348610e73c
* fix: handle rate limit error coming from llm model * fix: fixes lost edges and nodes in get_graph_from_model * fix: fixes database pruning issue in pgvector (#261) * fix: cognee_demo notebook pipeline is not saving summaries --------- Co-authored-by: hajdul88 <52442977+hajdul88@users.noreply.github.com>
85 lines
3.6 KiB
Python
85 lines
3.6 KiB
Python
from uuid import uuid5, NAMESPACE_OID
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from .models.DocumentChunk import DocumentChunk
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from cognee.tasks.chunks import chunk_by_paragraph
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class TextChunker():
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document = None
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max_chunk_size: int
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chunk_index = 0
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chunk_size = 0
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def __init__(self, document, get_text: callable, chunk_size: int = 1024):
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self.document = document
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self.max_chunk_size = chunk_size
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self.get_text = get_text
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def read(self):
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paragraph_chunks = []
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for content_text in self.get_text():
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for chunk_data in chunk_by_paragraph(
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content_text,
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self.max_chunk_size,
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batch_paragraphs = True,
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):
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if self.chunk_size + chunk_data["word_count"] <= self.max_chunk_size:
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paragraph_chunks.append(chunk_data)
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self.chunk_size += chunk_data["word_count"]
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else:
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if len(paragraph_chunks) == 0:
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yield DocumentChunk(
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id = chunk_data["chunk_id"],
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text = chunk_data["text"],
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word_count = chunk_data["word_count"],
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is_part_of = self.document,
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chunk_index = self.chunk_index,
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cut_type = chunk_data["cut_type"],
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contains = [],
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_metadata = {
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"index_fields": ["text"],
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"metadata_id": self.document.metadata_id
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}
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)
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paragraph_chunks = []
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self.chunk_size = 0
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else:
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chunk_text = " ".join(chunk["text"] for chunk in paragraph_chunks)
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try:
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yield DocumentChunk(
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id = uuid5(NAMESPACE_OID, f"{str(self.document.id)}-{self.chunk_index}"),
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text = chunk_text,
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word_count = self.chunk_size,
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is_part_of = self.document,
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chunk_index = self.chunk_index,
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cut_type = paragraph_chunks[len(paragraph_chunks) - 1]["cut_type"],
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contains = [],
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_metadata = {
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"index_fields": ["text"],
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"metadata_id": self.document.metadata_id
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}
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)
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except Exception as e:
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print(e)
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paragraph_chunks = [chunk_data]
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self.chunk_size = chunk_data["word_count"]
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self.chunk_index += 1
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if len(paragraph_chunks) > 0:
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try:
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yield DocumentChunk(
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id = uuid5(NAMESPACE_OID, f"{str(self.document.id)}-{self.chunk_index}"),
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text = " ".join(chunk["text"] for chunk in paragraph_chunks),
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word_count = self.chunk_size,
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is_part_of = self.document,
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chunk_index = self.chunk_index,
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cut_type = paragraph_chunks[len(paragraph_chunks) - 1]["cut_type"],
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contains = [],
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_metadata = {
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"index_fields": ["text"],
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"metadata_id": self.document.metadata_id
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}
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)
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except Exception as e:
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print(e)
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