Combining retrieval with agent reasoning in Agentic AI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to initialize the retrieval agent with a knowledge base.

Agentic AI

agent = RetrievalAgent(knowledge_base=[1])

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

Aresponse

Bquery

Ckb

Dagent

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'query' instead of the knowledge base variable.

Passing the agent itself as the knowledge base.

The retrieval agent needs the knowledge base object, usually named 'kb', to access stored information.

2fill in blank

medium

Complete the code to perform a retrieval before reasoning.

Agentic AI

retrieved_docs = agent.retrieve([1])

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Aresponse

Bagent

Cknowledge_base

Dquery_text

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the agent object instead of the query string.

Using the knowledge base variable instead of the query.

The agent retrieves documents based on the input query text.

3fill in blank

hard

Fix the error in the reasoning step by filling the correct method to process retrieved documents.

Agentic AI

answer = agent.[1](retrieved_docs)

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Athink

Breason

Cprocess

Dquery

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'query' which is for searching, not reasoning.

Using 'process' or 'think' which are not valid method names.

The agent uses the 'reason' method to analyze retrieved documents and generate an answer.

4fill in blank

hard

Fill both blanks to combine retrieval and reasoning in one step.

Agentic AI

final_answer = agent.[1](agent.[2](query_text))

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Areason

Bretrieve

Cquery

Danswer

Attempts:

3 left

💡 Hint

Common Mistakes

Reversing the order of 'reason' and 'retrieve'.

Using 'query' or 'answer' which are not correct method names here.

First, the agent retrieves documents with 'retrieve', then reasons over them with 'reason'.

5fill in blank

hard

Fill all three blanks to create a function that takes a query, retrieves documents, reasons, and returns the answer.

Agentic AI

def answer_query([1]):
    docs = agent.[2]([3])
    return agent.reason(docs)

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

Aquery_text

Bretrieve

Dresponse

Attempts:

3 left

💡 Hint

Common Mistakes

Using different variable names for the function input and retrieval argument.

Using 'response' instead of 'query_text' as input.

The function takes 'query_text' as input, uses 'retrieve' to get docs, then reasons to return the answer.