Customer support agent architecture in Agentic AI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to initialize the customer support agent with a knowledge base.

Agentic AI

agent = CustomerSupportAgent(knowledge_base=[1])

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AFAQDatabase()

BUserProfile()

CSessionManager()

DChatHistory()

Attempts:

3 left

💡 Hint

Common Mistakes

Using UserProfile instead of FAQDatabase as knowledge base.

Confusing ChatHistory with knowledge base.

The knowledge base for the agent should be the FAQDatabase, which contains common questions and answers.

2fill in blank

medium

Complete the code to preprocess the user's message before passing it to the agent.

Agentic AI

processed_message = preprocess([1])

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Auser_message

Bknowledge_base

Cagent_response

Dagent_state

Attempts:

3 left

💡 Hint

Common Mistakes

Preprocessing the agent's response instead of the user's message.

Passing the knowledge base to preprocess function.

The user's message needs to be preprocessed before the agent can understand it.

3fill in blank

hard

Fix the error in the code that generates the agent's reply.

Agentic AI

reply = agent.generate_reply([1])

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Aknowledge_base

Braw_input

Cagent_state

Dprocessed_message

Attempts:

3 left

💡 Hint

Common Mistakes

Passing raw_input instead of processed_message.

Using knowledge_base or agent_state as input to generate_reply.

The agent should generate a reply based on the processed message, not the raw input or other variables.

4fill in blank

hard

Fill both blanks to update the agent's state and log the conversation.

Agentic AI

agent.update_state([1])
logger.log_conversation([2])

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Areply

Buser_message

Cprocessed_message

Dagent_state

Attempts:

3 left

💡 Hint

Common Mistakes

Logging the reply instead of the user's message.

Updating state with the user's message instead of the reply.

The agent's state should be updated with the reply, and the conversation logger should log the user's original message.

5fill in blank

hard

Fill all three blanks to define the main loop of the customer support agent.

Agentic AI

while True:
    [1] = listen_to_user()
    [2] = preprocess([1])
    [3] = agent.generate_reply([2])
    send_to_user([3])

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

Auser_input

Bprocessed_input

Creply

Dagent_state

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing variable names or skipping preprocessing.

Using agent_state as a variable in the loop incorrectly.

The loop listens to the user, preprocesses the input, generates a reply, and sends it back.