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Merge branch 'main' of github.com:HKUDS/LightRAG

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This commit is contained in:
yangdx 2025-11-13 20:42:47 +08:00
commit c164c8f631
5 changed files with 904 additions and 681 deletions
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17
lightrag/api/config.py
View file

@ -258,6 +258,14 @@ def parse_args() -> argparse.Namespace:
help=f"Rerank binding type (default: from env or {DEFAULT_RERANK_BINDING})",
)
# Document loading engine configuration
parser.add_argument(
"--docling",
action="store_true",
default=False,
help="Enable DOCLING document loading engine (default: from env or DEFAULT)",
)
# Conditionally add binding options defined in binding_options module
# This will add command line arguments for all binding options (e.g., --ollama-embedding-num_ctx)
# and corresponding environment variables (e.g., OLLAMA_EMBEDDING_NUM_CTX)
@ -371,8 +379,13 @@ def parse_args() -> argparse.Namespace:
)
args.enable_llm_cache = get_env_value("ENABLE_LLM_CACHE", True, bool)
# Select Document loading tool (DOCLING, DEFAULT)
args.document_loading_engine = get_env_value("DOCUMENT_LOADING_ENGINE", "DEFAULT")
# Set document_loading_engine from --docling flag
if args.docling:
args.document_loading_engine = "DOCLING"
else:
args.document_loading_engine = get_env_value(
"DOCUMENT_LOADING_ENGINE", "DEFAULT"
)
# PDF decryption password
args.pdf_decrypt_password = get_env_value("PDF_DECRYPT_PASSWORD", None)

65
lightrag/api/routers/document_routes.py
View file

@ -3,6 +3,7 @@ This module contains all document-related routes for the LightRAG API.
"""
import asyncio
from functools import lru_cache
from lightrag.utils import logger, get_pinyin_sort_key
import aiofiles
import shutil
@ -27,19 +28,23 @@ from lightrag.utils import generate_track_id
from lightrag.api.utils_api import get_combined_auth_dependency
from ..config import global_args
# Check docling availability at module load time
DOCLING_AVAILABLE = False
try:
import docling # noqa: F401 # type: ignore[import-not-found]
DOCLING_AVAILABLE = True
except ImportError:
if global_args.document_loading_engine == "DOCLING":
logger.warning(
"DOCLING engine requested but 'docling' package not installed. "
"Falling back to standard document processing. "
"To use DOCLING, install with: pip install lightrag-hku[api,docling]"
)
@lru_cache(maxsize=1)
def _is_docling_available() -> bool:
"""Check if docling is available (cached check).
This function uses lru_cache to avoid repeated import attempts.
The result is cached after the first call.
Returns:
bool: True if docling is available, False otherwise
"""
try:
import docling # noqa: F401 # type: ignore[import-not-found]
return True
except ImportError:
return False
# Function to format datetime to ISO format string with timezone information
@ -1204,12 +1209,19 @@ async def pipeline_enqueue_file(
# Try DOCLING first if configured and available
if (
global_args.document_loading_engine == "DOCLING"
and DOCLING_AVAILABLE
and _is_docling_available()
):
content = await asyncio.to_thread(
_convert_with_docling, file_path
)
else:
if (
global_args.document_loading_engine == "DOCLING"
and not _is_docling_available()
):
logger.warning(
f"DOCLING engine configured but not available for {file_path.name}. Falling back to pypdf."
)
# Use pypdf (non-blocking via to_thread)
content = await asyncio.to_thread(
_extract_pdf_pypdf,
@ -1238,12 +1250,19 @@ async def pipeline_enqueue_file(
# Try DOCLING first if configured and available
if (
global_args.document_loading_engine == "DOCLING"
and DOCLING_AVAILABLE
and _is_docling_available()
):
content = await asyncio.to_thread(
_convert_with_docling, file_path
)
else:
if (
global_args.document_loading_engine == "DOCLING"
and not _is_docling_available()
):
logger.warning(
f"DOCLING engine configured but not available for {file_path.name}. Falling back to python-docx."
)
# Use python-docx (non-blocking via to_thread)
content = await asyncio.to_thread(_extract_docx, file)
except Exception as e:
@ -1268,12 +1287,19 @@ async def pipeline_enqueue_file(
# Try DOCLING first if configured and available
if (
global_args.document_loading_engine == "DOCLING"
and DOCLING_AVAILABLE
and _is_docling_available()
):
content = await asyncio.to_thread(
_convert_with_docling, file_path
)
else:
if (
global_args.document_loading_engine == "DOCLING"
and not _is_docling_available()
):
logger.warning(
f"DOCLING engine configured but not available for {file_path.name}. Falling back to python-pptx."
)
# Use python-pptx (non-blocking via to_thread)
content = await asyncio.to_thread(_extract_pptx, file)
except Exception as e:
@ -1298,12 +1324,19 @@ async def pipeline_enqueue_file(
# Try DOCLING first if configured and available
if (
global_args.document_loading_engine == "DOCLING"
and DOCLING_AVAILABLE
and _is_docling_available()
):
content = await asyncio.to_thread(
_convert_with_docling, file_path
)
else:
if (
global_args.document_loading_engine == "DOCLING"
and not _is_docling_available()
):
logger.warning(
f"DOCLING engine configured but not available for {file_path.name}. Falling back to openpyxl."
)
# Use openpyxl (non-blocking via to_thread)
content = await asyncio.to_thread(_extract_xlsx, file)
except Exception as e:

30
lightrag/api/run_with_gunicorn.py
View file

@ -5,6 +5,7 @@ Start LightRAG server with Gunicorn
import os
import sys
import platform
import pipmaster as pm
from lightrag.api.utils_api import display_splash_screen, check_env_file
from lightrag.api.config import global_args
@ -46,6 +47,35 @@ def main():
if not check_env_file():
sys.exit(1)
# Check DOCLING compatibility with Gunicorn multi-worker mode on macOS
if (
platform.system() == "Darwin"
and global_args.document_loading_engine == "DOCLING"
and global_args.workers > 1
):
print("\n" + "=" * 80)
print("❌ ERROR: Incompatible configuration detected!")
print("=" * 80)
print(
"\nDOCLING engine with Gunicorn multi-worker mode is not supported on macOS"
)
print("\nReason:")
print(" PyTorch (required by DOCLING) has known compatibility issues with")
print(" fork-based multiprocessing on macOS, which can cause crashes or")
print(" unexpected behavior when using Gunicorn with multiple workers.")
print("\nCurrent configuration:")
print(" - Operating System: macOS (Darwin)")
print(f" - Document Engine: {global_args.document_loading_engine}")
print(f" - Workers: {global_args.workers}")
print("\nPossible solutions:")
print(" 1. Use single worker mode:")
print(" --workers 1")
print("\n 2. Change document loading engine in .env:")
print(" DOCUMENT_LOADING_ENGINE=DEFAULT")
print("\n 3. Deploy on Linux where multi-worker mode is fully supported")
print("=" * 80 + "\n")
sys.exit(1)
# Check and install dependencies
check_and_install_dependencies()

8
pyproject.toml
View file

@ -29,7 +29,7 @@ dependencies = [
"json_repair",
"nano-vectordb",
"networkx",
"numpy",
"numpy>=1.24.0,<2.0.0",
"pandas>=2.0.0,<2.4.0",
"pipmaster",
"pydantic",
@ -50,7 +50,7 @@ api = [
"json_repair",
"nano-vectordb",
"networkx",
"numpy",
"numpy>=1.24.0,<2.0.0",
"openai>=1.0.0,<3.0.0",
"pandas>=2.0.0,<2.4.0",
"pipmaster",
@ -90,7 +90,9 @@ api = [
# Advanced document processing engine (optional)
docling = [
"docling>=2.0.0,<3.0.0",
# On macOS, pytorch and frameworks use Objective-C are not fork-safe,
# and not compatible to gunicorn multi-worker mode
"docling>=2.0.0,<3.0.0; sys_platform != 'darwin'",
]
# Offline deployment dependencies (layered design for flexibility)

1465
uv.lock generated
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