Text chunking strategies in Prompt Engineering / GenAI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to split text into chunks of fixed size.

Prompt Engineering / GenAI

def chunk_text(text, size):
    return [text[i:i+[1]] for i in range(0, len(text), size)]

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Alen

Btext

Csize

Di

Attempts:

3 left

💡 Hint

Common Mistakes

Using len instead of size causes incorrect slicing.

Using i instead of size results in wrong chunk lengths.

The chunk size is controlled by the 'size' parameter, so we slice text using size.

2fill in blank

medium

Complete the code to split text into chunks without breaking words.

Prompt Engineering / GenAI

def chunk_text_words(text, max_len):
    words = text.split()
    chunks = []
    current = ''
    for word in words:
        if len(current) + len(word) + 1 > [1]:
            chunks.append(current.strip())
            current = word + ' '
        else:
            current += word + ' '
    if current:
        chunks.append(current.strip())
    return chunks

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Amax_len

Blen(word)

Clen(current)

Dtext

Attempts:

3 left

💡 Hint

Common Mistakes

Using len(current) instead of max_len causes wrong chunk size checks.

Comparing to len(word) alone does not limit chunk length.

We compare the length of the current chunk plus the next word to max_len to avoid breaking words.

3fill in blank

hard

Fix the error in the code to create overlapping text chunks.

Prompt Engineering / GenAI

def overlapping_chunks(text, size, overlap):
    chunks = []
    start = 0
    while start < len(text):
        end = start + size
        chunks.append(text[start:end])
        start += [1]
    return chunks

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Asize

Bsize - overlap

Coverlap

Dsize + overlap

Attempts:

3 left

💡 Hint

Common Mistakes

Adding overlap to size causes gaps instead of overlaps.

Using overlap alone moves too little, causing repeated chunks.

To create overlapping chunks, we move the start by size minus overlap each time.

4fill in blank

hard

Fill both blanks to create a dictionary of chunk indices and their text.

Prompt Engineering / GenAI

def chunk_dict(text, chunk_size):
    return {i: text[i[1]i+[2]] for i in range(0, len(text), chunk_size)}

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A*

B+

C-

D//

Attempts:

3 left

💡 Hint

Common Mistakes

Using '*' or '//' causes type errors in slicing.

Using '-' results in negative slice indices.

We use '+' to add chunk_size to i for slicing the chunk correctly.

5fill in blank

hard

Fill all three blanks to create a list of chunks with a minimum overlap.

Prompt Engineering / GenAI

def min_overlap_chunks(text, size, min_overlap):
    chunks = []
    i = 0
    while i < len(text):
        chunk = text[i:i+[1]]
        chunks.append(chunk)
        i += [2] if [3] < size else size
    return chunks

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Asize

Bmin_overlap

Di

Attempts:

3 left

💡 Hint

Common Mistakes

Using i instead of size for chunk length causes wrong slices.

Not comparing min_overlap to size causes infinite loops.

We slice chunks of length size, then move i by min_overlap if it is less than size, else by size.