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110 lines
2.8 KiB
Python
Executable file
110 lines
2.8 KiB
Python
Executable file
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"""
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Simple decoder, accepts text documents on input, outputs chunks from the
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as text as separate output objects.
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"""
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from langchain_text_splitters import RecursiveCharacterTextSplitter
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from prometheus_client import Histogram
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from ... schema import TextDocument, Chunk, Metadata
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from ... schema import text_ingest_queue, chunk_ingest_queue
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from ... log_level import LogLevel
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from ... base import FlowProcessor
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module = "chunker"
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default_subscriber = module
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class Processor(FlowProcessor):
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def __init__(self, **params):
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id = params.get("id")
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subscriber = params.get("subscriber", default_subscriber)
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chunk_size = params.get("chunk_size", 2000)
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chunk_overlap = params.get("chunk_overlap", 100)
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super(Processor, self).__init__(
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**params | {
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"subscriber": subscriber,
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}
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)
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if not hasattr(__class__, "chunk_metric"):
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__class__.chunk_metric = Histogram(
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'chunk_size', 'Chunk size',
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["id", "flow"],
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buckets=[100, 160, 250, 400, 650, 1000, 1600,
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2500, 4000, 6400, 10000, 16000]
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)
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self.text_splitter = RecursiveCharacterTextSplitter(
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chunk_size=chunk_size,
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chunk_overlap=chunk_overlap,
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length_function=len,
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is_separator_regex=False,
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)
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self.register_consumer(
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name = "input",
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schema = TextDocument,
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handler = self.on_message,
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)
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self.register_producer(
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name = "output",
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schema = Chunk,
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)
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print("Chunker initialised", flush=True)
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async def on_message(self, msg, consumer):
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v = msg.value()
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print(f"Chunking {v.metadata.id}...", flush=True)
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texts = self.text_splitter.create_documents(
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[v.text.decode("utf-8")]
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)
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for ix, chunk in enumerate(texts):
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print("Chunk", len(chunk.page_content), flush=True)
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r = Chunk(
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metadata=v.metadata,
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chunk=chunk.page_content.encode("utf-8"),
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)
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__class__.chunk_metric.labels(
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id=consumer.id, flow=consumer.flow
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).observe(len(chunk.page_content))
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await consumer.q["output"].send(r)
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print("Done.", flush=True)
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@staticmethod
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def add_args(parser):
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FlowProcessor.add_args(parser, default_subscriber)
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parser.add_argument(
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'-z', '--chunk-size',
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type=int,
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default=2000,
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help=f'Chunk size (default: 2000)'
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)
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parser.add_argument(
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'-v', '--chunk-overlap',
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type=int,
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default=100,
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help=f'Chunk overlap (default: 100)'
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)
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def run():
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Processor.launch(module, __doc__)
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