Complete the code to start the agent's reasoning with a clear thought.
agent_thought = "I need to analyze the problem step by step: [1]"
The agent should begin by gathering information to reason effectively.
Complete the code to add a reasoning step that evaluates options.
agent_thought += " Next, I will [1] to decide the best action."
Evaluating all possible actions carefully is key to good chain-of-thought reasoning.
Fix the error in the agent's reasoning update to correctly append the next thought.
agent_thought = agent_thought [1] " Finally, I will execute the chosen action."
Using '+' concatenates strings properly to build the chain of thought.
Fill both blanks to create a dictionary that maps each step to its description.
reasoning_steps = {1: [1], 2: [2]The first step is to gather information, the second is to evaluate options.
Fill all three blanks to complete the agent's chain-of-thought function.
def chain_of_thought(agent_input): thoughts = [] thoughts.append([1]) thoughts.append([2]) thoughts.append([3]) return " -> ".join(thoughts)
The agent first gathers information, then evaluates options, and finally executes the action.