File size: 16,940 Bytes
f51bb92 6581a76 f51bb92 3ff5066 0958f93 229ace9 1e2550f 4fc2bf8 3ff5066 4fc2bf8 3ff5066 1e2550f 3ff5066 4fc2bf8 3ff5066 1e2550f 3ff5066 f51bb92 1e2550f f51bb92 3ff5066 f51bb92 3ff5066 229ace9 3ff5066 1e2550f 3ff5066 f51bb92 39c29a9 f51bb92 229ace9 f51bb92 4fc2bf8 f51bb92 1e2550f 6581a76 f51bb92 6581a76 1e2550f 6581a76 f51bb92 6581a76 1e2550f f51bb92 6581a76 f51bb92 c26167a 1e2550f 6581a76 f51bb92 c82efb6 f51bb92 1e2550f f51bb92 49140fa f51bb92 c658776 f51bb92 1e2550f f51bb92 3ff5066 638bffe f51bb92 6581a76 1e2550f 6581a76 638bffe f51bb92 638bffe f51bb92 1e2550f f51bb92 1e2550f f51bb92 5cd7fa4 ca828e7 5cd7fa4 60929fd 5cd7fa4 f51bb92 60929fd f51bb92 60929fd 4308a1a 1e2550f 3ff5066 1e2550f 3ff5066 f51bb92 4308a1a c82efb6 5cd7fa4 c82efb6 f51bb92 9a7da99 638bffe 9a7da99 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 |
import os
import re
import requests
import pysrt
from langchain_community.document_loaders import (
Docx2txtLoader,
YoutubeLoader,
TextLoader,
)
from langchain.schema import Document
import logging
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain_experimental.text_splitter import SemanticChunker
from langchain_openai.embeddings import OpenAIEmbeddings
import json
from concurrent.futures import ThreadPoolExecutor
from urllib.parse import urljoin
import html2text
import bs4
import PyPDF2
from modules.dataloader.pdf_readers.base import PDFReader
from modules.dataloader.pdf_readers.llama import LlamaParser
from modules.dataloader.pdf_readers.gpt import GPTParser
from modules.dataloader.helpers import get_metadata
from modules.config.constants import TIMEOUT
logger = logging.getLogger(__name__)
BASE_DIR = os.getcwd()
class HTMLReader:
def __init__(self):
pass
def read_url(self, url):
response = requests.get(url, timeout=TIMEOUT)
if response.status_code == 200:
return response.text
else:
logger.warning(f"Failed to download HTML from URL: {url}")
return None
def check_links(self, base_url, html_content):
soup = bs4.BeautifulSoup(html_content, "html.parser")
for link in soup.find_all("a"):
href = link.get("href")
if not href or href.startswith("#"):
continue
elif not href.startswith("https"):
href = href.replace("http", "https")
absolute_url = urljoin(base_url, href)
link["href"] = absolute_url
resp = requests.head(absolute_url, timeout=TIMEOUT)
if resp.status_code != 200:
logger.warning(
f"Link {absolute_url} is broken. Status code: {resp.status_code}"
)
return str(soup)
def html_to_md(self, url, html_content):
html_processed = self.check_links(url, html_content)
markdown_content = html2text.html2text(html_processed)
return markdown_content
def read_html(self, url):
html_content = self.read_url(url)
if html_content:
return self.html_to_md(url, html_content)
else:
return None
class FileReader:
def __init__(self, logger, kind):
self.logger = logger
self.kind = kind
if kind == "llama":
self.pdf_reader = LlamaParser()
elif kind == "gpt":
self.pdf_reader = GPTParser()
else:
self.pdf_reader = PDFReader()
self.web_reader = HTMLReader()
self.logger.info(
f"Initialized FileReader with {kind} PDF reader and HTML reader"
)
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 read_pdf(self, temp_file_path: str):
documents = self.pdf_reader.parse(temp_file_path)
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):
return [Document(page_content=self.web_reader.read_html(url))]
def read_tex_from_url(self, tex_url):
response = requests.get(tex_url, timeout=TIMEOUT)
if response.status_code == 200:
return [Document(page_content=response.text)]
else:
self.logger.error(f"Failed to fetch .tex file from URL: {tex_url}")
return None
class ChunkProcessor:
def __init__(self, config, logger):
self.config = config
self.logger = logger
self.document_data = {}
self.document_metadata = {}
self.document_chunks_full = []
# TODO: Fix when reparse_files is False
if not config["vectorstore"]["reparse_files"]:
self.load_document_data()
if config["splitter_options"]["use_splitter"]:
if config["splitter_options"]["chunking_mode"] == "fixed":
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 = SemanticChunker(
OpenAIEmbeddings(), breakpoint_threshold_type="percentile"
)
else:
self.splitter = None
self.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()
return document_chunks
def process_chunks(
self, documents, file_type="txt", source="", page=0, metadata={}
):
# TODO: Clear up this pipeline of re-adding metadata
documents = [Document(page_content=documents, source=source, page=page)]
if (
file_type == "pdf"
and self.config["splitter_options"]["chunking_mode"] == "fixed"
):
document_chunks = documents
else:
document_chunks = self.splitter.split_documents(documents)
# 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 chunk_docs(self, file_reader, uploaded_files, weblinks):
addl_metadata = get_metadata(
*self.config["metadata"]["metadata_links"], self.config
) # For any additional metadata
# remove already processed files if reparse_files is False
if not self.config["vectorstore"]["reparse_files"]:
total_documents = len(uploaded_files) + len(weblinks)
uploaded_files = [
file_path
for file_path in uploaded_files
if file_path not in self.document_data
]
weblinks = [link for link in weblinks if link not in self.document_data]
print(
f"Total documents to process: {total_documents}, Documents already processed: {total_documents - len(uploaded_files) - len(weblinks)}"
)
with ThreadPoolExecutor() as executor:
executor.map(
self.process_file,
uploaded_files,
range(len(uploaded_files)),
[file_reader] * len(uploaded_files),
[addl_metadata] * len(uploaded_files),
)
executor.map(
self.process_weblink,
weblinks,
range(len(weblinks)),
[file_reader] * len(weblinks),
[addl_metadata] * len(weblinks),
)
document_names = [
f"{file_name}_{page_num}"
for file_name, pages in self.document_data.items()
for page_num in pages.keys()
]
documents = [
page for doc in self.document_data.values() for page in doc.values()
]
document_metadata = [
page for doc in self.document_metadata.values() for page in doc.values()
]
self.save_document_data()
self.logger.info(
f"Total document chunks extracted: {len(self.document_chunks_full)}"
)
return self.document_chunks_full, document_names, documents, document_metadata
def process_documents(
self, documents, file_path, file_type, metadata_source, addl_metadata
):
file_data = {}
file_metadata = {}
for doc in documents:
# if len(doc.page_content) <= 400: # better approach to filter out non-informative documents
# continue
page_num = doc.metadata.get("page", 0)
file_data[page_num] = doc.page_content
# Create a new dictionary for metadata in each iteration
metadata = addl_metadata.get(file_path, {}).copy()
metadata["page"] = page_num
metadata["source"] = file_path
file_metadata[page_num] = metadata
if self.config["vectorstore"]["db_option"] not in ["RAGatouille"]:
document_chunks = self.process_chunks(
doc.page_content,
file_type,
source=file_path,
page=page_num,
metadata=metadata,
)
self.document_chunks_full.extend(document_chunks)
self.document_data[file_path] = file_data
self.document_metadata[file_path] = file_metadata
def process_file(self, file_path, file_index, file_reader, addl_metadata):
print(f"Processing file {file_index + 1} : {file_path}")
file_name = os.path.basename(file_path)
file_type = file_name.split(".")[-1]
read_methods = {
"pdf": file_reader.read_pdf,
"txt": file_reader.read_txt,
"docx": file_reader.read_docx,
"srt": file_reader.read_srt,
"tex": file_reader.read_tex_from_url,
}
if file_type not in read_methods:
self.logger.warning(f"Unsupported file type: {file_type}")
return
try:
if file_path in self.document_data:
self.logger.warning(f"File {file_name} already processed")
documents = [
Document(page_content=content)
for content in self.document_data[file_path].values()
]
else:
documents = read_methods[file_type](file_path)
self.process_documents(
documents, file_path, file_type, "file", addl_metadata
)
except Exception as e:
self.logger.error(f"Error processing file {file_name}: {str(e)}")
def process_weblink(self, link, link_index, file_reader, addl_metadata):
if link in self.document_data:
return
self.logger.info(f"Reading link {link_index + 1} : {link}")
try:
if "youtube" in link:
documents = file_reader.read_youtube_transcript(link)
else:
documents = file_reader.read_html(link)
self.process_documents(documents, link, "txt", "link", addl_metadata)
except Exception as e:
self.logger.error(f"Error Reading link {link_index + 1} : {link}: {str(e)}")
def save_document_data(self):
if not os.path.exists(f"{self.config['log_chunk_dir']}/docs"):
os.makedirs(f"{self.config['log_chunk_dir']}/docs")
self.logger.info(
f"Creating directory {self.config['log_chunk_dir']}/docs for document data"
)
self.logger.info(
f"Saving document content to {self.config['log_chunk_dir']}/docs/doc_content.json"
)
if not os.path.exists(f"{self.config['log_chunk_dir']}/metadata"):
os.makedirs(f"{self.config['log_chunk_dir']}/metadata")
self.logger.info(
f"Creating directory {self.config['log_chunk_dir']}/metadata for document metadata"
)
self.logger.info(
f"Saving document metadata to {self.config['log_chunk_dir']}/metadata/doc_metadata.json"
)
with open(
f"{self.config['log_chunk_dir']}/docs/doc_content.json", "w"
) as json_file:
json.dump(self.document_data, json_file, indent=4)
with open(
f"{self.config['log_chunk_dir']}/metadata/doc_metadata.json", "w"
) as json_file:
json.dump(self.document_metadata, json_file, indent=4)
def load_document_data(self):
try:
with open(
f"{self.config['log_chunk_dir']}/docs/doc_content.json", "r"
) as json_file:
self.document_data = json.load(json_file)
with open(
f"{self.config['log_chunk_dir']}/metadata/doc_metadata.json", "r"
) as json_file:
self.document_metadata = json.load(json_file)
self.logger.info(
f"Loaded document content from {self.config['log_chunk_dir']}/docs/doc_content.json. Total documents: {len(self.document_data)}"
)
except FileNotFoundError:
self.logger.warning(
f"Document content not found in {self.config['log_chunk_dir']}/docs/doc_content.json"
)
self.document_data = {}
self.document_metadata = {}
class DataLoader:
def __init__(self, config, logger=None):
self.file_reader = FileReader(
logger=logger, kind=config["llm_params"]["pdf_reader"]
)
self.chunk_processor = ChunkProcessor(config, logger=logger)
def get_chunks(self, uploaded_files, weblinks):
return self.chunk_processor.chunk_docs(
self.file_reader, uploaded_files, weblinks
)
if __name__ == "__main__":
import yaml
import argparse
parser = argparse.ArgumentParser(description="Process some links.")
parser.add_argument(
"--links", nargs="+", required=True, help="List of links to process."
)
parser.add_argument(
"--config_file", type=str, help="Path to the main config file", required=True
)
parser.add_argument(
"--project_config_file",
type=str,
help="Path to the project config file",
required=True,
)
args = parser.parse_args()
links_to_process = args.links
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
with open(args.config_file, "r") as f:
config = yaml.safe_load(f)
with open(args.project_config_file, "r") as f:
project_config = yaml.safe_load(f)
# Combine project config with the main config
config.update(project_config)
STORAGE_DIR = os.path.join(BASE_DIR, config["vectorstore"]["data_path"])
uploaded_files = [
os.path.join(STORAGE_DIR, file)
for file in os.listdir(STORAGE_DIR)
if file != "urls.txt"
]
data_loader = DataLoader(config, logger=logger)
# Just for testing
(
document_chunks,
document_names,
documents,
document_metadata,
) = data_loader.get_chunks(
links_to_process,
[],
)
print(document_names[:5])
print(len(document_chunks))
|