Metadata preservation during splitting in LangChain - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the correct splitter class from LangChain.

LangChain

from langchain.text_splitter import [1]

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

ARecursiveCharacterTextSplitter

BCharacterTextSplitter

CTextSplitter

DMetadataSplitter

Attempts:

3 left

💡 Hint

Common Mistakes

Importing a non-existent class like MetadataSplitter.

Using a generic TextSplitter which is abstract.

The CharacterTextSplitter is the correct class to import for splitting text by characters while preserving metadata.

2fill in blank

medium

Complete the code to create a splitter that keeps metadata during splitting.

LangChain

splitter = CharacterTextSplitter(chunk_size=100, chunk_overlap=10, [1]=True)

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

Akeep_metadata

Badd_metadata

Cpreserve_metadata

Dreturn_metadata

Attempts:

3 left

💡 Hint

Common Mistakes

Using a wrong parameter name like preserve_metadata.

Not setting the parameter to True.

The keep_metadata parameter set to True ensures metadata is preserved during splitting.

3fill in blank

hard

Fix the error in the code to split documents while preserving metadata.

LangChain

docs = splitter.split_documents([1])

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

Adocuments

Btext

Cdoc

Ddocument_list

Attempts:

3 left

💡 Hint

Common Mistakes

Passing a single string instead of a list of documents.

Using a singular variable name that is not a list.

The method split_documents expects a list of documents, so the variable should be documents.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps document texts to their metadata.

LangChain

{doc.page_content: doc[1] for doc in documents if doc[2] is not None}

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

A.metadata

B.content

C.text

D.data

Attempts:

3 left

💡 Hint

Common Mistakes

Using incorrect attributes like .content or .text.

Checking the wrong attribute in the condition.

Each document's page_content is the key, and doc.metadata is the value. The condition checks if doc.metadata is not None.

5fill in blank

hard

Fill all three blanks to create a list comprehension that extracts metadata keys from documents with metadata.

LangChain

[doc.metadata[1] for doc in documents if doc.metadata[2] and '[3]' in doc.metadata]

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

A.keys()

Bis not None

Csource

Dget('source')

Attempts:

3 left

💡 Hint

Common Mistakes

Using get('source') instead of checking key presence.

Not checking if metadata is None before accessing keys.

The code extracts keys from doc.metadata for documents where metadata exists and contains the key 'source'.

Practice

1. What is the main benefit of preserving metadata when splitting documents in Langchain?

easy

A. It speeds up the splitting process.

B. It removes unnecessary text from documents.

C. It reduces the size of each chunk.

D. It keeps important context linked to each chunk.

Solution

1. Step 1: Understand what metadata means in this context

   Metadata is extra information about the document, like source or tags, that helps keep context.

2. Step 2: Recognize why preserving metadata is useful

   When splitting, keeping metadata ensures each chunk still knows where it came from and what it relates to.

3. Final Answer:

   It keeps important context linked to each chunk. -> Option D

4. Quick Check:

   Metadata preservation = keeps context [OK]

Hint: Metadata keeps context linked to chunks [OK]

Common Mistakes:

• Thinking metadata speeds splitting
• Confusing metadata with chunk size
• Believing metadata removes text

2. Which method in Langchain is used to split documents while preserving metadata?

easy

A. split_documents

B. preserve_metadata

C. chunk_text

D. split_text

Solution

1. Step 1: Recall the method name for splitting with metadata

   The method designed to split documents and keep metadata is called split_documents.

2. Step 2: Eliminate incorrect options

   Other options like preserve_metadata, chunk_text, and split_text are not valid Langchain methods for this purpose.

3. Final Answer:

   split_documents -> Option A

4. Quick Check:

   Method to split with metadata = split_documents [OK]

Hint: Remember method name: split_documents [OK]

Common Mistakes:

• Using split_text instead of split_documents
• Assuming preserve_metadata is a method
• Confusing chunk_text with splitting

3. Given this code snippet, what will be the metadata of the first chunk after splitting?

docs = [Document(page_content='Hello world', metadata={'source': 'file1'})]
splitter = RecursiveCharacterTextSplitter(chunk_size=5, chunk_overlap=0)
chunks = splitter.split_documents(docs)
print(chunks[0].metadata)

medium

A. null

B. {}

C. {'source': 'file1'}

D. {'chunk': 0}

Solution

1. Step 1: Understand the input document metadata

   The original document has metadata {'source': 'file1'}.

2. Step 2: Check if splitting preserves metadata

   The split_documents method keeps metadata for each chunk, so the first chunk keeps {'source': 'file1'}.

3. Final Answer:

   {'source': 'file1'} -> Option C

4. Quick Check:

   Metadata preserved = {'source': 'file1'} [OK]

Hint: Chunks keep original metadata unchanged [OK]

Common Mistakes:

• Expecting empty metadata after split
• Assuming metadata is lost or null
• Thinking chunk index is added to metadata

4. What is wrong with this code if the metadata is missing after splitting?

docs = [Document(page_content='Test text', metadata={'id': 123})]
splitter = RecursiveCharacterTextSplitter(chunk_size=4, chunk_overlap=1)
chunks = splitter.split_texts(docs)
print(chunks[0].metadata)

medium

A. Using split_texts instead of split_documents loses metadata.

B. Chunk size is too small to keep metadata.

C. Metadata key 'id' is invalid and removed.

D. Overlap must be zero to preserve metadata.

Solution

1. Step 1: Identify the method used for splitting

   The code uses split_texts which only splits text strings, not Document objects with metadata.

2. Step 2: Understand consequence on metadata

   Since split_texts works on strings, metadata is lost. The correct method to preserve metadata is split_documents.

3. Final Answer:

   Using split_texts instead of split_documents loses metadata. -> Option A

4. Quick Check:

   split_texts loses metadata [OK]

Hint: Use split_documents to keep metadata [OK]

Common Mistakes:

• Thinking chunk size affects metadata
• Believing metadata keys cause loss
• Assuming overlap affects metadata

5. You want to split a document into chunks of 100 characters with 20 characters overlapping, preserving metadata. Which code correctly achieves this?

hard

A. splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=20)
chunks = splitter.split_texts(docs)

B. splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=20)
chunks = splitter.split_documents(docs)

C. splitter = RecursiveCharacterTextSplitter(chunk_size=80, chunk_overlap=20)
chunks = splitter.split_documents(docs)

D. splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=0)
chunks = splitter.split_documents(docs)

Solution

1. Step 1: Set chunk size and overlap correctly

   The question asks for 100 characters chunk size and 20 characters overlap, so chunk_size=100 and chunk_overlap=20.

2. Step 2: Use the correct splitting method to preserve metadata

   To keep metadata, use split_documents method, not split_texts.

3. Final Answer:

   splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=20) chunks = splitter.split_documents(docs) -> Option B

4. Quick Check:

   Correct chunk size, overlap, and method = splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=20) chunks = splitter.split_documents(docs) [OK]

Hint: Match chunk size, overlap, and use split_documents [OK]

Common Mistakes:

• Using split_texts instead of split_documents
• Setting wrong chunk size or overlap
• Using zero overlap when asked for 20