it fails to output an Action string)mrkl = initialize_agent(    tools,    ChatOpenAI(temperature=0),    agent=AgentType.CHAT_ZERO_SHOT_REACT_DESCRIPTION,    verbose=True,)mrkl.run("Who is Leo DiCaprio's girlfriend? No need to add Action")            > Entering new AgentExecutor chain...    ---------------------------------------------------------------------------    IndexError                                Traceback (most recent call last)    File ~/workplace/langchain/langchain/agents/chat/output_parser.py:21, in ChatOutputParser.parse(self, text)         20 try:    ---> 21     action = text.split("```")[1]         22     response = json.loads(action.strip())    IndexError: list index out of range        During handling of the above exception, another exception occurred:    OutputParserException                     Traceback (most recent call last)    Cell In[4], line 1    ----> 1 mrkl.run("Who is Leo DiCaprio's girlfriend? No need to add Action")    File ~/workplace/langchain/langchain/chains/base.py:236, in Chain.run(self, callbacks, *args, **kwargs)        234     if len(args) != 1:        235         raise ValueError("`run` supports only one positional argument.")    --> 236     return self(args[0], callbacks=callbacks)[self.output_keys[0]]        238 if kwargs and not args:        239     return self(kwargs, callbacks=callbacks)[self.output_keys[0]]    File ~/workplace/langchain/langchain/chains/base.py:140, in Chain.__call__(self, inputs, return_only_outputs, callbacks)        138 except (KeyboardInterrupt, Exception) as e:        139     run_manager.on_chain_error(e)    --> 140     raise e        141 run_manager.on_chain_end(outputs)        142 return self.prep_outputs(inputs, outputs, return_only_outputs)    File ~/workplace/langchain/langchain/chains/base.py:134, in Chain.__call__(self, inputs, return_only_outputs, callbacks)        128 run_manager = callback_manager.on_chain_start(        129     {"name": self.__class__.__name__},        130
Occasionally the LLM cannot determine what step to take because its outputs are not correctly formatted to be handled by the output parser. In this case, by default the agent errors. But you can easily control this functionality with handleparsingerrors! Let's explore how.
Occasionally the LLM cannot determine what step to take because its outputs are not correctly formatted to be handled by the output parser. In this case, by default the agent errors. But you can easily control this functionality with handleparsingerrors! Let's explore how. ->: it fails to output an Action string)mrkl = initialize_agent(    tools,    ChatOpenAI(temperature=0),    agent=AgentType.CHAT_ZERO_SHOT_REACT_DESCRIPTION,    verbose=True,)mrkl.run("Who is Leo DiCaprio's girlfriend? No need to add Action")            > Entering new AgentExecutor chain...    ---------------------------------------------------------------------------    IndexError                                Traceback (most recent call last)    File ~/workplace/langchain/langchain/agents/chat/output_parser.py:21, in ChatOutputParser.parse(self, text)         20 try:    ---> 21     action = text.split("```")[1]         22     response = json.loads(action.strip())    IndexError: list index out of range        During handling of the above exception, another exception occurred:    OutputParserException                     Traceback (most recent call last)    Cell In[4], line 1    ----> 1 mrkl.run("Who is Leo DiCaprio's girlfriend? No need to add Action")    File ~/workplace/langchain/langchain/chains/base.py:236, in Chain.run(self, callbacks, *args, **kwargs)        234     if len(args) != 1:        235         raise ValueError("`run` supports only one positional argument.")    --> 236     return self(args[0], callbacks=callbacks)[self.output_keys[0]]        238 if kwargs and not args:        239     return self(kwargs, callbacks=callbacks)[self.output_keys[0]]    File ~/workplace/langchain/langchain/chains/base.py:140, in Chain.__call__(self, inputs, return_only_outputs, callbacks)        138 except (KeyboardInterrupt, Exception) as e:        139     run_manager.on_chain_error(e)    --> 140     raise e        141 run_manager.on_chain_end(outputs)        142 return self.prep_outputs(inputs, outputs, return_only_outputs)    File ~/workplace/langchain/langchain/chains/base.py:134, in Chain.__call__(self, inputs, return_only_outputs, callbacks)        128 run_manager = callback_manager.on_chain_start(        129     {"name": self.__class__.__name__},        130