ReAct pattern in Prompt Engineering / GenAI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to initialize the ReAct agent with the correct reasoning step.

Prompt Engineering / GenAI

agent = ReActAgent(reasoning_steps=[1])

Drag options to blanks, or click blank then click option'

A1

B3

C0

D5

Attempts:

3 left

💡 Hint

Common Mistakes

Setting reasoning_steps to 0 disables reasoning.

Using too many steps initially can complicate the agent's behavior.

The ReAct pattern typically starts with one reasoning step to allow the agent to think and act iteratively.

2fill in blank

medium

Complete the code to add an observation after the agent takes an action.

Prompt Engineering / GenAI

agent.observe(action_output=[1])

Drag options to blanks, or click blank then click option'

Aobservation

Baction_result

Caction_output

Dresponse

Attempts:

3 left

💡 Hint

Common Mistakes

Using a variable name that is not defined or unrelated.

Confusing 'observation' with the variable holding the action output.

The agent observes the result of its action, which is stored in 'action_result'.

3fill in blank

hard

Fix the error in the code to correctly perform the agent's think-act cycle.

Prompt Engineering / GenAI

thought = agent.think(input_text)
action = agent.act([1])

Drag options to blanks, or click blank then click option'

Aagent

Binput_text

Caction

Dthought

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the original input instead of the thought.

Passing the action variable before it is defined.

The agent acts based on its thought, so the argument to act() should be the 'thought' variable.

4fill in blank

hard

Fill both blanks to create a loop that runs the ReAct agent for 3 cycles.

Prompt Engineering / GenAI

for _ in range([1]):
    thought = agent.think(input_text)
    action = agent.act(thought)
    agent.observe([2])

Drag options to blanks, or click blank then click option'

A3

Baction

Cthought

Dinput_text

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'thought' instead of 'action' for observation.

Setting the loop count incorrectly.

The loop runs 3 times, and the agent observes the result of its action each cycle.

5fill in blank

hard

Fill all three blanks to define a function that runs the ReAct agent for a given number of steps and returns the final thought.

Prompt Engineering / GenAI

def run_react_agent(agent, input_text, steps):
    for _ in range([1]):
        thought = agent.think(input_text)
        action = agent.act([2])
        agent.observe([3])
    return thought

Drag options to blanks, or click blank then click option'

Asteps

Bthought

Caction

Dinput_text

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'input_text' instead of 'thought' for the act method.

Observing 'thought' instead of 'action'.

The loop runs for 'steps' times, the agent acts on 'thought', observes 'action', and finally returns the last thought.

Practice

1. What is the main purpose of the ReAct pattern in AI?

easy

A. To speed up AI training by skipping reasoning

B. To combine thinking and acting steps for better problem solving

C. To store large datasets efficiently

D. To replace human decision making completely

Solution

1. Step 1: Understand the ReAct pattern concept

   The ReAct pattern mixes reasoning (thinking) and actions (doing) to solve problems step-by-step.

2. Step 2: Identify the main goal

   This approach helps AI be more transparent and effective by breaking down tasks into Thought, Action, Observation, and Final Answer.

3. Final Answer:

   To combine thinking and acting steps for better problem solving -> Option B

4. Quick Check:

   ReAct = Reason + Act [OK]

Hint: Remember ReAct means think then do, step-by-step [OK]

Common Mistakes:

• Thinking AI skips actions
• ReAct stores data only
• ReAct replaces humans fully

2. Which of the following shows the correct sequence in the ReAct pattern?

easy

A. Thought -> Action -> Observation -> Final Answer

B. Action -> Thought -> Final Answer -> Observation

C. Observation -> Final Answer -> Thought -> Action

D. Final Answer -> Thought -> Action -> Observation

Solution

1. Step 1: Recall the ReAct step order

   The ReAct pattern follows a clear order: first the AI thinks (Thought), then acts (Action), then sees results (Observation), and finally gives the answer.

2. Step 2: Match the correct sequence

   Thought -> Action -> Observation -> Final Answer correctly lists this order as Thought -> Action -> Observation -> Final Answer.

3. Final Answer:

   Thought -> Action -> Observation -> Final Answer -> Option A

4. Quick Check:

   Order = T -> A -> O -> FA [OK]

Hint: Think first, then act, observe, answer [OK]

Common Mistakes:

• Mixing up Observation and Action order
• Putting Final Answer before Observation
• Skipping Thought step

3. Given this simplified ReAct code snippet:

thought = 'Check weather'
action = 'Query weather API'
observation = 'It is sunny'
final_answer = f"Weather is {observation}"
print(final_answer)

What will be the printed output?

medium

A. Check weather

B. It is sunny

C. Query weather API

D. Weather is It is sunny

Solution

1. Step 1: Understand variable assignments

   The variable observation holds the string 'It is sunny'. The final_answer uses this to create 'Weather is It is sunny'.

2. Step 2: Evaluate the print statement

   The print outputs the final_answer string, which is 'Weather is It is sunny' because the f-string inserts the full observation string.

3. Final Answer:

   Weather is It is sunny -> Option D

4. Quick Check:

   Output includes 'Weather is' + observation [OK]

Hint: Look at final_answer string formatting carefully [OK]

Common Mistakes:

• Ignoring f-string variable insertion
• Printing wrong variable
• Confusing observation with action

4. Identify the error in this ReAct step code:

thought = 'Calculate sum'
action = 'Add 2 and 3'
observation = 2 + 3
final_answer = 'Sum is ' + observation
print(final_answer)

medium

A. Cannot concatenate string and integer directly

B. Missing action execution step

C. Observation should be a string, not a number

D. Final answer should be a number, not string

Solution

1. Step 1: Analyze the final_answer concatenation

   The code tries to add a string 'Sum is ' and an integer observation (5) directly, which causes a TypeError in Python.

2. Step 2: Identify the fix

   To fix, convert observation to string using str(observation) before concatenation.

3. Final Answer:

   Cannot concatenate string and integer directly -> Option A

4. Quick Check:

   String + int causes error [OK]

Hint: Convert numbers to strings before adding to text [OK]

Common Mistakes:

• Ignoring type mismatch in concatenation
• Thinking observation must be string always
• Confusing action with observation

5. You want to build a ReAct-based AI assistant that solves math problems step-by-step. Which approach best applies the ReAct pattern?

hard

A. AI randomly guesses answers and checks correctness later

B. AI immediately gives the answer without intermediate steps

C. AI thinks about the problem, performs a calculation action, observes the result, then states the final answer

D. AI stores all previous answers without reasoning

Solution

1. Step 1: Understand ReAct for stepwise problem solving

   The ReAct pattern requires the AI to think (reason), act (calculate), observe (check result), and then answer.

2. Step 2: Match the approach to ReAct steps

   AI thinks about the problem, performs a calculation action, observes the result, then states the final answer describes this exact process, making the AI transparent and effective in solving math problems step-by-step.

3. Final Answer:

   AI thinks about the problem, performs a calculation action, observes the result, then states the final answer -> Option C

4. Quick Check:

   ReAct = Thought + Action + Observation + Answer [OK]

Hint: Follow Thought -> Action -> Observation -> Answer for stepwise AI [OK]

Common Mistakes:

• Skipping reasoning steps
• Guessing without observation
• Ignoring stepwise transparency