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import os
import re
import requests
import pysrt
from langchain_community.document_loaders import (
PyMuPDFLoader,
Docx2txtLoader,
YoutubeLoader,
WebBaseLoader,
TextLoader,
)
from langchain_community.document_loaders import UnstructuredMarkdownLoader
from llama_parse import LlamaParse
from langchain.schema import Document
import logging
from langchain.text_splitter import RecursiveCharacterTextSplitter
from ragatouille import RAGPretrainedModel
from langchain.chains import LLMChain
from langchain.llms import OpenAI
from langchain import PromptTemplate
try:
from modules.helpers import get_metadata
except:
from helpers import get_metadata
logger = logging.getLogger(__name__)
class PDFReader:
def __init__(self):
pass
def get_loader(self, pdf_path):
loader = PyMuPDFLoader(pdf_path)
return loader
def get_documents(self, loader):
return loader.load()
class FileReader:
def __init__(self):
self.pdf_reader = PDFReader()
def extract_text_from_pdf(self, pdf_path):
text = ""
with open(pdf_path, "rb") as file:
reader = PyPDF2.PdfReader(file)
num_pages = len(reader.pages)
for page_num in range(num_pages):
page = reader.pages[page_num]
text += page.extract_text()
return text
def download_pdf_from_url(self, pdf_url):
response = requests.get(pdf_url)
if response.status_code == 200:
with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as temp_file:
temp_file.write(response.content)
temp_file_path = temp_file.name
return temp_file_path
else:
print("Failed to download PDF from URL:", pdf_url)
return None
def read_pdf(self, temp_file_path: str):
loader = self.pdf_reader.get_loader(temp_file_path)
documents = self.pdf_reader.get_documents(loader)
return documents
def read_txt(self, temp_file_path: str):
loader = TextLoader(temp_file_path, autodetect_encoding=True)
return loader.load()
def read_docx(self, temp_file_path: str):
loader = Docx2txtLoader(temp_file_path)
return loader.load()
def read_srt(self, temp_file_path: str):
subs = pysrt.open(temp_file_path)
text = ""
for sub in subs:
text += sub.text
return [Document(page_content=text)]
def read_youtube_transcript(self, url: str):
loader = YoutubeLoader.from_youtube_url(
url, add_video_info=True, language=["en"], translation="en"
)
return loader.load()
def read_html(self, url: str):
loader = WebBaseLoader(url)
return loader.load()
def read_tex_from_url(self, tex_url):
response = requests.get(tex_url)
if response.status_code == 200:
return [Document(page_content=response.text)]
else:
print("Failed to fetch .tex file from URL:", tex_url)
return None
class ChunkProcessor:
def __init__(self, config):
self.config = config
if config["splitter_options"]["use_splitter"]:
if config["splitter_options"]["split_by_token"]:
self.splitter = RecursiveCharacterTextSplitter.from_tiktoken_encoder(
chunk_size=config["splitter_options"]["chunk_size"],
chunk_overlap=config["splitter_options"]["chunk_overlap"],
separators=config["splitter_options"]["chunk_separators"],
disallowed_special=(),
)
else:
self.splitter = RecursiveCharacterTextSplitter(
chunk_size=config["splitter_options"]["chunk_size"],
chunk_overlap=config["splitter_options"]["chunk_overlap"],
separators=config["splitter_options"]["chunk_separators"],
disallowed_special=(),
)
else:
self.splitter = None
logger.info("ChunkProcessor instance created")
def remove_delimiters(self, document_chunks: list):
for chunk in document_chunks:
for delimiter in self.config["splitter_options"]["delimiters_to_remove"]:
chunk.page_content = re.sub(delimiter, " ", chunk.page_content)
return document_chunks
def remove_chunks(self, document_chunks: list):
front = self.config["splitter_options"]["front_chunk_to_remove"]
end = self.config["splitter_options"]["last_chunks_to_remove"]
for _ in range(front):
del document_chunks[0]
for _ in range(end):
document_chunks.pop()
logger.info(f"\tNumber of pages after skipping: {len(document_chunks)}")
return document_chunks
def process_chunks(
self, documents, file_type="txt", source="", page=0, metadata={}
):
documents = [Document(page_content=documents, source=source, page=page)]
if (
file_type == "txt"
or file_type == "docx"
or file_type == "srt"
or file_type == "tex"
):
document_chunks = self.splitter.split_documents(documents)
elif file_type == "pdf":
document_chunks = documents # Full page for now
# add the source and page number back to the metadata
for chunk in document_chunks:
chunk.metadata["source"] = source
chunk.metadata["page"] = page
# add the metadata extracted from the document
for key, value in metadata.items():
chunk.metadata[key] = value
if self.config["splitter_options"]["remove_leftover_delimiters"]:
document_chunks = self.remove_delimiters(document_chunks)
if self.config["splitter_options"]["remove_chunks"]:
document_chunks = self.remove_chunks(document_chunks)
return document_chunks
def get_chunks(self, file_reader, uploaded_files, weblinks):
self.document_chunks_full = []
self.parent_document_names = []
self.child_document_names = []
self.documents = []
self.document_metadata = []
addl_metadata = get_metadata(
"https://dl4ds.github.io/sp2024/lectures/",
"https://dl4ds.github.io/sp2024/schedule/",
) # For any additional metadata
for file_index, file_path in enumerate(uploaded_files):
file_name = os.path.basename(file_path)
if file_name not in self.parent_document_names:
file_type = file_name.split(".")[-1].lower()
# try:
if file_type == "pdf":
documents = file_reader.read_pdf(file_path)
elif file_type == "txt":
documents = file_reader.read_txt(file_path)
elif file_type == "docx":
documents = file_reader.read_docx(file_path)
elif file_type == "srt":
documents = file_reader.read_srt(file_path)
elif file_type == "tex":
documents = file_reader.read_tex_from_url(file_path)
else:
logger.warning(f"Unsupported file type: {file_type}")
continue
for doc in documents:
page_num = doc.metadata.get("page", 0)
self.documents.append(doc.page_content)
self.document_metadata.append(
{"source": file_path, "page": page_num}
)
metadata = addl_metadata.get(file_path, {})
self.document_metadata[-1].update(metadata)
self.child_document_names.append(f"{file_name}_{page_num}")
self.parent_document_names.append(file_name)
if self.config["embedding_options"]["db_option"] not in [
"RAGatouille"
]:
document_chunks = self.process_chunks(
self.documents[-1],
file_type,
source=file_path,
page=page_num,
metadata=metadata,
)
self.document_chunks_full.extend(document_chunks)
# except Exception as e:
# logger.error(f"Error processing file {file_name}: {str(e)}")
self.process_weblinks(file_reader, weblinks)
logger.info(
f"Total document chunks extracted: {len(self.document_chunks_full)}"
)
return (
self.document_chunks_full,
self.child_document_names,
self.documents,
self.document_metadata,
)
def process_weblinks(self, file_reader, weblinks):
if weblinks[0] != "":
logger.info(f"Splitting weblinks: total of {len(weblinks)}")
for link_index, link in enumerate(weblinks):
if link not in self.parent_document_names:
try:
logger.info(f"\tSplitting link {link_index+1} : {link}")
if "youtube" in link:
documents = file_reader.read_youtube_transcript(link)
else:
documents = file_reader.read_html(link)
for doc in documents:
page_num = doc.metadata.get("page", 0)
self.documents.append(doc.page_content)
self.document_metadata.append(
{"source": link, "page": page_num}
)
self.child_document_names.append(f"{link}")
self.parent_document_names.append(link)
if self.config["embedding_options"]["db_option"] not in [
"RAGatouille"
]:
document_chunks = self.process_chunks(
self.documents[-1],
"txt",
source=link,
page=0,
metadata={"source_type": "webpage"},
)
self.document_chunks_full.extend(document_chunks)
except Exception as e:
logger.error(
f"Error splitting link {link_index+1} : {link}: {str(e)}"
)
class DataLoader:
def __init__(self, config):
self.file_reader = FileReader()
self.chunk_processor = ChunkProcessor(config)
def get_chunks(self, uploaded_files, weblinks):
return self.chunk_processor.get_chunks(
self.file_reader, uploaded_files, weblinks
)
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