age power error

[sherwinNG]

System Info

If this error occurs, it is recommended to set the logic for requesting again.

Who can help?

No response

Information

• [X] The official example notebooks/scripts
• [ ] My own modified scripts

Related Components

• [X] LLMs/Chat Models
• [ ] Embedding Models
• [ ] Prompts / Prompt Templates / Prompt Selectors
• [X] Output Parsers
• [ ] Document Loaders
• [ ] Vector Stores / Retrievers
• [ ] Memory
• [ ] Agents / Agent Executors
• [ ] Tools / Toolkits
• [X] Chains
• [ ] Callbacks/Tracing
• [ ] Async

Reproduction

希望有更好的代码

Expected behavior

• Code optimization

[dosubot[bot]]

🤖

Hello,

Thank you for reaching out. I'm sorry, but I'm unable to view the images you've attached. Could you please provide the error message in text format? This will help me understand the issue better.

As for the "age power error", I couldn't find any specific references to this error in the LangChain repository. It would be helpful if you could provide more context about when and where this error occurs.

Regarding your request for code optimization, could you please specify which part of the code you're referring to? This will help me provide a more accurate response.

For reproducing the error, you've mentioned "希望有更好的代码" which translates to "hope to have better code". Could you please provide the specific steps or code that leads to the error? This will help in identifying the issue and providing a solution.

Looking forward to your response.

Best, Dosu

Sources

• .github/ISSUE_TEMPLATE/bug-report.yml

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Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

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[sherwinNG]

• code is :

  
  from langchain.agents import initialize_agent
  from langchain.agents import AgentType
  from langchain.chat_models import ChatOpenAI
  from langchain.llms import OpenAI

First, let's load the language model we're going to use to control the agent.

chat = ChatOpenAI(temperature=0.9)

Next, let's load some tools to use. Note that the llm-math tool uses an LLM, so we need to pass that in.

llm = OpenAI(temperature=0) tools = load_tools(["serpapi", "llm-math"], llm=llm)

Finally, let's initialize an agent with the tools, the language model, and the type of agent we want to use.

agent = initialize_agent(tools, chat, agent=AgentType.CHAT_ZERO_SHOT_REACT_DESCRIPTION, verbose=True)

Now let's test it out!

agent.run("Who is Olivia Wilde's boyfriend? What is his current age raised to the 0.23 power?")

- error is :

Entering new AgentExecutor chain... Question: Who is Olivia Wilde's boyfriend? Thought: I don't have this information, so I should use a search engine to find Olivia Wilde's boyfriend. Action:

{
"action": "Search",
"action_input": "Olivia Wilde boyfriend"
}

Observation: Looks like Olivia Wilde and Jason Sudeikis are starting 2023 on good terms. Amid their highly publicized custody battle – and the actress' ... Thought:I found the information about Olivia Wilde's boyfriend. Now I need to calculate his current age raised to the 0.23 power. Action:

{
"action": "Calculator",
"action_input": "age ^ 0.23"
}

---

KeyError Traceback (most recent call last) File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/numexpr/necompiler.py:753, in getArguments(names, local_dict, global_dict, _frame_depth) 752 try: --> 753 a = local_dict[name] 754 except KeyError:

KeyError: 'age'

During handling of the above exception, another exception occurred:

KeyError Traceback (most recent call last) File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/chains/llm_math/base.py:80, in LLMMathChain._evaluate_expression(self, expression) 78 local_dict = {"pi": math.pi, "e": math.e} 79 output = str( ---> 80 numexpr.evaluate( 81 expression.strip(), 82 global_dict={}, # restrict access to globals 83 local_dict=local_dict, # add common mathematical functions 84 ) 85 ) 86 except Exception as e:

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/numexpr/necompiler.py:943, in evaluate(ex, local_dict, global_dict, out, order, casting, _frame_depth, **kwargs) 942 else: --> 943 raise e

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/numexpr/necompiler.py:853, in validate(ex, local_dict, global_dict, out, order, casting, _frame_depth, **kwargs) 852 names, ex_uses_vml = _names_cache[expr_key] --> 853 arguments = getArguments(names, local_dict, global_dict, _frame_depth=_frame_depth) 855 # Create a signature

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/numexpr/necompiler.py:755, in getArguments(names, local_dict, global_dict, _frame_depth) 754 except KeyError: --> 755 a = global_dict[name] 756 arguments.append(numpy.asarray(a))

KeyError: 'age'

During handling of the above exception, another exception occurred:

ValueError Traceback (most recent call last) Cell In[53], line 18 15 agent = initialize_agent(tools, chat, agent=AgentType.CHAT_ZERO_SHOT_REACT_DESCRIPTION, verbose=True) 17 # Now let's test it out! ---> 18 agent.run("Who is Olivia Wilde's boyfriend? What is his current age raised to the 0.23 power?")

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/chains/base.py:451, in Chain.run(self, callbacks, tags, metadata, *args, **kwargs) 449 if len(args) != 1: 450 raise ValueError("run supports only one positional argument.") --> 451 return self(args[0], callbacks=callbacks, tags=tags, metadata=metadata)[ 452 _output_key 453 ] 455 if kwargs and not args: 456 return self(kwargs, callbacks=callbacks, tags=tags, metadata=metadata)[ 457 _output_key 458 ]

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/chains/base.py:258, in Chain.call(self, inputs, return_only_outputs, callbacks, tags, metadata, include_run_info) 256 except (KeyboardInterrupt, Exception) as e: 257 run_manager.on_chain_error(e) --> 258 raise e 259 run_manager.on_chain_end(outputs) 260 final_outputs: Dict[str, Any] = self.prep_outputs( 261 inputs, outputs, return_only_outputs 262 )

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/chains/base.py:252, in Chain.call(self, inputs, return_only_outputs, callbacks, tags, metadata, include_run_info) 246 run_manager = callback_manager.on_chain_start( 247 dumpd(self), 248 inputs, 249 ) 250 try: 251 outputs = ( --> 252 self._call(inputs, run_manager=run_manager) 253 if new_arg_supported 254 else self._call(inputs) 255 ) 256 except (KeyboardInterrupt, Exception) as e: 257 run_manager.on_chain_error(e)

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/agents/agent.py:1035, in AgentExecutor._call(self, inputs, run_manager) 1033 # We now enter the agent loop (until it returns something). 1034 while self._should_continue(iterations, time_elapsed): -> 1035 next_step_output = self._take_next_step( 1036 name_to_tool_map, 1037 color_mapping, 1038 inputs, 1039 intermediate_steps, 1040 run_manager=run_manager, 1041 ) 1042 if isinstance(next_step_output, AgentFinish): 1043 return self._return( 1044 next_step_output, intermediate_steps, run_manager=run_manager 1045 )

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/agents/agent.py:890, in AgentExecutor._take_next_step(self, name_to_tool_map, color_mapping, inputs, intermediate_steps, run_manager) 888 tool_run_kwargs["llm_prefix"] = "" 889 # We then call the tool on the tool input to get an observation --> 890 observation = tool.run( 891 agent_action.tool_input, 892 verbose=self.verbose, 893 color=color, 894 callbacks=run_manager.get_child() if run_manager else None, 895 **tool_run_kwargs, 896 ) 897 else: 898 tool_run_kwargs = self.agent.tool_run_logging_kwargs()

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/tools/base.py:349, in BaseTool.run(self, tool_input, verbose, start_color, color, callbacks, tags, metadata, kwargs) 347 except (Exception, KeyboardInterrupt) as e: 348 run_manager.on_tool_error(e) --> 349 raise e 350 else: 351 run_manager.on_tool_end( 352 str(observation), color=color, name=self.name, kwargs 353 )

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/tools/base.py:321, in BaseTool.run(self, tool_input, verbose, start_color, color, callbacks, tags, metadata, kwargs) 318 try: 319 tool_args, tool_kwargs = self._to_args_and_kwargs(parsed_input) 320 observation = ( --> 321 self._run(*tool_args, run_manager=run_manager, *tool_kwargs) 322 if new_arg_supported 323 else self._run(tool_args, tool_kwargs) 324 ) 325 except ToolException as e: 326 if not self.handle_tool_error:

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/tools/base.py:491, in Tool._run(self, run_manager, *args, kwargs) 488 """Use the tool.""" 489 new_argument_supported = signature(self.func).parameters.get("callbacks") 490 return ( --> 491 self.func( 492 *args, 493 callbacks=run_manager.get_child() if run_manager else None, 494 *kwargs, 495 ) 496 if new_argument_supported 497 else self.func(args, kwargs) 498 )

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/chains/base.py:451, in Chain.run(self, callbacks, tags, metadata, *args, **kwargs) 449 if len(args) != 1: 450 raise ValueError("run supports only one positional argument.") --> 451 return self(args[0], callbacks=callbacks, tags=tags, metadata=metadata)[ 452 _output_key 453 ] 455 if kwargs and not args: 456 return self(kwargs, callbacks=callbacks, tags=tags, metadata=metadata)[ 457 _output_key 458 ]

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/chains/base.py:258, in Chain.call(self, inputs, return_only_outputs, callbacks, tags, metadata, include_run_info) 256 except (KeyboardInterrupt, Exception) as e: 257 run_manager.on_chain_error(e) --> 258 raise e 259 run_manager.on_chain_end(outputs) 260 final_outputs: Dict[str, Any] = self.prep_outputs( 261 inputs, outputs, return_only_outputs 262 )

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/chains/base.py:252, in Chain.call(self, inputs, return_only_outputs, callbacks, tags, metadata, include_run_info) 246 run_manager = callback_manager.on_chain_start( 247 dumpd(self), 248 inputs, 249 ) 250 try: 251 outputs = ( --> 252 self._call(inputs, run_manager=run_manager) 253 if new_arg_supported 254 else self._call(inputs) 255 ) 256 except (KeyboardInterrupt, Exception) as e: 257 run_manager.on_chain_error(e)

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/chains/llm_math/base.py:149, in LLMMathChain._call(self, inputs, run_manager) 143 _run_manager.on_text(inputs[self.input_key]) 144 llm_output = self.llm_chain.predict( 145 question=inputs[self.input_key], 146 stop=["```output"], 147 callbacks=_run_manager.get_child(), 148 ) --> 149 return self._process_llm_result(llm_output, _run_manager)

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/chains/llm_math/base.py:103, in LLMMathChain._process_llm_result(self, llm_output, run_manager) 101 if text_match: 102 expression = text_match.group(1) --> 103 output = self._evaluate_expression(expression) 104 run_manager.on_text("\nAnswer: ", verbose=self.verbose) 105 run_manager.on_text(output, color="yellow", verbose=self.verbose)

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/chains/llm_math/base.py:87, in LLMMathChain._evaluate_expression(self, expression) 79 output = str( 80 numexpr.evaluate( 81 expression.strip(), (...) 84 ) 85 ) 86 except Exception as e: ---> 87 raise ValueError( 88 f'LLMMathChain._evaluate("{expression}") raised error: {e}.' 89 " Please try again with a valid numerical expression" 90 ) 92 # Remove any leading and trailing brackets from the output 93 return re.sub(r"^[|]$", "", output)

ValueError: LLMMathChain._evaluate(" age**0.23 ") raised error: 'age'. Please try again with a valid numerical expression Selection deleted```

[dosubot[bot]]

Hi, @sherwinNG,

I'm helping the LangChain team manage their backlog and am marking this issue as stale. From what I understand, you are encountering an "age power error" and are seeking help to set the logic for requesting again when this error occurs, along with the need for code optimization. I responded, asking for more details about the error message and the specific code that leads to the error. You provided the code snippet and the error message, which indicates a KeyError related to the 'age' variable. However, there has been no further activity on this issue.

Could you please confirm if this issue is still relevant to the latest version of the LangChain repository? If it is, please let the LangChain team know by commenting on the issue. Otherwise, feel free to close the issue yourself, or it will be automatically closed in 7 days.

Thank you!