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Source code for langchain.document_loaders.mediawikidump import logging from pathlib import Path from typing import List, Optional, Sequence, Union from langchain.docstore.document import Document from langchain.document_loaders.base import BaseLoader logger = logging.getLogger(__name__) [docs]class MWDumpLoader(BaseLo...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/mediawikidump.html
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""" [docs] def __init__( self, file_path: Union[str, Path], encoding: Optional[str] = "utf8", namespaces: Optional[Sequence[int]] = None, skip_redirects: Optional[bool] = False, stop_on_error: Optional[bool] = True, ): self.file_path = file_path if isinstan...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/mediawikidump.html
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except Exception as e: logger.error("Parsing error: {}".format(e)) if self.stop_on_error: raise e else: continue return docs
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/mediawikidump.html
b3d242302893-0
Source code for langchain.document_loaders.imsdb from typing import List from langchain.docstore.document import Document from langchain.document_loaders.web_base import WebBaseLoader [docs]class IMSDbLoader(WebBaseLoader): """Load `IMSDb` webpages.""" [docs] def load(self) -> List[Document]: """Load web...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/imsdb.html
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Source code for langchain.document_loaders.notebook """Loads .ipynb notebook files.""" import json from pathlib import Path from typing import Any, List from langchain.docstore.document import Document from langchain.document_loaders.base import BaseLoader [docs]def concatenate_cells( cell: dict, include_outputs: b...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/notebook.html
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output = output[0]["text"] min_output = min(max_output_length, len(output)) return ( f"'{cell_type}' cell: '{source}'\n with " f"output: '{output[:min_output]}'\n\n" ) else: return f"'{cell_type}' cell: '{source}'\n\n" return "" [docs]d...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/notebook.html
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Defaults to False. """ self.file_path = path self.include_outputs = include_outputs self.max_output_length = max_output_length self.remove_newline = remove_newline self.traceback = traceback [docs] def load( self, ) -> List[Document]: """Load docume...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/notebook.html
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Source code for langchain.document_loaders.web_base """Web base loader class.""" import asyncio import logging import warnings from typing import Any, Dict, Iterator, List, Optional, Sequence, Union import aiohttp import requests from langchain.docstore.document import Document from langchain.document_loaders.base impo...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/web_base.html
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verify_ssl: bool = True, proxies: Optional[dict] = None, continue_on_failure: bool = False, autoset_encoding: bool = True, encoding: Optional[str] = None, web_paths: Sequence[str] = (), requests_per_second: int = 2, default_parser: str = "html.parser", req...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/web_base.html
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f" web_paths must be Sequence[str] got ({type(web_paths)})" ) self.requests_per_second = requests_per_second self.default_parser = default_parser self.requests_kwargs = requests_kwargs or {} self.raise_for_status = raise_for_status self.bs_get_text_kwargs = bs_get_tex...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/web_base.html
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async with session.get( url, headers=self.session.headers, ssl=None if self.session.verify else False, ) as response: return await response.text() except aiohttp.ClientConnectionError as e...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/web_base.html
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) except ImportError: warnings.warn("For better logging of progress, `pip install tqdm`") return await asyncio.gather(*tasks) @staticmethod def _check_parser(parser: str) -> None: """Check that parser is valid for bs4.""" valid_parsers = ["html.parser", "lxml", "x...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/web_base.html
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if self.raise_for_status: html_doc.raise_for_status() if self.encoding is not None: html_doc.encoding = self.encoding elif self.autoset_encoding: html_doc.encoding = html_doc.apparent_encoding return BeautifulSoup(html_doc.text, parser, **(bs_kwargs or {})) [d...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/web_base.html
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Source code for langchain.document_loaders.text import logging from typing import List, Optional from langchain.docstore.document import Document from langchain.document_loaders.base import BaseLoader from langchain.document_loaders.helpers import detect_file_encodings logger = logging.getLogger(__name__) [docs]class T...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/text.html
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except Exception as e: raise RuntimeError(f"Error loading {self.file_path}") from e metadata = {"source": self.file_path} return [Document(page_content=text, metadata=metadata)]
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/text.html
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Source code for langchain.document_loaders.wikipedia from typing import List, Optional from langchain.docstore.document import Document from langchain.document_loaders.base import BaseLoader from langchain.utilities.wikipedia import WikipediaAPIWrapper [docs]class WikipediaLoader(BaseLoader): """Load from `Wikipedi...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/wikipedia.html
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Loads the query result from Wikipedia into a list of Documents. Returns: List[Document]: A list of Document objects representing the loaded Wikipedia pages. """ client = WikipediaAPIWrapper( lang=self.lang, top_k_results=self.load_max_docs, ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/wikipedia.html
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Source code for langchain.document_loaders.powerpoint import os from typing import List from langchain.document_loaders.unstructured import UnstructuredFileLoader [docs]class UnstructuredPowerPointLoader(UnstructuredFileLoader): """Load `Microsoft PowerPoint` files using `Unstructured`. Works with both .ppt and...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/powerpoint.html
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try: import magic # noqa: F401 is_ppt = detect_filetype(self.file_path) == FileType.PPT except ImportError: _, extension = os.path.splitext(str(self.file_path)) is_ppt = extension == ".ppt" if is_ppt and unstructured_version < (0, 4, 11): rais...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/powerpoint.html
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Source code for langchain.document_loaders.assemblyai from __future__ import annotations from enum import Enum from typing import TYPE_CHECKING, List, Optional from langchain.docstore.document import Document from langchain.document_loaders.base import BaseLoader if TYPE_CHECKING: import assemblyai [docs]class Tran...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/assemblyai.html
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config: Optional[assemblyai.TranscriptionConfig] = None, api_key: Optional[str] = None, ): """ Initializes the AssemblyAI AudioTranscriptLoader. Args: file_path: An URL or a local file path. transcript_format: Transcript format to use. See clas...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/assemblyai.html
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sentences = transcript.get_sentences() return [ Document(page_content=s.text, metadata=s.dict(exclude={"text"})) for s in sentences ] elif self.transcript_format == TranscriptFormat.PARAGRAPHS: paragraphs = transcript.get_paragraphs() ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/assemblyai.html
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Source code for langchain.document_loaders.acreom import re from pathlib import Path from typing import Iterator, List from langchain.docstore.document import Document from langchain.document_loaders.base import BaseLoader [docs]class AcreomLoader(BaseLoader): """Load `acreom` vault from a directory.""" FRONT_M...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/acreom.html
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if not self.collect_metadata: return content return self.FRONT_MATTER_REGEX.sub("", content) def _process_acreom_content(self, content: str) -> str: # remove acreom specific elements from content that # do not contribute to the context of current document content = re.sub...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/acreom.html
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Source code for langchain.document_loaders.hugging_face_dataset from typing import Iterator, List, Mapping, Optional, Sequence, Union from langchain.docstore.document import Document from langchain.document_loaders.base import BaseLoader [docs]class HuggingFaceDatasetLoader(BaseLoader): """Load from `Hugging Face H...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/hugging_face_dataset.html
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save_infos: Save the dataset information (checksums/size/splits/...). Default is False. use_auth_token: Bearer token for remote files on the Dataset Hub. num_proc: Number of processes. """ self.path = path self.page_content_column = page_content_column ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/hugging_face_dataset.html
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Source code for langchain.document_loaders.duckdb_loader from typing import Dict, List, Optional, cast from langchain.docstore.document import Document from langchain.document_loaders.base import BaseLoader [docs]class DuckDBLoader(BaseLoader): """Load from `DuckDB`. Each document represents one row of the resu...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/duckdb_loader.html
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[docs] def load(self) -> List[Document]: try: import duckdb except ImportError: raise ImportError( "Could not import duckdb python package. " "Please install it with `pip install duckdb`." ) docs = [] with duckdb.conn...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/duckdb_loader.html
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Source code for langchain.document_loaders.browserless from typing import Iterator, List, Union import requests from langchain.docstore.document import Document from langchain.document_loaders.base import BaseLoader [docs]class BrowserlessLoader(BaseLoader): """Load webpages with `Browserless` /content endpoint."""...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/browserless.html
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metadata={ "source": url, }, ) [docs] def load(self) -> List[Document]: """Load Documents from URLs.""" return list(self.lazy_load())
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/browserless.html
fa8c8756a37b-0
Source code for langchain.document_loaders.trello from __future__ import annotations from typing import TYPE_CHECKING, Any, List, Literal, Optional, Tuple from langchain.docstore.document import Document from langchain.document_loaders.base import BaseLoader from langchain.utils import get_from_env if TYPE_CHECKING: ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/trello.html
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self.include_card_name = include_card_name self.include_comments = include_comments self.include_checklist = include_checklist self.extra_metadata = extra_metadata self.card_filter = card_filter [docs] @classmethod def from_credentials( cls, board_name: str, ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/trello.html
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token = token or get_from_env("token", "TRELLO_TOKEN") client = TrelloClient(api_key=api_key, token=token) return cls(client, board_name, **kwargs) [docs] def load(self) -> List[Document]: """Loads all cards from the specified Trello board. You can filter the cards, metadata and text ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/trello.html
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if self.include_card_name: text_content = card.name + "\n" if card.description.strip(): text_content += BeautifulSoup(card.description, "lxml").get_text() if self.include_checklist: # Get all the checklist items on the card for checklist in card.checklists...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/trello.html
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Source code for langchain.document_loaders.parsers.pdf """Module contains common parsers for PDFs.""" from __future__ import annotations from typing import TYPE_CHECKING, Any, Iterator, Mapping, Optional, Sequence, Union from urllib.parse import urlparse from langchain.document_loaders.base import BaseBlobParser from l...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/pdf.html
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[docs]class PyMuPDFParser(BaseBlobParser): """Parse `PDF` using `PyMuPDF`.""" [docs] def __init__(self, text_kwargs: Optional[Mapping[str, Any]] = None) -> None: """Initialize the parser. Args: text_kwargs: Keyword arguments to pass to ``fitz.Page.get_text()``. """ sel...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/pdf.html
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" `pip install pypdfium2`" ) [docs] def lazy_parse(self, blob: Blob) -> Iterator[Document]: """Lazily parse the blob.""" import pypdfium2 # pypdfium2 is really finicky with respect to closing things, # if done incorrectly creates seg faults. with blob.as_bytes_io()...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/pdf.html
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doc = pdfplumber.open(file_path) # open document yield from [ Document( page_content=self._process_page_content(page), metadata=dict( { "source": blob.source, "file_path":...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/pdf.html
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self.tc = tc if textract_features is not None: self.textract_features = [ tc.Textract_Features(f) for f in textract_features ] else: self.textract_features = [] except ImportError: raise ImportError( ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/pdf.html
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) else: textract_response_json = self.tc.call_textract( input_document=blob.as_bytes(), features=self.textract_features, call_mode=self.tc.Textract_Call_Mode.FORCE_SYNC, boto3_textract_client=self.boto3_textract_client, ) ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/pdf.html
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"""Lazily parse the blob.""" with blob.as_bytes_io() as file_obj: poller = self.client.begin_analyze_document(self.model, file_obj) result = poller.result() docs = self._generate_docs(blob, result) yield from docs
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/pdf.html
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Source code for langchain.document_loaders.parsers.registry """Module includes a registry of default parser configurations.""" from langchain.document_loaders.base import BaseBlobParser from langchain.document_loaders.parsers.generic import MimeTypeBasedParser from langchain.document_loaders.parsers.msword import MsWor...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/registry.html
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Source code for langchain.document_loaders.parsers.audio import logging import time from typing import Dict, Iterator, Optional, Tuple from langchain.document_loaders.base import BaseBlobParser from langchain.document_loaders.blob_loaders import Blob from langchain.schema import Document logger = logging.getLogger(__na...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/audio.html
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# Audio chunk chunk = audio[i : i + chunk_duration_ms] file_obj = io.BytesIO(chunk.export(format="mp3").read()) if blob.source is not None: file_obj.name = blob.source + f"_part_{split_number}.mp3" else: file_obj.name = f"part_{split_number...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/audio.html
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forced_decoder_ids = WhisperProcessor.get_decoder_prompt_ids(language="french", task="transcribe") forced_decoder_ids = WhisperProcessor.get_decoder_prompt_ids(language="french", task="translate") """ [docs] def __init__( self, device: str = "0", lang_model: Opti...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/audio.html
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# check GPU memory and select automatically the model mem = torch.cuda.get_device_properties(self.device).total_memory / ( 1024**2 ) if mem < 5000: rec_model = "openai/whisper-base" elif mem < 7000: ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/audio.html
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from pydub import AudioSegment except ImportError: raise ImportError( "pydub package not found, please install it with `pip install pydub`" ) try: import librosa except ImportError: raise ImportError( "librosa packag...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/audio.html
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Source code for langchain.document_loaders.parsers.msword from typing import Iterator from langchain.document_loaders.base import BaseBlobParser from langchain.document_loaders.blob_loaders import Blob from langchain.schema import Document [docs]class MsWordParser(BaseBlobParser): [docs] def lazy_parse(self, blob: B...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/msword.html
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Source code for langchain.document_loaders.parsers.txt """Module for parsing text files..""" from typing import Iterator from langchain.document_loaders.base import BaseBlobParser from langchain.document_loaders.blob_loaders import Blob from langchain.schema import Document [docs]class TextParser(BaseBlobParser): "...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/txt.html
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Source code for langchain.document_loaders.parsers.grobid import logging from typing import Dict, Iterator, List, Union import requests from langchain.docstore.document import Document from langchain.document_loaders.base import BaseBlobParser from langchain.document_loaders.blob_loaders import Blob logger = logging.ge...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/grobid.html
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chunks = [] for section in sections: sect = section.find("head") if sect is not None: for i, paragraph in enumerate(section.find_all("p")): chunk_bboxes = [] paragraph_text = [] for i, sentence in enumerate(parag...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/grobid.html
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"pages": (fpage, lpage), } chunks.append(paragraph_dict) yield from [ Document( page_content=chunk["text"], metadata=dict( { "text": str(chunk["text"]), ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/grobid.html
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xml_data = None if xml_data is None: return iter([]) else: return self.process_xml(file_path, xml_data, self.segment_sentences)
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/grobid.html
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Source code for langchain.document_loaders.parsers.generic """Code for generic / auxiliary parsers. This module contains some logic to help assemble more sophisticated parsers. """ from typing import Iterator, Mapping, Optional from langchain.document_loaders.base import BaseBlobParser from langchain.document_loaders.b...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/generic.html
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""" self.handlers = handlers self.fallback_parser = fallback_parser [docs] def lazy_parse(self, blob: Blob) -> Iterator[Document]: """Load documents from a blob.""" mimetype = blob.mimetype if mimetype is None: raise ValueError(f"{blob} does not have a mimetype.") ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/generic.html
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Source code for langchain.document_loaders.parsers.docai """Module contains a PDF parser based on DocAI from Google Cloud. You need to install two libraries to use this parser: pip install google-cloud-documentai pip install google-cloud-documentai-toolbox """ import logging import time from dataclasses import dataclas...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/docai.html
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"You should provide either a client or a location but not both " "of them." ) if not client and not location: raise ValueError( "You must specify either a client or a location to instantiate " "a client." ) self._gcs_out...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/docai.html
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Args: blobs: a list of blobs to parse gcs_output_path: a path on GCS to store parsing results timeout_sec: a timeout to wait for DocAI to complete, in seconds check_in_interval_sec: an interval to wait until next check whether parsing operations have been ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/docai.html
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) logger.debug(".") results = self.get_results(operations=operations) yield from self.parse_from_results(results) [docs] def parse_from_results( self, results: List[DocAIParsingResults] ) -> Iterator[Document]: try: from google.cloud.documentai_toolbox.wrap...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/docai.html
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" `pip install gapic-google-longrunning`" ) operations = [] for name in operation_names: request = GetOperationRequest(name=name) operations.append(self._client.get_operation(request=request)) return operations [docs] def is_running(self, operations: List["...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/docai.html
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raise ValueError("Processor name is not defined, aborting!") output_path = gcs_output_path if gcs_output_path else self._gcs_output_path if output_path is None: raise ValueError("An output path on GCS should be provided!") operations = [] for batch in batch_iterate(size=batch...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/docai.html
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except ImportError: raise ImportError( "documentai package not found, please install it with" " `pip install google-cloud-documentai`" ) results = [] for op in operations: if isinstance(op.metadata, BatchProcessMetadata): ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/docai.html
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Source code for langchain.document_loaders.parsers.language.code_segmenter from abc import ABC, abstractmethod from typing import List [docs]class CodeSegmenter(ABC): """Abstract class for the code segmenter.""" [docs] def __init__(self, code: str): self.code = code [docs] def is_valid(self) -> bool: ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/language/code_segmenter.html
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Source code for langchain.document_loaders.parsers.language.language_parser from typing import Any, Dict, Iterator, Optional from langchain.docstore.document import Document from langchain.document_loaders.base import BaseBlobParser from langchain.document_loaders.blob_loaders import Blob from langchain.document_loader...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/language/language_parser.html
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Example instantiations to manually select the language: .. code-block:: python from langchain.text_splitter import Language loader = GenericLoader.from_filesystem( "./code", glob="**/*", suffixes=[".py"], parser=LanguagePars...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/language/language_parser.html
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"language": language, }, ) return self.Segmenter = LANGUAGE_SEGMENTERS[language] segmenter = self.Segmenter(blob.as_string()) if not segmenter.is_valid(): yield Document( page_content=code, metadata={ ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/language/language_parser.html
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Source code for langchain.document_loaders.parsers.language.python import ast from typing import Any, List from langchain.document_loaders.parsers.language.code_segmenter import CodeSegmenter [docs]class PythonSegmenter(CodeSegmenter): """Code segmenter for `Python`.""" [docs] def __init__(self, code: str): ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/language/python.html
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simplified_lines[line_num] = None # type: ignore return "\n".join(line for line in simplified_lines if line is not None)
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/language/python.html
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Source code for langchain.document_loaders.parsers.language.javascript from typing import Any, List from langchain.document_loaders.parsers.language.code_segmenter import CodeSegmenter [docs]class JavaScriptSegmenter(CodeSegmenter): """Code segmenter for JavaScript.""" [docs] def __init__(self, code: str): ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/language/javascript.html
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for node in tree.body: if isinstance( node, (esprima.nodes.FunctionDeclaration, esprima.nodes.ClassDeclaration), ): start = node.loc.start.line - 1 simplified_lines[start] = f"// Code for: {simplified_lines[start]}" ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/language/javascript.html
e3fe7c059402-0
Source code for langchain.document_loaders.parsers.html.bs4 """Loader that uses bs4 to load HTML files, enriching metadata with page title.""" import logging from typing import Any, Dict, Iterator, Union from langchain.docstore.document import Document from langchain.document_loaders.base import BaseBlobParser from lan...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/parsers/html/bs4.html
732d15c59dc4-0
Source code for langchain.document_loaders.blob_loaders.file_system """Use to load blobs from the local file system.""" from pathlib import Path from typing import Callable, Iterable, Iterator, Optional, Sequence, TypeVar, Union from langchain.document_loaders.blob_loaders.schema import Blob, BlobLoader T = TypeVar("T"...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blob_loaders/file_system.html
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*, glob: str = "**/[!.]*", exclude: Sequence[str] = (), suffixes: Optional[Sequence[str]] = None, show_progress: bool = False, ) -> None: """Initialize with a path to directory and how to glob over it. Args: path: Path to directory to load from ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blob_loaders/file_system.html
732d15c59dc4-2
elif isinstance(path, str): _path = Path(path) else: raise TypeError(f"Expected str or Path, got {type(path)}") self.path = _path.expanduser() # Expand user to handle ~ self.glob = glob self.suffixes = set(suffixes or []) self.show_progress = show_progres...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blob_loaders/file_system.html
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Source code for langchain.document_loaders.blob_loaders.schema """Schema for Blobs and Blob Loaders. The goal is to facilitate decoupling of content loading from content parsing code. In addition, content loading code should provide a lazy loading interface by default. """ from __future__ import annotations import cont...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blob_loaders/schema.html
59d6cb26dd27-1
return str(self.path) if self.path else None @root_validator(pre=True) def check_blob_is_valid(cls, values: Mapping[str, Any]) -> Mapping[str, Any]: """Verify that either data or path is provided.""" if "data" not in values and "path" not in values: raise ValueError("Either data or p...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blob_loaders/schema.html
59d6cb26dd27-2
yield f else: raise NotImplementedError(f"Unable to convert blob {self}") [docs] @classmethod def from_path( cls, path: PathLike, *, encoding: str = "utf-8", mime_type: Optional[str] = None, guess_type: bool = True, ) -> Blob: """Loa...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blob_loaders/schema.html
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mime_type: if provided, will be set as the mime-type of the data path: if provided, will be set as the source from which the data came Returns: Blob instance """ return cls(data=data, mimetype=mime_type, encoding=encoding, path=path) def __repr__(self) -> str: ...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blob_loaders/schema.html
72d1bb8e609a-0
Source code for langchain.document_loaders.blob_loaders.youtube_audio from typing import Iterable, List from langchain.document_loaders.blob_loaders import FileSystemBlobLoader from langchain.document_loaders.blob_loaders.schema import Blob, BlobLoader [docs]class YoutubeAudioLoader(BlobLoader): """Load YouTube url...
https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blob_loaders/youtube_audio.html
b8058e01c197-0
Source code for langchain.smith.evaluation.string_run_evaluator """Run evaluator wrapper for string evaluators.""" from __future__ import annotations from abc import abstractmethod from typing import Any, Dict, List, Optional from langsmith import EvaluationResult, RunEvaluator from langsmith.schemas import DataType, E...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/string_run_evaluator.html
b8058e01c197-1
return self.map(run) [docs]class LLMStringRunMapper(StringRunMapper): """Extract items to evaluate from the run object.""" [docs] def serialize_chat_messages(self, messages: List[Dict]) -> str: """Extract the input messages from the run.""" if isinstance(messages, list) and messages: ...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/string_run_evaluator.html
b8058e01c197-2
first_generation: Dict = generations[0] if isinstance(first_generation, list): # Runs from Tracer have generations as a list of lists of dicts # Whereas Runs from the API have a list of dicts first_generation = first_generation[0] if "message" in first_generation: ...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/string_run_evaluator.html
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"""The key from the model Run's inputs to use as the eval input. If not provided, will use the only input key or raise an error if there are multiple.""" prediction_key: Optional[str] = None """The key from the model Run's outputs to use as the eval prediction. If not provided, will use the only out...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/string_run_evaluator.html
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available_keys = ", ".join(run.outputs.keys()) raise ValueError( f"Run with ID {run.id} doesn't have the expected prediction key" f" '{self.prediction_key}'. Available prediction keys in this Run are:" f" {available_keys}. Adjust the evaluator's prediction_key...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/string_run_evaluator.html
b8058e01c197-5
"""Maps the Example, or dataset row to a dictionary.""" if not example.outputs: raise ValueError( f"Example {example.id} has no outputs to use as a reference." ) if self.reference_key is None: if len(example.outputs) > 1: raise ValueErr...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/string_run_evaluator.html
b8058e01c197-6
"""The name of the evaluation metric.""" string_evaluator: StringEvaluator """The evaluation chain.""" @property def input_keys(self) -> List[str]: return ["run", "example"] @property def output_keys(self) -> List[str]: return ["feedback"] def _prepare_input(self, inputs: Dic...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/string_run_evaluator.html
b8058e01c197-7
"""Call the evaluation chain.""" evaluate_strings_inputs = self._prepare_input(inputs) _run_manager = run_manager or CallbackManagerForChainRun.get_noop_manager() callbacks = _run_manager.get_child() chain_output = self.string_evaluator.evaluate_strings( **evaluate_strings_in...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/string_run_evaluator.html
b8058e01c197-8
return EvaluationResult( key=self.string_evaluator.evaluation_name, comment=f"Error evaluating run {run.id}: {e}", # TODO: Add run ID once we can declare it via callbacks ) [docs] async def aevaluate_run( self, run: Run, example: Optional[Example] =...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/string_run_evaluator.html
b8058e01c197-9
data_type (DataType): The type of dataset used in the run. input_key (str, optional): The key used to map the input from the run. prediction_key (str, optional): The key used to map the prediction from the run. reference_key (str, optional): The key used to map the reference from the...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/string_run_evaluator.html
b8058e01c197-10
) else: example_mapper = None return cls( name=evaluator.evaluation_name, run_mapper=run_mapper, example_mapper=example_mapper, string_evaluator=evaluator, tags=tags, )
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/string_run_evaluator.html
8b66c083e60d-0
Source code for langchain.smith.evaluation.name_generation import random adjectives = [ "abandoned", "aching", "advanced", "ample", "artistic", "back", "best", "bold", "brief", "clear", "cold", "complicated", "cooked", "crazy", "crushing", "damp", "dea...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/name_generation.html
8b66c083e60d-1
"sunny", "tart", "terrific", "timely", "unique", "upbeat", "vacant", "virtual", "warm", "weary", "whispered", "worthwhile", "yellow", ] nouns = [ "account", "acknowledgment", "address", "advertising", "airplane", "animal", "appointment", "a...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/name_generation.html
8b66c083e60d-2
"cheek", "cheese", "chef", "cherry", "chicken", "child", "church", "circle", "class", "clay", "click", "clock", "cloth", "cloud", "clove", "club", "coach", "coal", "coast", "coat", "cod", "coffee", "collar", "color", "comb",...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/name_generation.html
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"discussion", "disease", "disgust", "distance", "distribution", "division", "doctor", "dog", "door", "drain", "drawer", "dress", "drink", "driving", "dust", "ear", "earth", "edge", "education", "effect", "egg", "end", "energy", ...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/name_generation.html
8b66c083e60d-4
"group", "growth", "guide", "guitar", "hair", "hall", "hand", "harbor", "harmony", "hat", "head", "health", "heart", "heat", "hill", "history", "hobbies", "hole", "hope", "horn", "horse", "hospital", "hour", "house", "humor"...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/name_generation.html
8b66c083e60d-5
"list", "look", "loss", "love", "lunch", "machine", "man", "manager", "map", "marble", "mark", "market", "mass", "match", "meal", "measure", "meat", "meeting", "memory", "metal", "middle", "milk", "mind", "mine", "minute", ...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/name_generation.html
8b66c083e60d-6
"pear", "pen", "pencil", "person", "pest", "pet", "picture", "pie", "pin", "pipe", "pizza", "place", "plane", "plant", "plastic", "plate", "play", "pleasure", "plot", "plough", "pocket", "point", "poison", "police", "polluti...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/name_generation.html
8b66c083e60d-7
"rice", "river", "road", "roll", "room", "root", "rose", "route", "rub", "rule", "run", "sack", "sail", "salt", "sand", "scale", "scarecrow", "scarf", "scene", "scent", "school", "science", "scissors", "screw", "sea", "s...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/name_generation.html
8b66c083e60d-8
"sound", "soup", "space", "spark", "speed", "sponge", "spoon", "spray", "spring", "spy", "square", "stamp", "star", "start", "statement", "station", "steam", "steel", "stem", "step", "stew", "stick", "stitch", "stocking", "s...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/name_generation.html
8b66c083e60d-9
"toad", "toe", "tooth", "toothpaste", "touch", "town", "toy", "trade", "train", "transport", "tray", "treatment", "tree", "trick", "trip", "trouble", "trousers", "truck", "tub", "turkey", "turn", "twist", "umbrella", "uncle", ...
https://api.python.langchain.com/en/latest/_modules/langchain/smith/evaluation/name_generation.html