) --> 296 response = client.chat.completions.create( 297 messages=message_dicts, 298 stream=False, 299 **self._get_model_kwargs(**kwargs), 300 ) 301 openai_message = response.choices[0].message 302 message = from_openai_message(openai_message) File /opt/miniconda3/envs/llamapy38/lib/python3.8/site-packages/openai/_utils/_utils.py:271, in required_args.<locals>.inner.<locals>.wrapper(*args, **kwargs) 269 msg = f\"Missing required argument: {quote(missing[0])}\" 270 raise TypeError(msg) --> 271 return func(*args, **kwargs) File /opt/miniconda3/envs/llamapy38/lib/python3.8/site-packages/openai/resources/chat/completions.py:648, in Completions.create(self, messages, model, frequency_penalty, function_call, functions, logit_bias, logprobs, max_tokens, n, presence_penalty, response_format, seed, stop, stream, temperature, tool_choice, tools, top_logprobs, top_p, user, extra_headers, extra_query, extra_body, timeout) 599 @required_args([\"messages\", \"model\"], [\"messages\", \"model\", \"stream\"]) 600 def create( 601 self, (...) 646 timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, 647 ) -> ChatCompletion | Stream[ChatCompletionChunk]: --> 648 return self._post( 649 \"/chat/completions\", 650 body=maybe_transform( 651 { 652 \"messages\": messages, 653 \"model\": model, 654 \"frequency_penalty\": frequency_penalty, 655 \"function_call\": function_call, 656 \"functions\": functions, 657 \"logit_bias\": logit_bias, 658 \"logprobs\": logprobs, 659 \"max_tokens\": max_tokens, 660 \"n\": n, 661 \"presence_penalty\": presence_penalty, 662 \"response_format\": response_format, 663 \"seed\": seed, 664 \"stop\": stop, 665 \"stream\": stream, 666 \"temperature\": temperature, 667 \"tool_choice\": tool_choice, 668 \"tools\": tools, 669 \"top_logprobs\": top_logprobs, 670 \"top_p\": top_p, 671 \"user\": user, 672 }, 673 completion_create_params.CompletionCreateParams, 674 ), 675 options=make_request_options( 676 extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout 677 ), 678 cast_to=ChatCompletion, 679 stream=stream or False, 680 stream_cls=Stream[ChatCompletionChunk], 681 ) File /opt/miniconda3/envs/llamapy38/lib/python3.8/site-packages/openai/_base_client.py:1179, in SyncAPIClient.post(self, path, cast_to, body, options, files, stream, stream_cls) 1165 def post( 1166 self, 1167 path: str, (...) 1174 stream_cls: type[_StreamT] | None = None, 1175 ) -> ResponseT | _StreamT: 1176 opts = FinalRequestOptions.construct( 1177 method=\"post\", url=path, json_data=body, files=to_httpx_files(files), **options 1178 ) -> 1179 return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)) File /opt/miniconda3/envs/llamapy38/lib/python3.8/site-packages/openai/_base_client.py:868, in SyncAPIClient.request(self, cast_to, options, remaining_retries, stream, stream_cls) 859 def request( 860 self, 861 cast_to: Type[ResponseT], (...) 866 stream_cls: type[_StreamT] | None = None, 867 ) -> ResponseT | _StreamT: --> 868 return self._request( 869 cast_to=cast_to, 870 options=options, 871 stream=stream, 872 stream_cls=stream_cls, 873 remaining_retries=remaining_retries, 874 ) File /opt/miniconda3/envs/llamapy38/lib/python3.8/site-packages/openai/_base_client.py:959, in SyncAPIClient._request(self, cast_to, options, remaining_retries, stream, stream_cls) 956 err.response.read() 958 log.debug(\"Re-raising status error\") --> 959 raise self._make_status_error_from_response(err.response) from None 961 return self._process_response( 962 cast_to=cast_to, 963 options=options, (...) 966 stream_cls=stream_cls, 967 ) BadRequestError: Error code: 400 - {'error': {'message': '\\'\\\ Use this tool to load data from the following function. It must then be read from\\\ the corresponding read_search_and_retrieve_documents function.\\\ \\\ search_and_retrieve_documents(query: str, num_results: Union[int, NoneType] = 10, include_domains: Union[List[str], NoneType] = None, exclude_domains: Union[List[str], NoneType] = None, start_published_date: Union[str, NoneType] = None, end_published_date: Union[str, NoneType] = None) -> List[llama_index.schema.Document]\\\ \\\ Combines the functionality of `search` and `retrieve_documents`\\\ \\\ Args:\\\ query (str): the natural language query\\\ num_results (Optional[int]): Number of results. Defaults to 10.\\\ include_domains (Optional[List(str)]): A list of top level domains to search, like [\"wsj.com\"]\\\ exclude_domains (Optional[List(str)]): Top level domains to exclude.\\\ start_published_date (Optional[str]): A date string like \"2020-06-15\".\\\ end_published_date (Optional[str]): End date string\\\ \\\ \\' is too long - \\'tools.0.function.description\\'', 'type': 'invalid_request_error', 'param': None, 'code': None}}" }
Version: 0.9.39
https://github.com/run-llama/llama-hub/blob/main/llama_hub/tools/notebooks/exa.ipynb when i run the last line code: print( agent.chat( "Can you summarize everything published in the last month regarding news on" " superconductors" ) )
print( agent.chat( "Can you summarize everything published in the last month regarding news on" " superconductors" ) )
No response
Bug Description
Version
Version: 0.9.39
Steps to Reproduce
https://github.com/run-llama/llama-hub/blob/main/llama_hub/tools/notebooks/exa.ipynb when i run the last line code:
print( agent.chat( "Can you summarize everything published in the last month regarding news on" " superconductors" ) )Relevant Logs/Tracbacks
No response