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To debug the ReAct agent, you can set the
verbose
parameter to
True
when creating the agent. This will allow you to see what's going on during the agent's operation. Here's an example of how to do this:
from llama_index.core.agent import ReActAgent
from llama_index.llms.openai import OpenAI
llm = OpenAI(model="gpt-3.5-turbo-0613")
agent = ReActAgent.from_tools([multiply_tool, add_tool], llm=llm, verbose=True)
In this example,
multiply_tool
and
add_tool
are the tools that the agent will use. Replace these with the tools you're using in your project.
If the agent is not creating the correct action, it could be due to the reasoning loop entering an incorrect state. The ReAct agent combines chain-of-thought reasoning with action planning, and sometimes it can enter the incorrect reasoning loop to answer the question. You can run some example queries to see if this is the case.
If you're still having trouble, you might want to check the prompts used by the agent. You can do this with the
get_prompts
method:
prompt_dict = agent.get_prompts()
for k, v in prompt_dict.items():
print(f"Prompt: {k}\n\nValue: {v.template}")
This will print out all the prompts used by the agent, which might help you identify any issues.