Parent-child document retrieval in Prompt Engineering / GenAI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to retrieve child documents linked to a parent document.

Prompt Engineering / GenAI

child_docs = client.search(index='children', query={'parent_id': [1])

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

A'12345'

B'parent_id'

C'children'

D'parent_doc'

Attempts:

3 left

💡 Hint

Common Mistakes

Using the field name 'parent_id' instead of the actual ID value.

Using the index name instead of the ID.

The parent document ID '12345' is needed to find its child documents.

2fill in blank

medium

Complete the code to filter parent documents that have children with a specific attribute.

Prompt Engineering / GenAI

parents = client.search(index='parents', query={'has_child': {'type': 'child', 'query': {'term': {'[1]': 'active'}}}})

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

Astatus

Bparent_id

Cchild_id

Dtype

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'parent_id' which is not a child attribute.

Using 'type' which is a fixed value.

We filter children by their 'status' field to find parents with active children.

3fill in blank

hard

Fix the error in the code to correctly retrieve parents with children matching a condition.

Prompt Engineering / GenAI

results = client.search(index='parents', query={'has_child': {'type': 'child', 'query': {'match': {'[1]': 'urgent'}}}})

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

Achild_id

Bpriority

Cparent_id

Dstatus

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'parent_id' which is not a child field.

Using 'status' which may not indicate urgency.

The 'priority' field in children is matched to find urgent child documents.

4fill in blank

hard

Fill both blanks to build a dictionary comprehension that maps parent IDs to counts of their children with score above 80.

Prompt Engineering / GenAI

parent_child_counts = {parent['id']: sum(1 for child in parent['children'] if child['score'][1] 80) for parent in parents if 'children' [2] parent}

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

A>

Bin

C==

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' for score comparison.

Using '==' instead of 'in' to check key existence.

We count children with score > 80 and check if 'children' key exists in parent.

5fill in blank

hard

Fill all three blanks to create a filtered list of child documents with type 'comment' and length of text over 50.

Prompt Engineering / GenAI

filtered_children = [child for child in children if child['type'] == '[1]' and len(child['[2]']) [3] 50]

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

Acomment

Btext

C>

Dcontent

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'content' instead of 'text' for the field name.

Using '<' instead of '>' for length comparison.

We filter children of type 'comment' whose 'text' length is greater than 50 characters.

Practice

1. What is the main purpose of parent-child document retrieval in GenAI systems?

easy

A. To find related documents where one is the parent and others are children

B. To sort documents alphabetically

C. To delete duplicate documents automatically

D. To translate documents into different languages

Solution

1. Step 1: Understand parent-child relationship

   Parent-child document retrieval means finding documents linked by a hierarchical relationship, where one document is the parent and others are its children.

2. Step 2: Identify retrieval goal

   The goal is to retrieve documents that are connected in this way, not just any documents or unrelated tasks like sorting or translating.

3. Final Answer:

   To find related documents where one is the parent and others are children -> Option A

4. Quick Check:

   Parent-child retrieval = find related hierarchical documents [OK]

Hint: Think hierarchy: parent document with linked child documents [OK]

Common Mistakes:

• Confusing retrieval with sorting or translation
• Ignoring the hierarchical link between documents
• Assuming it deletes or modifies documents

2. Which of the following is the correct syntax to query child documents given a parent ID in a GenAI retrieval system?

easy

A. query = {"parent": "12345"}

B. query = {"child_of": "12345"}

C. query = {"parent_id": "12345"}

D. query = {"child_id": "12345"}

Solution

1. Step 1: Identify correct key for parent ID

   In GenAI retrieval, the key to specify parent document ID for child retrieval is usually "parent_id".

2. Step 2: Check other options for correctness

   Options like "child_of", "parent", or "child_id" are not standard or correct keys for this query.

3. Final Answer:

   query = {"parent_id": "12345"} -> Option C

4. Quick Check:

   Use "parent_id" key to query children [OK]

Hint: Look for "parent_id" key to find children documents [OK]

Common Mistakes:

• Using incorrect keys like "child_of" or "child_id"
• Confusing parent and child identifiers
• Omitting quotes around keys or values

3. Given the following code snippet for retrieving child documents, what will be the output if the parent ID has two children with IDs 'c1' and 'c2'?

parent_id = 'p123'
children = retrieve_children(parent_id)
print(children)

medium

A. ['c1', 'c2']

B. ['p123']

C. []

D. Error: retrieve_children not defined

Solution

1. Step 1: Understand function purpose

   The function retrieve_children(parent_id) is designed to return a list of child document IDs for the given parent ID.

2. Step 2: Analyze given data

   Since the parent ID 'p123' has two children with IDs 'c1' and 'c2', the function should return these IDs in a list.

3. Final Answer:

   ['c1', 'c2'] -> Option A

4. Quick Check:

   retrieve_children returns child IDs list [OK]

Hint: Function returns list of children IDs for given parent [OK]

Common Mistakes:

• Assuming it returns parent ID instead of children
• Expecting empty list when children exist
• Confusing function name or missing definition

4. You have this code snippet to retrieve parent documents but it raises an error:

def get_parent(child_id):
    return retrieve_parent(child_id)

print(get_parent('c123'))

What is the most likely cause of the error?

medium

A. The function get_parent has wrong indentation

B. The child_id 'c123' does not exist

C. The print statement syntax is incorrect

D. The function retrieve_parent is not defined or imported

Solution

1. Step 1: Check function usage

   The function get_parent calls retrieve_parent, which must be defined or imported to work.

2. Step 2: Identify error cause

   If retrieve_parent is missing, Python raises a NameError. Other options like child ID missing or print syntax error would cause different errors.

3. Final Answer:

   The function retrieve_parent is not defined or imported -> Option D

4. Quick Check:

   Undefined function causes NameError [OK]

Hint: Check if all called functions are defined or imported [OK]

Common Mistakes:

• Assuming child ID missing causes this error
• Thinking print syntax is wrong
• Ignoring missing function definitions

5. You want to retrieve all child documents for multiple parent documents efficiently. Which approach best applies parent-child document retrieval in GenAI to achieve this?

hard

A. Query each parent ID separately in a loop and combine results

B. Batch query using a list of parent IDs to fetch all children at once

C. Retrieve all documents and filter children manually by parent ID

D. Use a random sampling of documents ignoring parent-child links

Solution

1. Step 1: Understand efficiency in retrieval

   Batch querying multiple parent IDs at once reduces repeated calls and speeds up retrieval.

2. Step 2: Compare approaches

   Querying separately is slower; filtering all documents wastes resources; random sampling ignores relationships.

3. Final Answer:

   Batch query using a list of parent IDs to fetch all children at once -> Option B

4. Quick Check:

   Batch queries improve efficiency in parent-child retrieval [OK]

Hint: Batch queries reduce calls and speed retrieval [OK]

Common Mistakes:

• Querying parents one by one causing slow performance
• Filtering all documents instead of targeted retrieval
• Ignoring parent-child relationships in sampling