ValueError: Could not parse LLM output:
# ValueError: Could not parse LLM output:
'Could not parse LLM output' from a LangChain agent almost always means the model isn't following the ReAct format: models like google/flan-t5-xl or Bloom don't reliably produce the Thought / Action / Action Input structure the parser expects. Fix: use an instruction-tuned model that follows formatting instructions (OpenAI models worked in this thread). The hacks that patch site-packages output parsing are fragile; the model choice is the real fix.
## Context from the issue
gh:langchain-ai/langchain#1358: Issue langchain-ai/langchain#1358 (closed, 82 comments): `agent_chain = initialize_agent( tools=tools, llm= HuggingFaceHub(repo_id="google/flan-t5-xl"), agent="conversational-react-description", memory=memory, verbose=False)
agent_chain.run("Hi")`
**throws error. This happens with Bloom as well. Agent only with OpenAI is only working well.**
`_(self, inputs, return_only_outputs)
140 except (KeyboardInterrupt, Exception) as e:
141 self.callback_manager.on_chain_error(e, verbose=self.verbose)
--> 142 raise e
143 self.callback_manager.on_chain_end(outputs, verbose=self.verbose)
...
---> 83 raise...Find related guidance
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