chore: increase the lib version

[borisarzentar]

Summary by CodeRabbit

• New Features

  • Added chunk_size parameter to the read method across various document types (Audio, Document, Image, PDF, Text) to allow for customizable chunk sizes during text processing.
  • Updated the source_documents_to_chunks function to include a chunk_size parameter for improved document reading.
  • Modified the demo notebook to specify a chunk_size of 800 for document processing.

• Version Update

  • Project version updated from 0.1.15 to 0.1.16.

[coderabbitai]

Walkthrough

The pull request introduces modifications to the read methods across multiple document classes, including AudioDocument, Document, ImageDocument, PdfDocument, and TextDocument. Each read method now accepts an additional parameter, chunk_size, allowing for more controlled processing of text chunks. Additionally, the source_documents_to_chunks function has been updated to incorporate this new parameter, and the project version in pyproject.toml has been incremented.

Changes

File Path	Change Summary
cognee/modules/data/processing/document_types/*.py	Updated read method signatures to include chunk_size: int across AudioDocument, Document, ImageDocument, PdfDocument, and TextDocument.
cognee/tasks/source_documents_to_chunks/source_documents_to_chunks.py	Modified source_documents_to_chunks function to accept chunk_size parameter, defaulting to 1024.
notebooks/cognee_demo_1.5.ipynb	Updated Task(source_documents_to_chunks) to include chunk_size parameter with a value of 800.
pyproject.toml	Version updated from "0.1.15" to "0.1.16".

Possibly related PRs

• feat: add sqlalchemy as dlt destination #137: The changes in this PR are unrelated to the modifications made in the main PR, which focuses on the read method's parameter updates across various document classes.

Suggested reviewers

• Vasilije1990

Poem

🐰 In a world of chunks both big and small,
The rabbit hops to heed the call.
With chunk_size set, the text flows right,
Processing documents, day and night!
A version bump, a leap so grand,
Hooray for changes, let’s take a stand! 🌟

---

Recent review details

Configuration used: CodeRabbit UI
Review profile: CHILL

Commits

Files that changed from the base of the PR and between a9433e9 and f46308c.

Files selected for processing (8)

• cognee/modules/data/processing/document_types/AudioDocument.py (1 hunks)
• cognee/modules/data/processing/document_types/Document.py (1 hunks)
• cognee/modules/data/processing/document_types/ImageDocument.py (1 hunks)
• cognee/modules/data/processing/document_types/PdfDocument.py (1 hunks)
• cognee/modules/data/processing/document_types/TextDocument.py (2 hunks)
• cognee/tasks/source_documents_to_chunks/source_documents_to_chunks.py (2 hunks)
• notebooks/cognee_demo_1.5.ipynb (1 hunks)
• pyproject.toml (1 hunks)

Files skipped from review due to trivial changes (1)

• pyproject.toml

Additional comments not posted (11)

cognee/modules/data/processing/document_types/Document.py (1)

10-11: Verify the impact of the breaking change in the codebase.

The addition of the chunk_size parameter to the read method is a breaking change. It alters the method's interface and requires all implementations of the Document protocol to be updated.

Run the following script to verify the usage of the read method across the codebase:

To maintain backward compatibility, consider adding a default value for the chunk_size parameter if possible:

def read(self, chunk_size: int = -1) -> str:
    pass

A default value of -1 could indicate reading the entire data in one chunk, preserving the previous behavior.

Verification successful

---

Breaking change successfully implemented across the codebase

The addition of the chunk_size parameter to the read method in the Document protocol has been properly implemented across the codebase. All implementations of the Document protocol (TextDocument, PdfDocument, ImageDocument, AudioDocument) have been updated to include the chunk_size: int parameter in their read method.

No instances of Document.read() being called without the chunk_size parameter were found. The .read() calls without parameters that were detected are unrelated to the Document protocol and appear to be standard file I/O operations.

Based on this analysis, it appears that the breaking change has been consistently and correctly applied throughout the codebase.

Scripts executed

The following scripts were executed for the analysis:

Script:

#!/bin/bash
# Description: Verify all calls to the `read` method of `Document` protocol.

# Test: Search for the method usage. Expect: Only occurrences with the new signature.
rg --type python -A 5 $'Document\(\)\.read'

Length of output: 75

---

Script:

#!/bin/bash
# Description: Verify usage of the `read` method and implementations of the `Document` protocol

# Search for `read` method calls
echo "Searching for 'read' method calls:"
rg -i '\.read\s*\(' -A 5

# Look for potential implementations of the Document protocol
echo -e "\nSearching for potential Document implementations:"
rg -i 'class.*\(.*Document.*\):'

# Search for import statements of the Document class
echo -e "\nSearching for Document imports:"
rg -i 'from.*import.*Document'

Length of output: 12666

---

Script:

#!/bin/bash
# Description: Verify Document implementations and remaining calls without chunk_size

# Check Document implementations
echo "Checking Document implementations:"
rg -i 'def read\s*\(' cognee/modules/data/processing/document_types/*.py

# Check for remaining calls without chunk_size
echo -e "\nChecking for remaining calls without chunk_size:"
rg -i '\.read\s*\(\s*\)' --type py

Length of output: 2599

cognee/modules/data/processing/document_types/ImageDocument.py (2)

22-22: Verify that TextChunker constructor is updated to handle chunk_size.

Passing the chunk_size from the read method to the TextChunker constructor is the correct way to propagate the chunking configuration.

Verify that the TextChunker constructor is indeed updated to accept and handle the chunk_size parameter correctly. Ensure that the chunking logic inside TextChunker is adapted to use the provided chunk_size.

Run the following script to check the TextChunker constructor:

#!/bin/bash
# Description: Check if `TextChunker` constructor accepts `chunk_size` parameter.

# Test: Search for the constructor definition. Expect: `chunk_size` in the parameter list.
ast-grep --lang python --pattern $'class TextChunker {
  $$$
  __init__($_, chunk_size: int, $_) {
    $$$
  }
  $$$
}'

---

17-17: Verify method calls and update documentation for the new chunk_size parameter.

The new chunk_size parameter allows for more control over the text chunking process, which is a good improvement.

However, this is a breaking change. Verify if the read method is being called from other parts of the codebase and ensure those calls are updated to pass the chunk_size argument.

Also, update the method's docstring to document the new parameter and its purpose.

Run the following script to find all references to the read method:

Verification successful

Manual verification required for ImageDocument.read() method

The ImageDocument class exists in ./cognee/modules/data/processing/document_types/ImageDocument.py, but we couldn't verify the presence or current state of the read() method. Our search didn't find any usage of this method in the codebase.

Please manually check the ImageDocument class to confirm:

1. If the read() method still exists.
2. If it exists, verify its current signature and implementation.
3. If it has been removed or renamed, assess the impact on the rest of the codebase.

This is crucial because:

• If the method was changed as per the review comment (adding a chunk_size parameter), there might be breaking changes in the codebase.
• If the method was removed or renamed, it could lead to errors in parts of the code that might be using it.

To assist with the manual verification, you can start by examining the contents of the ImageDocument.py file:

---

Verification successful: ImageDocument.read() method implemented correctly

The read() method in the ImageDocument class has been successfully implemented with the chunk_size parameter as suggested in the original review comment. The method signature is:

def read(self, chunk_size: int):

Key points:

• The chunk_size parameter is correctly used when creating a TextChunker instance.
• The method transcribes the image file and then chunks the resulting text.
• The implementation yields chunks using the chunker.read() method.

Recommendations:

1. Update the method's docstring to document the new chunk_size parameter and its purpose.
2. Review any code that calls this method to ensure it's updated with the new chunk_size argument.
3. Consider adding type hints for the return value (e.g., -> Iterator[str]) to improve code clarity.

While our previous searches didn't find any direct usage of this method, it's still important to thoroughly review the codebase for any potential calls to ImageDocument.read() that might need updating.

Scripts executed

The following scripts were executed for the analysis:

Script:

#!/bin/bash
# Description: Find all references to the `read` method of `ImageDocument` class.

# Test: Search for the method usage. Expect: Only occurrences with the new signature.
rg --type python -A 5 $'ImageDocument.+\.read'

Length of output: 465

---

Script:

#!/bin/bash
# Description: Verify ImageDocument class and its read method

# Find the ImageDocument class definition
echo "Searching for ImageDocument class definition:"
rg --type python "class ImageDocument"

# Find imports of ImageDocument
echo -e "\nSearching for ImageDocument imports:"
rg --type python "from .+ import ImageDocument|import .+ImageDocument"

# Find the read method definition in ImageDocument class
echo -e "\nSearching for read method in ImageDocument class:"
rg --type python -A 3 "class ImageDocument" | rg "def read"

# Find any usage of read method on ImageDocument instances
echo -e "\nSearching for read method usage on ImageDocument instances:"
rg --type python "ImageDocument.+\.read"

Length of output: 782

---

Script:

#!/bin/bash
# Description: Verify ImageDocument class and its read method using basic Unix commands

# Find Python files
echo "Searching for Python files:"
find . -name "*.py"

# Find the ImageDocument class definition
echo -e "\nSearching for ImageDocument class definition:"
find . -name "*.py" -exec grep -H "class ImageDocument" {} +

# Find imports of ImageDocument
echo -e "\nSearching for ImageDocument imports:"
find . -name "*.py" -exec grep -H -E "from .+ import ImageDocument|import .+ImageDocument" {} +

# Find the read method definition in ImageDocument class
echo -e "\nSearching for read method in ImageDocument class:"
find . -name "*.py" -exec grep -H -A 3 "class ImageDocument" {} + | grep "def read"

# Find any usage of read method on ImageDocument instances
echo -e "\nSearching for read method usage on ImageDocument instances:"
find . -name "*.py" -exec grep -H -E "ImageDocument.+\.read" {} +

# If no results, search for files containing "ImageDocument" in case the class name changed
echo -e "\nSearching for files containing 'ImageDocument':"
find . -type f -exec grep -l "ImageDocument" {} +

Length of output: 15558

---

Script:

#!/bin/bash
# Display the contents of the ImageDocument.py file
cat ./cognee/modules/data/processing/document_types/ImageDocument.py

Length of output: 1106

cognee/modules/data/processing/document_types/PdfDocument.py (2)

24-24: LGTM!

Passing the chunk_size parameter to the TextChunker constructor is the correct way to utilize the new functionality.

---

16-16: Verify the method signature change in the codebase.

The read method signature has been updated to accept a new parameter chunk_size. This change looks good, but please ensure that all callers of this method have been updated to pass the chunk_size argument.

Run the following script to verify the method usage:

cognee/modules/data/processing/document_types/TextDocument.py (2)

27-27: LGTM!

The TextChunker instantiation has been updated to pass the chunk_size argument, which is consistent with the read method signature change. This allows the TextChunker to utilize the specified chunk size when processing the text data.

---

15-15: Verify the method signature change in the codebase.

The read method signature has been updated to accept a new parameter chunk_size of type int. This change allows the caller to control the chunk size when reading the text document.

Please ensure that all callers of this method have been updated to pass the chunk_size argument to avoid runtime exceptions.

Run the following script to verify the method usage:

Verification successful

---

Verification complete: chunk_size parameter correctly implemented across document types.

The read method has been consistently updated to include the chunk_size: int parameter in all document types that inherit from the Document class:

• TextDocument
• ImageDocument
• AudioDocument

All implementations correctly use the chunk_size parameter when initializing the TextChunker. While we didn't find direct calls to the read method, the consistent implementation across all document types suggests that the change was intentional and thoroughly applied.

No issues were found with this implementation. The change appears to be correct and consistent throughout the codebase.

Scripts executed

The following scripts were executed for the analysis:

Script:

#!/bin/bash
# Description: Verify all calls to the `read` method of `TextDocument` pass the `chunk_size` argument.

# Test: Search for the method usage. Expect: Only occurrences with the `chunk_size` argument.
rg --type python -A 5 $'TextDocument\(\)\.read'

Length of output: 79

---

Script:

#!/bin/bash
# Description: Verify all calls to the `read` method of `TextDocument` pass the `chunk_size` argument.

# Find all Python files and search for TextDocument().read and TextDocument.read
fd '\.py$' --exec rg -n -A 5 'TextDocument(\(\))?\.read' {}

# Search for TextDocument class definition to understand its usage
ast-grep --lang python --pattern 'class TextDocument:
  $$$
  def read($$$):
    $$$
'

# Search for imports of TextDocument to find files that might use it
rg -n 'from .*TextDocument import TextDocument'

Length of output: 301

---

Script:

#!/bin/bash
# Verify the existence and content of TextDocument.py
cat cognee/modules/data/processing/document_types/TextDocument.py

# Search for any usage of TextDocument class
rg -n 'TextDocument'

# Search for potential wrapper functions that might use TextDocument
ast-grep --lang python --pattern 'def $_($$):
  $$$
  TextDocument
  $$$
'

Length of output: 1831

---

Script:

#!/bin/bash
# Search for calls to Document.read() method
rg -n 'Document.*\.read\('

# Search for other classes that inherit from Document
ast-grep --lang python --pattern 'class $_(Document):
  $$$
  def read($$$):
    $$$
'

Length of output: 8715

cognee/modules/data/processing/document_types/AudioDocument.py (2)

23-23: LGTM!

Passing the chunk_size argument to the TextChunker constructor aligns with the updated read method signature and its purpose of controlling the size of the text chunks.

---

18-18: Verify the method signature change in the codebase.

The change to the read method signature to accept the chunk_size parameter is a good addition. It allows controlling the size of the text chunks yielded by the method.

Run the following script to verify the method usage:

Verification successful

---

Verification successful: read method signature change is consistent with usage

The change to the read method signature in AudioDocument to include the chunk_size parameter is verified and consistent with its usage across the codebase. Key points:

1. The Document Protocol defines the read method with the chunk_size parameter.
2. The source_documents_to_chunks function demonstrates correct usage of document.read(chunk_size=chunk_size).
3. As AudioDocument implements the Document Protocol, it correctly includes the chunk_size parameter in its read method.

This change ensures that AudioDocument remains compatible with the existing codebase and maintains consistency with other document types.

Scripts executed

The following scripts were executed for the analysis:

Script:

#!/bin/bash
# Description: Verify all calls to the `read` method of `AudioDocument` pass the `chunk_size` argument.

# Test: Search for the method usage. Expect: Only occurrences with the `chunk_size` argument.
rg --type python -A 5 $'AudioDocument\(\)\.read'

Length of output: 80

---

Script:

#!/bin/bash
# Search for AudioDocument class definition
echo "Searching for AudioDocument class definition:"
rg "class AudioDocument"

# Search for usage of read method on AudioDocument instances
echo -e "\nSearching for usage of read method on AudioDocument instances:"
rg "AudioDocument.*\.read"

# Use ast-grep to find more precise matches for method calls
echo -e "\nUsing ast-grep to find method calls:"
ast-grep --lang python --pattern "AudioDocument().read($$$)"

Length of output: 546

---

Script:

#!/bin/bash
# Search for imports of AudioDocument
echo "Searching for imports of AudioDocument:"
rg "from.*import.*AudioDocument"

# Search for any references to AudioDocument
echo -e "\nSearching for references to AudioDocument:"
rg "AudioDocument"

# Use ast-grep to find variable assignments of AudioDocument instances
echo -e "\nSearching for AudioDocument instance assignments:"
ast-grep --lang python --pattern "$_ = AudioDocument($$$)"

Length of output: 1694

---

Script:

#!/bin/bash
# Search for Document base class definition
echo "Searching for Document base class definition:"
rg "class Document"

# Search for usage of read method on Document instances
echo -e "\nSearching for usage of read method on Document instances:"
rg "Document.*\.read"

# Search for polymorphic usage of Document subclasses
echo -e "\nSearching for polymorphic usage of Document subclasses:"
rg "def.*\(.*Document.*\).*:"

# Use ast-grep to find method calls on variables of type Document
echo -e "\nSearching for method calls on Document variables:"
ast-grep --lang python --pattern "$_: Document
$$$
$_.read($$$)"

Length of output: 3326

---

Script:

#!/bin/bash
# Check the contents of the Document Protocol
echo "Checking the contents of the Document Protocol:"
cat cognee/modules/data/processing/document_types/Document.py

# Investigate the source_documents_to_chunks function
echo -e "\nInvestigating the source_documents_to_chunks function:"
cat cognee/tasks/source_documents_to_chunks/source_documents_to_chunks.py

# Look for iteration or comprehension over Document objects
echo -e "\nSearching for iteration or comprehension over Document objects:"
rg -A 5 "for.*document.*in.*documents:"
rg -A 5 "\[.*for.*document.*in.*documents.*\]"

Length of output: 4487

cognee/tasks/source_documents_to_chunks/source_documents_to_chunks.py (1)

5-5: LGTM!

The changes to the function signature and logic are correct and provide more flexibility to the caller.

• The new chunk_size parameter allows the caller to specify the size of the chunks.
• The default value of 1024 for chunk_size is a reasonable default for most use cases.
• The function logic correctly passes the chunk_size parameter to the document.read() method.

Also applies to: 43-43

notebooks/cognee_demo_1.5.ipynb (1)

394-394: Approve the chunk_size parameter addition.

The new chunk_size parameter allows controlling the size of the chunks created from source documents, which can impact the granularity and performance of the pipeline.

To ensure the chosen chunk_size value is optimal, consider:

1. Benchmarking the pipeline's performance with different chunk_size values to find the best balance between speed and resource usage.
2. Assessing the quality of the output generated by downstream tasks (e.g., chunks_into_graph) for different chunk_size values to ensure the desired level of detail is maintained.
3. Documenting the rationale behind the chosen chunk_size value and any trade-offs made.

Here's a script to help verify the impact of chunk_size on the pipeline:

Please update the TODO sections with the appropriate code to execute the pipeline and evaluate the results for each chunk_size value. The script's output will help determine the optimal chunk_size based on performance and quality metrics.

Verification successful

To gather more information about existing performance measurements and quality assessments in the codebase, let's run the following script:

This script will help us find any existing code or documentation related to performance measurement, chunk_size optimization, quality assessment, and pipeline configuration. The results will guide our next steps in verifying the impact of the chunk_size parameter.

---

Confirm the importance of verifying chunk_size impact and suggest improvements.

The review comment highlighting the need to verify the impact of the chunk_size parameter is valid and important. The chunk_size parameter is used extensively throughout the codebase for document processing and affects how documents are split into smaller pieces.

To ensure optimal performance and output quality:

1. Implement a benchmarking mechanism to measure processing time and resource usage for different chunk_size values.
2. Create a quality assessment process to evaluate the output of downstream tasks for various chunk_size settings.
3. Document the rationale behind the chosen chunk_size value (currently set to 800) and any trade-offs considered.
4. If not already integrated, consider incorporating the RAG test tool mentioned in the blog post to facilitate easier testing and optimization of RAG applications, including chunk_size tuning.

These improvements will help validate the chosen chunk_size value and provide a systematic way to optimize it in the future.

Scripts executed

The following scripts were executed for the analysis:

Script:

#!/bin/bash

# Description: Verify the impact of chunk_size on pipeline performance and output quality.

# Test 1: Benchmark pipeline performance for different chunk_size values.
for size in 100 200 400 800 1600; do
  echo "Running pipeline with chunk_size=$size"
  # TODO: Implement code to run the pipeline with the specified chunk_size and measure execution time.
done

# Test 2: Assess output quality for different chunk_size values.
for size in 100 200 400 800 1600; do
  echo "Assessing output quality for chunk_size=$size"
  # TODO: Implement code to run the pipeline with the specified chunk_size and evaluate the quality of the generated knowledge graph.
done

Length of output: 1253

---

Script:

#!/bin/bash

# Search for performance measurement or benchmarking code
echo "Searching for performance measurement or benchmarking code:"
rg -i "benchmark|performance|execution time|measure" --type py -A 5 -B 5

echo "\nSearching for chunk_size related comments or documentation:"
rg -i "chunk_size|chunk size" --type py --type md -A 3 -B 3

echo "\nSearching for quality assessment or evaluation code:"
rg -i "quality|evaluation|assess|metric" --type py -A 5 -B 5

echo "\nSearching for pipeline configuration or parameter tuning:"
rg -i "pipeline|parameter|tuning|optimization" --type py --type md -A 3 -B 3

Length of output: 123571

---

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