feat: externalize chunkers [cog-1354] (#547)

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## Description
<!-- Provide a clear description of the changes in this PR -->

## DCO Affirmation
I affirm that all code in every commit of this pull request conforms to
the terms of the Topoteretes Developer Certificate of Origin


<!-- This is an auto-generated comment: release notes by coderabbit.ai
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## Summary by CodeRabbit

- **New Features**
- Enhanced document chunk extraction for improved processing consistency
across multiple formats.

- **Refactor**
- Streamlined the configuration for text chunking by replacing indirect
mappings with a direct instantiation approach across document types.
- Updated method signatures across various document classes to accept
chunker class references instead of string identifiers.

- **Chores**
- Removed legacy configuration utilities related to document chunking to
simplify processing.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Co-authored-by: Boris <boris@topoteretes.com>

cognee/api/v1/cognify/cognify_v2.py

@@ -25,6 +25,7 @@ from cognee.tasks.documents import (
 from cognee.tasks.graph import extract_graph_from_data
 from cognee.tasks.storage import add_data_points
 from cognee.tasks.summarization import summarize_text
+from cognee.modules.chunking.TextChunker import TextChunker
 
 logger = logging.getLogger("cognify.v2")
 
@@ -123,7 +124,9 @@ async def get_default_tasks(
             Task(classify_documents),
             Task(check_permissions_on_documents, user=user, permissions=["write"]),
             Task(
-                extract_chunks_from_documents, max_chunk_tokens=get_max_chunk_tokens()
+                extract_chunks_from_documents,
+                max_chunk_tokens=get_max_chunk_tokens(),
+                chunker=TextChunker,
             ),  # Extract text chunks based on the document type.
             Task(
                 extract_graph_from_data, graph_model=graph_model, task_config={"batch_size": 10}

cognee/modules/data/processing/document_types/AudioDocument.py

@@ -1,8 +1,5 @@
-from typing import Optional
-
 from cognee.infrastructure.llm.get_llm_client import get_llm_client
 
-from .ChunkerMapping import ChunkerConfig
 from .Document import Document
 
 
@@ -13,13 +10,12 @@ class AudioDocument(Document):
         result = get_llm_client().create_transcript(self.raw_data_location)
         return result.text
 
-    def read(self, chunk_size: int, chunker: str, max_chunk_tokens: int):
+    def read(self, chunk_size: int, chunker_cls: type, max_chunk_tokens: int):
         # Transcribe the audio file
 
         text = self.create_transcript()
 
-        chunker_func = ChunkerConfig.get_chunker(chunker)
+        chunker = chunker_cls(
-        chunker = chunker_func(
             self, chunk_size=chunk_size, get_text=lambda: [text], max_chunk_tokens=max_chunk_tokens
         )
 

cognee/modules/data/processing/document_types/ChunkerMapping.py

@@ -1,14 +0,0 @@
-from cognee.modules.chunking.TextChunker import TextChunker
-
-
-class ChunkerConfig:
-    chunker_mapping = {"text_chunker": TextChunker}
-
-    @classmethod
-    def get_chunker(cls, chunker_name: str):
-        chunker_class = cls.chunker_mapping.get(chunker_name)
-        if chunker_class is None:
-            raise NotImplementedError(
-                f"Chunker '{chunker_name}' is not implemented. Available options: {list(cls.chunker_mapping.keys())}"
-            )
-        return chunker_class

cognee/modules/data/processing/document_types/Document.py

@@ -9,5 +9,7 @@ class Document(DataPoint):
     mime_type: str
     metadata: dict = {"index_fields": ["name"]}
 
-    def read(self, chunk_size: int, chunker=str, max_chunk_tokens: Optional[int] = None) -> str:
+    def read(
+        self, chunk_size: int, chunker_cls: type, max_chunk_tokens: Optional[int] = None
+    ) -> str:
         pass

cognee/modules/data/processing/document_types/ImageDocument.py

@@ -1,8 +1,5 @@
-from typing import Optional
-
 from cognee.infrastructure.llm.get_llm_client import get_llm_client
 
-from .ChunkerMapping import ChunkerConfig
 from .Document import Document
 
 
@@ -13,12 +10,11 @@ class ImageDocument(Document):
         result = get_llm_client().transcribe_image(self.raw_data_location)
         return result.choices[0].message.content
 
-    def read(self, chunk_size: int, chunker: str, max_chunk_tokens: int):
+    def read(self, chunk_size: int, chunker_cls: type, max_chunk_tokens: int):
         # Transcribe the image file
         text = self.transcribe_image()
 
-        chunker_func = ChunkerConfig.get_chunker(chunker)
+        chunker = chunker_cls(
-        chunker = chunker_func(
             self, chunk_size=chunk_size, get_text=lambda: [text], max_chunk_tokens=max_chunk_tokens
         )
 

cognee/modules/data/processing/document_types/PdfDocument.py

@@ -1,15 +1,12 @@
-from typing import Optional
-
 from pypdf import PdfReader
 
-from .ChunkerMapping import ChunkerConfig
 from .Document import Document
 
 
 class PdfDocument(Document):
     type: str = "pdf"
 
-    def read(self, chunk_size: int, chunker: str, max_chunk_tokens: int):
+    def read(self, chunk_size: int, chunker_cls: type, max_chunk_tokens: int):
         file = PdfReader(self.raw_data_location)
 
         def get_text():
@@ -17,8 +14,7 @@ class PdfDocument(Document):
                 page_text = page.extract_text()
                 yield page_text
 
-        chunker_func = ChunkerConfig.get_chunker(chunker)
+        chunker = chunker_cls(
-        chunker = chunker_func(
             self, chunk_size=chunk_size, get_text=get_text, max_chunk_tokens=max_chunk_tokens
         )
 

cognee/modules/data/processing/document_types/TextDocument.py

@@ -1,11 +1,10 @@
-from .ChunkerMapping import ChunkerConfig
 from .Document import Document
 
 
 class TextDocument(Document):
     type: str = "text"
 
-    def read(self, chunk_size: int, chunker: str, max_chunk_tokens: int):
+    def read(self, chunk_size: int, chunker_cls: type, max_chunk_tokens: int):
         def get_text():
             with open(self.raw_data_location, mode="r", encoding="utf-8") as file:
                 while True:
@@ -16,9 +15,7 @@ class TextDocument(Document):
 
                     yield text
 
-        chunker_func = ChunkerConfig.get_chunker(chunker)
+        chunker = chunker_cls(
-
-        chunker = chunker_func(
             self, chunk_size=chunk_size, get_text=get_text, max_chunk_tokens=max_chunk_tokens
         )
 

cognee/modules/data/processing/document_types/UnstructuredDocument.py

@@ -1,5 +1,4 @@
 from io import StringIO
-from typing import Optional
 
 from cognee.modules.chunking.TextChunker import TextChunker
 from cognee.modules.data.exceptions import UnstructuredLibraryImportError
@@ -10,7 +9,7 @@ from .Document import Document
 class UnstructuredDocument(Document):
     type: str = "unstructured"
 
-    def read(self, chunk_size: int, chunker: str, max_chunk_tokens: int) -> str:
+    def read(self, chunk_size: int, chunker_cls: type, max_chunk_tokens: int) -> str:
         def get_text():
             try:
                 from unstructured.partition.auto import partition
@@ -29,7 +28,7 @@ class UnstructuredDocument(Document):
 
                 yield text
 
-        chunker = TextChunker(
+        chunker = chunker_cls(
             self, chunk_size=chunk_size, get_text=get_text, max_chunk_tokens=max_chunk_tokens
         )
 

cognee/tasks/documents/extract_chunks_from_documents.py

@@ -5,6 +5,7 @@ from sqlalchemy import select
 from cognee.modules.data.models import Data
 from cognee.infrastructure.databases.relational import get_relational_engine
 from uuid import UUID
+from cognee.modules.chunking.TextChunker import TextChunker
 
 
 async def update_document_token_count(document_id: UUID, token_count: int) -> None:
@@ -26,7 +27,7 @@ async def extract_chunks_from_documents(
     documents: list[Document],
     max_chunk_tokens: int,
     chunk_size: int = 1024,
-    chunker="text_chunker",
+    chunker=TextChunker,
 ) -> AsyncGenerator:
     """
     Extracts chunks of data from a list of documents based on the specified chunking parameters.
@@ -38,7 +39,7 @@ async def extract_chunks_from_documents(
     for document in documents:
         document_token_count = 0
         for document_chunk in document.read(
-            chunk_size=chunk_size, chunker=chunker, max_chunk_tokens=max_chunk_tokens
+            chunk_size=chunk_size, chunker_cls=chunker, max_chunk_tokens=max_chunk_tokens
         ):
             document_token_count += document_chunk.token_count
             yield document_chunk

cognee/tests/integration/documents/AudioDocument_test.py

@@ -1,6 +1,6 @@
 import uuid
 from unittest.mock import patch
-
+from cognee.modules.chunking.TextChunker import TextChunker
 from cognee.modules.data.processing.document_types.AudioDocument import AudioDocument
 
 GROUND_TRUTH = [
@@ -34,7 +34,8 @@ def test_AudioDocument():
     )
     with patch.object(AudioDocument, "create_transcript", return_value=TEST_TEXT):
         for ground_truth, paragraph_data in zip(
-            GROUND_TRUTH, document.read(chunk_size=64, chunker="text_chunker", max_chunk_tokens=512)
+            GROUND_TRUTH,
+            document.read(chunk_size=64, chunker_cls=TextChunker, max_chunk_tokens=512),
         ):
             assert ground_truth["word_count"] == paragraph_data.word_count, (
                 f'{ground_truth["word_count"] = } != {paragraph_data.word_count = }'

cognee/tests/integration/documents/ImageDocument_test.py

@@ -1,6 +1,6 @@
 import uuid
 from unittest.mock import patch
-
+from cognee.modules.chunking.TextChunker import TextChunker
 from cognee.modules.data.processing.document_types.ImageDocument import ImageDocument
 
 GROUND_TRUTH = [
@@ -23,7 +23,8 @@ def test_ImageDocument():
     )
     with patch.object(ImageDocument, "transcribe_image", return_value=TEST_TEXT):
         for ground_truth, paragraph_data in zip(
-            GROUND_TRUTH, document.read(chunk_size=64, chunker="text_chunker", max_chunk_tokens=512)
+            GROUND_TRUTH,
+            document.read(chunk_size=64, chunker_cls=TextChunker, max_chunk_tokens=512),
         ):
             assert ground_truth["word_count"] == paragraph_data.word_count, (
                 f'{ground_truth["word_count"] = } != {paragraph_data.word_count = }'

cognee/tests/integration/documents/PdfDocument_test.py

@@ -1,6 +1,6 @@
 import os
 import uuid
-
+from cognee.modules.chunking.TextChunker import TextChunker
 from cognee.modules.data.processing.document_types.PdfDocument import PdfDocument
 
 GROUND_TRUTH = [
@@ -25,7 +25,7 @@ def test_PdfDocument():
     )
 
     for ground_truth, paragraph_data in zip(
-        GROUND_TRUTH, document.read(chunk_size=1024, chunker="text_chunker", max_chunk_tokens=2048)
+        GROUND_TRUTH, document.read(chunk_size=1024, chunker_cls=TextChunker, max_chunk_tokens=2048)
     ):
         assert ground_truth["word_count"] == paragraph_data.word_count, (
             f'{ground_truth["word_count"] = } != {paragraph_data.word_count = }'

cognee/tests/integration/documents/TextDocument_test.py

@@ -2,7 +2,7 @@ import os
 import uuid
 
 import pytest
-
+from cognee.modules.chunking.TextChunker import TextChunker
 from cognee.modules.data.processing.document_types.TextDocument import TextDocument
 
 GROUND_TRUTH = {
@@ -38,7 +38,7 @@ def test_TextDocument(input_file, chunk_size):
 
     for ground_truth, paragraph_data in zip(
         GROUND_TRUTH[input_file],
-        document.read(chunk_size=chunk_size, chunker="text_chunker", max_chunk_tokens=1024),
+        document.read(chunk_size=chunk_size, chunker_cls=TextChunker, max_chunk_tokens=1024),
     ):
         assert ground_truth["word_count"] == paragraph_data.word_count, (
             f'{ground_truth["word_count"] = } != {paragraph_data.word_count = }'

cognee/tests/integration/documents/UnstructuredDocument_test.py

@@ -1,6 +1,6 @@
 import os
 import uuid
-
+from cognee.modules.chunking.TextChunker import TextChunker
 from cognee.modules.data.processing.document_types.UnstructuredDocument import UnstructuredDocument
 
 
@@ -69,7 +69,7 @@ def test_UnstructuredDocument():
 
     # Test PPTX
     for paragraph_data in pptx_document.read(
-        chunk_size=1024, chunker="text_chunker", max_chunk_tokens=1024
+        chunk_size=1024, chunker_cls=TextChunker, max_chunk_tokens=1024
     ):
         assert 19 == paragraph_data.word_count, f" 19 != {paragraph_data.word_count = }"
         assert 104 == len(paragraph_data.text), f" 104 != {len(paragraph_data.text) = }"
@@ -79,7 +79,7 @@ def test_UnstructuredDocument():
 
     # Test DOCX
     for paragraph_data in docx_document.read(
-        chunk_size=1024, chunker="text_chunker", max_chunk_tokens=1024
+        chunk_size=1024, chunker_cls=TextChunker, max_chunk_tokens=1024
     ):
         assert 16 == paragraph_data.word_count, f" 16 != {paragraph_data.word_count = }"
         assert 145 == len(paragraph_data.text), f" 145 != {len(paragraph_data.text) = }"
@@ -89,7 +89,7 @@ def test_UnstructuredDocument():
 
     # TEST CSV
     for paragraph_data in csv_document.read(
-        chunk_size=1024, chunker="text_chunker", max_chunk_tokens=1024
+        chunk_size=1024, chunker_cls=TextChunker, max_chunk_tokens=1024
     ):
         assert 15 == paragraph_data.word_count, f" 15 != {paragraph_data.word_count = }"
         assert "A A A A A A A A A,A A A A A A,A A" == paragraph_data.text, (
@@ -101,7 +101,7 @@ def test_UnstructuredDocument():
 
     # Test XLSX
     for paragraph_data in xlsx_document.read(
-        chunk_size=1024, chunker="text_chunker", max_chunk_tokens=1024
+        chunk_size=1024, chunker_cls=TextChunker, max_chunk_tokens=1024
     ):
         assert 36 == paragraph_data.word_count, f" 36 != {paragraph_data.word_count = }"
         assert 171 == len(paragraph_data.text), f" 171 != {len(paragraph_data.text) = }"