chore: Update extraction strategy to support GPU, MPS, and CPU, add batch processing for CPU devices
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@@ -16,7 +16,7 @@ class ChunkingStrategy(ABC):
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# Regex-based chunking
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class RegexChunking(ChunkingStrategy):
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def __init__(self, patterns=None):
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def __init__(self, patterns=None, **kwargs):
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if patterns is None:
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patterns = [r'\n\n'] # Default split pattern
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self.patterns = patterns
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@@ -32,7 +32,7 @@ class RegexChunking(ChunkingStrategy):
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# NLP-based sentence chunking
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class NlpSentenceChunking(ChunkingStrategy):
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def __init__(self):
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def __init__(self, **kwargs):
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load_nltk_punkt()
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pass
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@@ -52,7 +52,7 @@ class NlpSentenceChunking(ChunkingStrategy):
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# Topic-based segmentation using TextTiling
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class TopicSegmentationChunking(ChunkingStrategy):
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def __init__(self, num_keywords=3):
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def __init__(self, num_keywords=3, **kwargs):
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import nltk as nl
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self.tokenizer = nl.toknize.TextTilingTokenizer()
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self.num_keywords = num_keywords
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@@ -82,7 +82,7 @@ class TopicSegmentationChunking(ChunkingStrategy):
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# Fixed-length word chunks
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class FixedLengthWordChunking(ChunkingStrategy):
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def __init__(self, chunk_size=100):
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def __init__(self, chunk_size=100, **kwargs):
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self.chunk_size = chunk_size
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def chunk(self, text: str) -> list:
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@@ -91,7 +91,7 @@ class FixedLengthWordChunking(ChunkingStrategy):
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# Sliding window chunking
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class SlidingWindowChunking(ChunkingStrategy):
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def __init__(self, window_size=100, step=50):
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def __init__(self, window_size=100, step=50, **kwargs):
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self.window_size = window_size
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self.step = step
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