Open abhinabsarkar opened 4 months ago
Garett601
commented
4 months ago Exactly the same issue. Worked last week, tried to test it this week and consistent 500 internal server error.
I have tried our chat completions agent and our completions agent in a standalone manner, they both work. It is only once we incorporate SQL agent and string it all together that we get the error.
mickey-ventura
commented
4 months ago Exactly the same issue. Worked last week, tried to test it this week and consistent 500 internal server error.
I have tried our chat completions agent and our completions agent in a standalone manner, they both work. It is only once we incorporate SQL agent and string it all together that we get the error.
Same here.
Garett601
commented
4 months ago https://github.com/langchain-ai/langchain/discussions/24488#discussion-6962911
I am having the exact same problem. I have tested my chat LLM and my DB LLM individually and they work. Once I put it together in an agent chain, we run into the error
openai.InternalServerError: Error code: 500 - {'statusCode': 500, 'message': 'Internal server error', 'activityId': 'xxx-xxx-xxx-xxx'}We have followed all the API documentation on how to build a SQL Agent, this was all working perfectly until Thursday last week (25/07/2024).
def init_langchain_client(
chat: AzureChatOpenAI,
memory: ConversationSummaryBufferMemory,
suffix: str,
tools: List[ToolType],
system_prefix: str,
) -> AgentExecutor:
"""
Initialise the Langchain client with necessary configurations.
Returns
-------
AgentExecutor
The agent executor configured with SQL database tools and Azure OpenAI models.
"""
prompt = PromptTemplate.from_template(system_prefix + suffix)
agent = create_react_agent(
llm=chat,
tools=tools,
prompt=prompt,
)
agent_chain = AgentExecutor.from_agent_and_tools(
agent=agent,
tools=tools,
verbose=True,
memory=memory,
handle_parsing_errors=True,
return_intermediate_steps=True,
)
return agent_chainlangchain_agent_chain = init_langchain_client(
chat=chat,
memory=memory,
suffix=SUFFIX_REACT,
tools=tools,
system_prefix=system_prefix,
)langchain_agent_chain.invoke({"input":"Who are you?"})---------------------------------------------------------------------------
InternalServerError Traceback (most recent call last)
Cell In[4], line 1
----> 1 langchain_agent_chain.invoke({"input":"Who are you?"})
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/langchain/chains/base.py:163, in Chain.invoke(self, input, config, **kwargs)
161 except BaseException as e:
162 run_manager.on_chain_error(e)
--> 163 raise e
164 run_manager.on_chain_end(outputs)
166 if include_run_info:
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/langchain/chains/base.py:153, in Chain.invoke(self, input, config, **kwargs)
150 try:
151 self._validate_inputs(inputs)
152 outputs = (
--> 153 self._call(inputs, run_manager=run_manager)
154 if new_arg_supported
155 else self._call(inputs)
156 )
158 final_outputs: Dict[str, Any] = self.prep_outputs(
159 inputs, outputs, return_only_outputs
160 )
161 except BaseException as e:
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/langchain/agents/agent.py:1432, in AgentExecutor._call(self, inputs, run_manager)
1430 # We now enter the agent loop (until it returns something).
1431 while self._should_continue(iterations, time_elapsed):
-> 1432 next_step_output = self._take_next_step(
1433 name_to_tool_map,
1434 color_mapping,
1435 inputs,
1436 intermediate_steps,
1437 run_manager=run_manager,
1438 )
1439 if isinstance(next_step_output, AgentFinish):
1440 return self._return(
1441 next_step_output, intermediate_steps, run_manager=run_manager
1442 )
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/langchain/agents/agent.py:1138, in AgentExecutor._take_next_step(self, name_to_tool_map, color_mapping, inputs, intermediate_steps, run_manager)
1129 def _take_next_step(
1130 self,
1131 name_to_tool_map: Dict[str, BaseTool],
(...)
1135 run_manager: Optional[CallbackManagerForChainRun] = None,
1136 ) -> Union[AgentFinish, List[Tuple[AgentAction, str]]]:
1137 return self._consume_next_step(
-> 1138 [
1139 a
1140 for a in self._iter_next_step(
1141 name_to_tool_map,
1142 color_mapping,
1143 inputs,
1144 intermediate_steps,
1145 run_manager,
1146 )
1147 ]
1148 )
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/langchain/agents/agent.py:1166, in AgentExecutor._iter_next_step(self, name_to_tool_map, color_mapping, inputs, intermediate_steps, run_manager)
1163 intermediate_steps = self._prepare_intermediate_steps(intermediate_steps)
1165 # Call the LLM to see what to do.
-> 1166 output = self.agent.plan(
1167 intermediate_steps,
1168 callbacks=run_manager.get_child() if run_manager else None,
1169 **inputs,
1170 )
1171 except OutputParserException as e:
1172 if isinstance(self.handle_parsing_errors, bool):
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/langchain/agents/agent.py:397, in RunnableAgent.plan(self, intermediate_steps, callbacks, **kwargs)
389 final_output: Any = None
390 if self.stream_runnable:
391 # Use streaming to make sure that the underlying LLM is invoked in a
392 # streaming
(...)
395 # Because the response from the plan is not a generator, we need to
396 # accumulate the output into final output and return that.
--> 397 for chunk in self.runnable.stream(inputs, config={"callbacks": callbacks}):
398 if final_output is None:
399 final_output = chunk
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/langchain_core/runnables/base.py:2875, in RunnableSequence.stream(self, input, config, **kwargs)
2869 def stream(
2870 self,
2871 input: Input,
2872 config: Optional[RunnableConfig] = None,
2873 **kwargs: Optional[Any],
2874 ) -> Iterator[Output]:
-> 2875 yield from self.transform(iter([input]), config, **kwargs)
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/langchain_core/runnables/base.py:2862, in RunnableSequence.transform(self, input, config, **kwargs)
2856 def transform(
2857 self,
2858 input: Iterator[Input],
2859 config: Optional[RunnableConfig] = None,
2860 **kwargs: Optional[Any],
2861 ) -> Iterator[Output]:
-> 2862 yield from self._transform_stream_with_config(
2863 input,
2864 self._transform,
2865 patch_config(config, run_name=(config or {}).get("run_name") or self.name),
2866 **kwargs,
2867 )
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/langchain_core/runnables/base.py:1881, in Runnable._transform_stream_with_config(self, input, transformer, config, run_type, **kwargs)
1879 try:
1880 while True:
-> 1881 chunk: Output = context.run(next, iterator) # type: ignore
1882 yield chunk
1883 if final_output_supported:
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/langchain_core/runnables/base.py:2826, in RunnableSequence._transform(self, input, run_manager, config)
2817 for step in steps:
2818 final_pipeline = step.transform(
2819 final_pipeline,
2820 patch_config(
(...)
2823 ),
2824 )
-> 2826 for output in final_pipeline:
2827 yield output
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/langchain_core/runnables/base.py:1282, in Runnable.transform(self, input, config, **kwargs)
1279 final: Input
1280 got_first_val = False
-> 1282 for ichunk in input:
1283 # The default implementation of transform is to buffer input and
1284 # then call stream.
1285 # It'll attempt to gather all input into a single chunk using
1286 # the `+` operator.
1287 # If the input is not addable, then we'll assume that we can
1288 # only operate on the last chunk,
1289 # and we'll iterate until we get to the last chunk.
1290 if not got_first_val:
1291 final = ichunk
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/langchain_core/runnables/base.py:4736, in RunnableBindingBase.transform(self, input, config, **kwargs)
4730 def transform(
4731 self,
4732 input: Iterator[Input],
4733 config: Optional[RunnableConfig] = None,
4734 **kwargs: Any,
4735 ) -> Iterator[Output]:
-> 4736 yield from self.bound.transform(
4737 input,
4738 self._merge_configs(config),
4739 **{**self.kwargs, **kwargs},
4740 )
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/langchain_core/runnables/base.py:1300, in Runnable.transform(self, input, config, **kwargs)
1297 final = ichunk
1299 if got_first_val:
-> 1300 yield from self.stream(final, config, **kwargs)
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/langchain_core/language_models/chat_models.py:249, in BaseChatModel.stream(self, input, config, stop, **kwargs)
242 except BaseException as e:
243 run_manager.on_llm_error(
244 e,
245 response=LLMResult(
246 generations=[[generation]] if generation else []
247 ),
248 )
--> 249 raise e
250 else:
251 run_manager.on_llm_end(LLMResult(generations=[[generation]]))
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/langchain_core/language_models/chat_models.py:229, in BaseChatModel.stream(self, input, config, stop, **kwargs)
227 generation: Optional[ChatGenerationChunk] = None
228 try:
--> 229 for chunk in self._stream(messages, stop=stop, **kwargs):
230 if chunk.message.id is None:
231 chunk.message.id = f"run-{run_manager.run_id}"
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/langchain_openai/chat_models/base.py:480, in BaseChatOpenAI._stream(self, messages, stop, run_manager, **kwargs)
477 params = {**params, **kwargs, "stream": True}
479 default_chunk_class = AIMessageChunk
--> 480 with self.client.create(messages=message_dicts, **params) as response:
481 for chunk in response:
482 if not isinstance(chunk, dict):
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/openai/_utils/_utils.py:277, in required_args.<locals>.inner.<locals>.wrapper(*args, **kwargs)
275 msg = f"Missing required argument: {quote(missing[0])}"
276 raise TypeError(msg)
--> 277 return func(*args, **kwargs)
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/openai/resources/chat/completions.py:643, in Completions.create(self, messages, model, frequency_penalty, function_call, functions, logit_bias, logprobs, max_tokens, n, parallel_tool_calls, presence_penalty, response_format, seed, service_tier, stop, stream, stream_options, temperature, tool_choice, tools, top_logprobs, top_p, user, extra_headers, extra_query, extra_body, timeout)
609 @required_args(["messages", "model"], ["messages", "model", "stream"])
610 def create(
611 self,
(...)
641 timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
642 ) -> ChatCompletion | Stream[ChatCompletionChunk]:
--> 643 return self._post(
644 "/chat/completions",
645 body=maybe_transform(
646 {
647 "messages": messages,
648 "model": model,
649 "frequency_penalty": frequency_penalty,
650 "function_call": function_call,
651 "functions": functions,
652 "logit_bias": logit_bias,
653 "logprobs": logprobs,
654 "max_tokens": max_tokens,
655 "n": n,
656 "parallel_tool_calls": parallel_tool_calls,
657 "presence_penalty": presence_penalty,
658 "response_format": response_format,
659 "seed": seed,
660 "service_tier": service_tier,
661 "stop": stop,
662 "stream": stream,
663 "stream_options": stream_options,
664 "temperature": temperature,
665 "tool_choice": tool_choice,
666 "tools": tools,
667 "top_logprobs": top_logprobs,
668 "top_p": top_p,
669 "user": user,
670 },
671 completion_create_params.CompletionCreateParams,
672 ),
673 options=make_request_options(
674 extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
675 ),
676 cast_to=ChatCompletion,
677 stream=stream or False,
678 stream_cls=Stream[ChatCompletionChunk],
679 )
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/openai/_base_client.py:1250, in SyncAPIClient.post(self, path, cast_to, body, options, files, stream, stream_cls)
1236 def post(
1237 self,
1238 path: str,
(...)
1245 stream_cls: type[_StreamT] | None = None,
1246 ) -> ResponseT | _StreamT:
1247 opts = FinalRequestOptions.construct(
1248 method="post", url=path, json_data=body, files=to_httpx_files(files), **options
1249 )
-> 1250 return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/openai/_base_client.py:931, in SyncAPIClient.request(self, cast_to, options, remaining_retries, stream, stream_cls)
922 def request(
923 self,
924 cast_to: Type[ResponseT],
(...)
929 stream_cls: type[_StreamT] | None = None,
930 ) -> ResponseT | _StreamT:
--> 931 return self._request(
932 cast_to=cast_to,
933 options=options,
934 stream=stream,
935 stream_cls=stream_cls,
936 remaining_retries=remaining_retries,
937 )
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/openai/_base_client.py:1015, in SyncAPIClient._request(self, cast_to, options, remaining_retries, stream, stream_cls)
1013 if retries > 0 and self._should_retry(err.response):
1014 err.response.close()
-> 1015 return self._retry_request(
1016 options,
1017 cast_to,
1018 retries,
1019 err.response.headers,
1020 stream=stream,
1021 stream_cls=stream_cls,
1022 )
1024 # If the response is streamed then we need to explicitly read the response
1025 # to completion before attempting to access the response text.
1026 if not err.response.is_closed:
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/openai/_base_client.py:1063, in SyncAPIClient._retry_request(self, options, cast_to, remaining_retries, response_headers, stream, stream_cls)
1059 # In a synchronous context we are blocking the entire thread. Up to the library user to run the client in a
1060 # different thread if necessary.
1061 time.sleep(timeout)
-> 1063 return self._request(
1064 options=options,
1065 cast_to=cast_to,
1066 remaining_retries=remaining,
1067 stream=stream,
1068 stream_cls=stream_cls,
1069 )
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/openai/_base_client.py:1015, in SyncAPIClient._request(self, cast_to, options, remaining_retries, stream, stream_cls)
1013 if retries > 0 and self._should_retry(err.response):
1014 err.response.close()
-> 1015 return self._retry_request(
1016 options,
1017 cast_to,
1018 retries,
1019 err.response.headers,
1020 stream=stream,
1021 stream_cls=stream_cls,
1022 )
1024 # If the response is streamed then we need to explicitly read the response
1025 # to completion before attempting to access the response text.
1026 if not err.response.is_closed:
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/openai/_base_client.py:1063, in SyncAPIClient._retry_request(self, options, cast_to, remaining_retries, response_headers, stream, stream_cls)
1059 # In a synchronous context we are blocking the entire thread. Up to the library user to run the client in a
1060 # different thread if necessary.
1061 time.sleep(timeout)
-> 1063 return self._request(
1064 options=options,
1065 cast_to=cast_to,
1066 remaining_retries=remaining,
1067 stream=stream,
1068 stream_cls=stream_cls,
1069 )
File ~/xxx/xxx/virtualenvs/xxx/lib/python3.12/site-packages/openai/_base_client.py:1030, in SyncAPIClient._request(self, cast_to, options, remaining_retries, stream, stream_cls)
1027 err.response.read()
1029 log.debug("Re-raising status error")
-> 1030 raise self._make_status_error_from_response(err.response) from None
1032 return self._process_response(
1033 cast_to=cast_to,
1034 options=options,
(...)
1037 stream_cls=stream_cls,
1038 )
openai.InternalServerError: Error code: 500 - {'statusCode': 500, 'message': 'Internal server error', 'activityId': 'xxx-xxx-xxx-xxx'}
abhinabsarkar
commented
4 months ago Hello, is there any update on this issue that can be shared plz?
hk102
commented
3 months ago I don't see the 'streaming' parameter in the create_sql_agent() method. Please try removing it and check again.
Reference: libs/community/langchain_community/agent_toolkits/sql/base.py.
Also, please re-check connectivity by running the following:
This will help verify the connection and query execution.
dosubot[bot]
commented
4 days ago Hi, @abhinabsarkar. I'm Dosu, and I'm helping the LangChain team manage their backlog. I'm marking this issue as stale.
Issue Summary:
Next Steps:
Thank you for your understanding and contribution!
Checked other resources
Example Code
I am trying to use Langchain to query Azure SQL using Azure OpenAI. The code is based on the samples provided in GitHub - Langchain to query Azure SQL using Azure OpenAI. I have already tested connectivity with Azure SQL using Langchain & it works. I also tested connectivity with Azure OpenAI using Langchain & it works as well. I am using the API version as 2023-08-01-preview as per the comment that "Azure OpenAI on your own data is only supported by the 2023-08-01-preview API version." Referred this link.
After I create the SQL agent & execute the invoke method, it fails returning internal server error & return code as 500.
Error Message and Stack Trace (if applicable)
Entering new SQL Agent Executor chain... Traceback (most recent call last): File "test.py", line 62, in agent_executor.invoke(final_prompt.format( File "/home/user/.local/lib/python3.8/site-packages/langchain/chains/base.py", line 166, in invoke raise e File "/home/user/.local/lib/python3.8/site-packages/langchain/chains/base.py", line 156, in invoke self._call(inputs, run_manager=run_manager) File "/home/user/.local/lib/python3.8/site-packages/langchain/agents/agent.py", line 1636, in _call next_step_output = self._take_next_step( File "/home/user/.local/lib/python3.8/site-packages/langchain/agents/agent.py", line 1342, in _take_next_step [ File "/home/user/.local/lib/python3.8/site-packages/langchain/agents/agent.py", line 1342, in [ File "/home/user/.local/lib/python3.8/site-packages/langchain/agents/agent.py", line 1370, in _iter_next_step output = self.agent.plan( File "/home/user/.local/lib/python3.8/site-packages/langchain/agents/agent.py", line 463, in plan for chunk in self.runnable.stream(inputs, config={"callbacks": callbacks}): File "/home/user/.local/lib/python3.8/site-packages/langchain_core/runnables/base.py", line 3251, in stream yield from self.transform(iter([input]), config, kwargs) File "/home/user/.local/lib/python3.8/site-packages/langchain_core/runnables/base.py", line 3238, in transform yield from self._transform_stream_with_config( File "/home/user/.local/lib/python3.8/site-packages/langchain_core/runnables/base.py", line 2052, in _transform_stream_with_config chunk: Output = context.run(next, iterator) # type: ignore File "/home/user/.local/lib/python3.8/site-packages/langchain_core/runnables/base.py", line 3200, in _transform for output in final_pipeline: File "/home/user/.local/lib/python3.8/site-packages/langchain_core/runnables/base.py", line 1270, in transform for ichunk in input: File "/home/user/.local/lib/python3.8/site-packages/langchain_core/runnables/base.py", line 5262, in transform yield from self.bound.transform( File "/home/user/.local/lib/python3.8/site-packages/langchain_core/runnables/base.py", line 1288, in transform yield from self.stream(final, config, kwargs) File "/home/user/.local/lib/python3.8/site-packages/langchain_core/language_models/chat_models.py", line 360, in stream raise e File "/home/user/.local/lib/python3.8/site-packages/langchain_core/language_models/chat_models.py", line 340, in stream for chunk in self._stream(messages, stop=stop, kwargs): File "/home/user/.local/lib/python3.8/site-packages/langchain_openai/chat_models/base.py", line 489, in _stream with self.client.create(payload) as response: File "/home/user/.local/lib/python3.8/site-packages/openai/_utils/_utils.py", line 277, in wrapper return func(*args, **kwargs) File "/home/user/.local/lib/python3.8/site-packages/openai/resources/chat/completions.py", line 643, in create return self._post( File "/home/user/.local/lib/python3.8/site-packages/openai/_base_client.py", line 1266, in post return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)) File "/home/user/.local/lib/python3.8/site-packages/openai/_base_client.py", line 942, in request return self._request( File "/home/user/.local/lib/python3.8/site-packages/openai/_base_client.py", line 1031, in _request return self._retry_request( File "/home/user/.local/lib/python3.8/site-packages/openai/_base_client.py", line 1079, in _retry_request return self._request( File "/home/user/.local/lib/python3.8/site-packages/openai/_base_client.py", line 1031, in _request return self._retry_request( File "/home/user/.local/lib/python3.8/site-packages/openai/_base_client.py", line 1079, in _retry_request return self._request( File "/home/user/.local/lib/python3.8/site-packages/openai/_base_client.py", line 1046, in _request raise self._make_status_error_from_response(err.response) from None openai.InternalServerError: Error code: 500 - {'statusCode': 500, 'message': 'Internal server error', 'activityId': 'xxx-yyy-zzz'}
Description
System Info
Langchain version
langchain==0.2.10 langchain-community==0.2.9 langchain-core==0.2.22 langchain-openai==0.1.16 langchain-text-splitters==0.2.2
Platform
Windows 11
Python version
Python 3.8.10