Research assistant agent in Agentic AI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to initialize the research assistant agent with a knowledge base.

Agentic AI

agent = ResearchAssistantAgent(knowledge_base=[1])

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A123

Bmy_knowledge_base

CNone

DTrue

Attempts:

3 left

💡 Hint

Common Mistakes

Passing None instead of a knowledge base

Passing a number or boolean instead of a knowledge base object

The research assistant agent needs a knowledge base object to access information. Here, my_knowledge_base is the correct input.

2fill in blank

medium

Complete the code to make the agent search for a topic.

Agentic AI

results = agent.[1]('machine learning basics')

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Asummarize

Bpredict

Csearch

Dtrain

Attempts:

3 left

💡 Hint

Common Mistakes

Using summarize instead of search

Using train or predict which are for models, not searching

The search method lets the agent find information about a topic in the knowledge base.

3fill in blank

hard

Fix the error in the code to generate a summary from search results.

Agentic AI

summary = agent.[1](results)

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Asummarize

Bsearch

Ctrain

Dpredict

Attempts:

3 left

💡 Hint

Common Mistakes

Calling search again on results

Using train or predict which are unrelated here

The summarize method creates a short explanation from the search results.

4fill in blank

hard

Fill both blanks to train the agent and then make a prediction.

Agentic AI

agent.[1](training_data)
prediction = agent.[2](new_input)

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Atrain

Bpredict

Csearch

Dsummarize

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping train and predict

Using search or summarize instead of train or predict

First, the agent must be trained with data using train. Then it can make predictions with predict.

5fill in blank

hard

Fill all three blanks to create a report dictionary from keys, values, and a filter condition.

Agentic AI

report = [1]: [2] for [3], [2] in data.items() if [2] > 0

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Ak

Bv

Attempts:

3 left

💡 Hint

Common Mistakes

Using the same variable for key and value

Not matching variables in the filter condition

This dictionary comprehension uses k as key, v as value, and iterates over k, v pairs in data.items(). The filter keeps only items with value > 0.