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"""
This module contains the `DocumentParsingPipe` class, which is responsible for parsing incoming documents into plaintext.
"""
import asyncio
import logging
import time
import uuid
from typing import AsyncGenerator, Optional, Union
from r2r.base import (
AsyncParser,
AsyncState,
Document,
DocumentType,
Extraction,
ExtractionType,
KVLoggingSingleton,
PipeType,
generate_id_from_label,
)
from r2r.base.abstractions.exception import R2RDocumentProcessingError
from r2r.base.pipes.base_pipe import AsyncPipe
from r2r.parsers.media.audio_parser import AudioParser
from r2r.parsers.media.docx_parser import DOCXParser
from r2r.parsers.media.img_parser import ImageParser
from r2r.parsers.media.movie_parser import MovieParser
from r2r.parsers.media.pdf_parser import PDFParser
from r2r.parsers.media.ppt_parser import PPTParser
from r2r.parsers.structured.csv_parser import CSVParser
from r2r.parsers.structured.json_parser import JSONParser
from r2r.parsers.structured.xlsx_parser import XLSXParser
from r2r.parsers.text.html_parser import HTMLParser
from r2r.parsers.text.md_parser import MDParser
from r2r.parsers.text.text_parser import TextParser
logger = logging.getLogger(__name__)
class ParsingPipe(AsyncPipe):
"""
Processes incoming documents into plaintext based on their data type.
Supports TXT, JSON, HTML, and PDF formats.
"""
class Input(AsyncPipe.Input):
message: AsyncGenerator[Document, None]
AVAILABLE_PARSERS = {
DocumentType.CSV: CSVParser,
DocumentType.DOCX: DOCXParser,
DocumentType.HTML: HTMLParser,
DocumentType.JSON: JSONParser,
DocumentType.MD: MDParser,
DocumentType.PDF: PDFParser,
DocumentType.PPTX: PPTParser,
DocumentType.TXT: TextParser,
DocumentType.XLSX: XLSXParser,
DocumentType.GIF: ImageParser,
DocumentType.JPEG: ImageParser,
DocumentType.JPG: ImageParser,
DocumentType.PNG: ImageParser,
DocumentType.SVG: ImageParser,
DocumentType.MP3: AudioParser,
DocumentType.MP4: MovieParser,
}
IMAGE_TYPES = {
DocumentType.GIF,
DocumentType.JPG,
DocumentType.JPEG,
DocumentType.PNG,
DocumentType.SVG,
}
def __init__(
self,
excluded_parsers: list[DocumentType],
override_parsers: Optional[dict[DocumentType, AsyncParser]] = None,
pipe_logger: Optional[KVLoggingSingleton] = None,
type: PipeType = PipeType.INGESTOR,
config: Optional[AsyncPipe.PipeConfig] = None,
*args,
**kwargs,
):
super().__init__(
pipe_logger=pipe_logger,
type=type,
config=config
or AsyncPipe.PipeConfig(name="default_document_parsing_pipe"),
*args,
**kwargs,
)
self.parsers = {}
if not override_parsers:
override_parsers = {}
# Apply overrides if specified
for doc_type, parser in override_parsers.items():
self.parsers[doc_type] = parser
for doc_type, parser_info in self.AVAILABLE_PARSERS.items():
if (
doc_type not in excluded_parsers
and doc_type not in self.parsers
):
self.parsers[doc_type] = parser_info()
@property
def supported_types(self) -> list[str]:
"""
Lists the data types supported by the pipe.
"""
return [entry_type for entry_type in DocumentType]
async def _parse(
self,
document: Document,
run_id: uuid.UUID,
version: str,
) -> AsyncGenerator[Union[R2RDocumentProcessingError, Extraction], None]:
if document.type not in self.parsers:
yield R2RDocumentProcessingError(
document_id=document.id,
error_message=f"Parser for {document.type} not found in `ParsingPipe`.",
)
return
parser = self.parsers[document.type]
texts = parser.ingest(document.data)
extraction_type = ExtractionType.TXT
t0 = time.time()
if document.type in self.IMAGE_TYPES:
extraction_type = ExtractionType.IMG
document.metadata["image_type"] = document.type.value
# SAVE IMAGE DATA
# try:
# import base64
# sanitized_data = base64.b64encode(document.data).decode('utf-8')
# except Exception as e:
# sanitized_data = document.data
# document.metadata["image_data"] = sanitized_data
elif document.type == DocumentType.MP4:
extraction_type = ExtractionType.MOV
document.metadata["audio_type"] = document.type.value
iteration = 0
async for text in texts:
extraction_id = generate_id_from_label(
f"{document.id}-{iteration}-{version}"
)
document.metadata["version"] = version
extraction = Extraction(
id=extraction_id,
data=text,
metadata=document.metadata,
document_id=document.id,
type=extraction_type,
)
yield extraction
# TODO - Add settings to enable extraction logging
# extraction_dict = extraction.dict()
# await self.enqueue_log(
# run_id=run_id,
# key="extraction",
# value=json.dumps(
# {
# "data": extraction_dict["data"],
# "document_id": str(extraction_dict["document_id"]),
# "extraction_id": str(extraction_dict["id"]),
# }
# ),
# )
iteration += 1
logger.debug(
f"Parsed document with id={document.id}, title={document.metadata.get('title', None)}, user_id={document.metadata.get('user_id', None)}, metadata={document.metadata} into {iteration} extractions in t={time.time() - t0:.2f} seconds."
)
async def _run_logic(
self,
input: Input,
state: AsyncState,
run_id: uuid.UUID,
versions: Optional[list[str]] = None,
*args,
**kwargs,
) -> AsyncGenerator[Extraction, None]:
parse_tasks = []
iteration = 0
async for document in input.message:
version = versions[iteration] if versions else "v0"
iteration += 1
parse_tasks.append(
self._handle_parse_task(document, version, run_id)
)
# Await all tasks and yield results concurrently
for parse_task in asyncio.as_completed(parse_tasks):
for extraction in await parse_task:
yield extraction
async def _handle_parse_task(
self, document: Document, version: str, run_id: uuid.UUID
) -> AsyncGenerator[Extraction, None]:
extractions = []
async for extraction in self._parse(document, run_id, version):
extractions.append(extraction)
return extractions
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