Agent API design patterns in Agentic AI - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main purpose of an Agent API in AI systems?

An Agent API allows different AI components or services to communicate and work together by defining clear interfaces and protocols.

intermediate

Explain the 'Command Pattern' in Agent API design.

The Command Pattern encapsulates a request as an object, allowing parameterization and queuing of requests, which helps agents execute commands flexibly and asynchronously.

intermediate

What role does the 'Observer Pattern' play in Agent API design?

The Observer Pattern lets agents subscribe to events or state changes in other agents, enabling reactive and event-driven communication.

advanced

Why is 'Idempotency' important in Agent API design?

Idempotency ensures that repeating the same API call multiple times has the same effect as calling it once, which prevents errors and inconsistencies in agent interactions.

beginner

Describe the 'Request-Response' pattern in Agent APIs.

The Request-Response pattern involves an agent sending a request and waiting for a response, which is useful for synchronous operations and clear communication flow.

Which design pattern allows agents to react to changes in other agents automatically?

A Command Pattern

B Observer Pattern

C Singleton Pattern

D Factory Pattern

The Observer Pattern enables agents to subscribe and react to events or state changes in other agents.

What does idempotency in an Agent API ensure?

A Multiple calls have the same effect as one call

B Calls always fail if repeated

C Calls are processed in random order

D Calls require authentication every time

Idempotency means repeating the same call does not change the result beyond the initial application.

In the Command Pattern, what is encapsulated as an object?

A A user interface

B An agent's state

C A data model

D A request or action

The Command Pattern wraps a request or action into an object to allow flexible execution.

Which pattern is best for synchronous communication in Agent APIs?

A Request-Response

B Observer

C Command

D Decorator

Request-Response pattern involves sending a request and waiting for a reply, suitable for synchronous calls.

Why are clear interfaces important in Agent API design?

A They hide all functionality

B They make the API slower

C They allow different agents to communicate reliably

D They prevent any communication

Clear interfaces ensure agents understand how to interact, enabling reliable communication.

Describe three common design patterns used in Agent API design and explain their roles.

Think about how agents send commands, listen for events, and communicate synchronously.

Explain why idempotency is critical in designing reliable Agent APIs.

Consider what happens if a network call is repeated due to failure.

Practice

1. What is the main purpose of using Agent API design patterns in AI systems?

easy

A. To organize how AI agents communicate and work together

B. To speed up the training of machine learning models

C. To store large datasets efficiently

D. To improve the hardware performance of AI servers

Solution

1. Step 1: Understand the role of Agent API design patterns

   These patterns help define clear communication and interaction rules between AI agents.

2. Step 2: Compare with other options

   Options A, C, and D relate to training speed, data storage, and hardware, which are not the focus of Agent API design patterns.

3. Final Answer:

   To organize how AI agents communicate and work together -> Option A

4. Quick Check:

   Agent API design patterns = organize communication [OK]

Hint: Agent API patterns focus on agent communication, not hardware or data [OK]

Common Mistakes:

• Confusing design patterns with hardware optimization
• Thinking patterns speed up model training directly
• Mixing data storage with agent communication

2. Which of the following is the correct way to define a simple message passing function in an Agent API?

easy

A. def send_message(agent, message): return message + agent

B. def send_message(agent, message): agent.send(message)

C. def send_message(agent, message): return agent.receive(message)

D. def send_message(agent, message): print(agent + message)

Solution

1. Step 1: Analyze the function purpose

   The function should send a message to an agent and get a response by calling the agent's receive method.

2. Step 2: Check each option

   def send_message(agent, message): return agent.receive(message) correctly calls agent.receive(message). def send_message(agent, message): agent.send(message) calls agent.send which is not standard. Options A and C incorrectly try to add or print agent and message.

3. Final Answer:

   def send_message(agent, message): return agent.receive(message) -> Option C

4. Quick Check:

   Message passing calls agent.receive(message) [OK]

Hint: Message passing calls agent.receive(message) to send data [OK]

Common Mistakes:

• Using agent.send instead of agent.receive
• Trying to concatenate agent object with string
• Printing instead of returning the message

3. Given the code below, what will be the output?

class Agent:
    def receive(self, message):
        return f"Received: {message}"

def send_message(agent, message):
    return agent.receive(message)

agent = Agent()
print(send_message(agent, "Hello"))

medium

A. Error: method not found

B. Hello

C. send_message(agent, Hello)

D. Received: Hello

Solution

1. Step 1: Understand the Agent class and receive method

   The receive method returns the string 'Received: ' plus the message passed.

2. Step 2: Trace the send_message call

   send_message calls agent.receive with "Hello", so it returns 'Received: Hello'.

3. Final Answer:

   Received: Hello -> Option D

4. Quick Check:

   agent.receive("Hello") = "Received: Hello" [OK]

Hint: Agent.receive returns 'Received: ' plus message [OK]

Common Mistakes:

• Expecting just the message without prefix
• Thinking send_message prints instead of returns
• Assuming method does not exist causing error

4. Identify the error in the following Agent API code snippet:

class Agent:
    def receive(self, message):
        print(f"Got message: {message}")

def send_message(agent, message):
    return agent.receive(message)

agent = Agent()
response = send_message(agent, "Hi")
print(response)

medium

A. The receive method should return a value, not just print

B. send_message should not call agent.receive

C. Agent class is missing an __init__ method

D. The print statement in send_message is incorrect

Solution

1. Step 1: Check receive method behavior

   receive only prints the message but does not return anything, so it returns None by default.

2. Step 2: Analyze send_message and print(response)

   send_message returns None, so printing response outputs None, which is likely unintended.

3. Final Answer:

   The receive method should return a value, not just print -> Option A

4. Quick Check:

   receive must return message for send_message to work [OK]

Hint: receive must return, not just print, to pass data back [OK]

Common Mistakes:

• Ignoring that print returns None
• Thinking __init__ is required here
• Confusing print location with syntax error

5. You want to design an Agent API where multiple agents can collaborate by passing messages and roles define their behavior. Which design pattern best supports this?

hard

A. Factory pattern to create agents dynamically

B. Mediator pattern to centralize communication between agents

C. Singleton pattern to ensure one agent instance

D. Observer pattern to notify agents of state changes

Solution

1. Step 1: Understand collaboration and role-based behavior

   Agents need a central way to communicate and coordinate roles effectively.

2. Step 2: Match design patterns to needs

   The Mediator pattern centralizes communication, making it ideal for agent collaboration. Singleton limits to one instance, Factory creates objects, Observer handles notifications but not central communication.

3. Final Answer:

   Mediator pattern to centralize communication between agents -> Option B

4. Quick Check:

   Collaboration with roles = Mediator pattern [OK]

Hint: Mediator centralizes agent communication for collaboration [OK]

Common Mistakes:

• Choosing Singleton which limits to one agent
• Confusing Factory with communication pattern
• Using Observer which is for event notification only