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a9197d11ee
- Keeps processing in different flows separate so that data can go to different stores / collections etc. - Potentially supports different processing flows - Tidies the processing API with common base-classes for e.g. LLMs, and automatic configuration of 'clients' to use the right queue names in a flow
83 lines
2 KiB
Python
Executable file
83 lines
2 KiB
Python
Executable file
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"""
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Simple decoder, accepts PDF documents on input, outputs pages from the
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PDF document as text as separate output objects.
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"""
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import tempfile
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import base64
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import pytesseract
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from pdf2image import convert_from_bytes
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from ... schema import Document, TextDocument, Metadata
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from ... schema import document_ingest_queue, text_ingest_queue
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from ... log_level import LogLevel
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from ... base import ConsumerProducer
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module = "ocr"
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default_input_queue = document_ingest_queue
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default_output_queue = text_ingest_queue
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default_subscriber = module
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class Processor(ConsumerProducer):
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def __init__(self, **params):
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input_queue = params.get("input_queue", default_input_queue)
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output_queue = params.get("output_queue", default_output_queue)
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subscriber = params.get("subscriber", default_subscriber)
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super(Processor, self).__init__(
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**params | {
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"input_queue": input_queue,
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"output_queue": output_queue,
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"subscriber": subscriber,
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"input_schema": Document,
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"output_schema": TextDocument,
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}
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)
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print("PDF OCR inited")
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async def handle(self, msg):
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print("PDF message received")
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v = msg.value()
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print(f"Decoding {v.metadata.id}...", flush=True)
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blob = base64.b64decode(v.data)
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pages = convert_from_bytes(blob)
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for ix, page in enumerate(pages):
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try:
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text = pytesseract.image_to_string(page, lang='eng')
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except Exception as e:
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print(f"Page did not OCR: {e}")
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continue
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r = TextDocument(
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metadata=v.metadata,
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text=text.encode("utf-8"),
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)
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await self.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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ConsumerProducer.add_args(
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parser, default_input_queue, default_subscriber,
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default_output_queue,
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)
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def run():
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Processor.launch(module, __doc__)
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