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This commit is contained in:
hzywhite 2025-09-04 10:57:41 +08:00
parent e27031587d
commit 82a0f8cc1f
3 changed files with 36 additions and 18 deletions
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19
lightrag/api/lightrag_server.py
View file

@ -543,6 +543,9 @@ def create_app(args):
},
ollama_server_infos=ollama_server_infos,
)
except Exception as e:
logger.error(f"Failed to initialize LightRAG: {e}")
raise
# Initialize RAGAnything with comprehensive error handling
rag_anything = None
@ -648,33 +651,33 @@ def create_app(args):
RAGManager.set_rag(rag_anything)
raganything_enabled = True
logger.info(
"✅ The RAGAnything feature has been successfully enabled, supporting multimodal document processing functionality"
"The RAGAnything feature has been successfully enabled, supporting multimodal document processing functionality"
)
except ImportError as e:
raganything_error_message = (
f"RAGAnything dependency package not installed: {str(e)}"
)
logger.warning(f"⚠️ {raganything_error_message}")
logger.warning(f"{raganything_error_message}")
logger.info(
"💡 Please run 'pip install raganything' to install dependency packages to enable multimodal document processing functionality"
"Please run 'pip install raganything' to install dependency packages to enable multimodal document processing functionality"
)
except ValueError as e:
raganything_error_message = f"RAGAnything configuration error: {str(e)}"
logger.warning(f"⚠️ {raganything_error_message}")
logger.warning(f"{raganything_error_message}")
logger.info(
"💡 Please check if the environment variables LLM-BINDING_API_KEY and LLM-BINDING_HOST are set correctly"
"Please check if the environment variables LLM-BINDING_API_KEY and LLM-BINDING_HOST are set correctly"
)
except Exception as e:
raganything_error_message = f"RAGAnything initialization failed: {str(e)}"
logger.error(f"❌ {raganything_error_message}")
logger.error(f" {raganything_error_message}")
logger.info(
"💡 The system will run in basic mode and only support standard document processing functions"
"The system will run in basic mode and only support standard document processing functions"
)
if not raganything_enabled:
logger.info(
"🔄 The system has been downgraded to basic mode, but LightRAG core functions are still available"
"The system has been downgraded to basic mode, but LightRAG core functions are still available"
)
# Add routes

19
lightrag/api/routers/document_routes.py
View file

@ -5,7 +5,6 @@ This module contains all document-related routes for the LightRAG API.
import asyncio
import json
import uuid
from lightrag.utils import logger, get_pinyin_sort_key
import aiofiles
import shutil
@ -464,7 +463,7 @@ class DocStatusResponse(BaseModel):
"id": "doc_123456",
"content_summary": "Research paper on machine learning",
"scheme_name": "lightrag",
"multimodal_content": None,
"multimodal_content": [],
"content_length": 15240,
"status": "PROCESSED",
"created_at": "2025-03-31T12:34:56",
@ -499,7 +498,7 @@ class DocsStatusesResponse(BaseModel):
"id": "doc_123",
"content_summary": "Pending document",
"scheme_name": "lightrag",
"multimodal_content": None,
"multimodal_content": [],
"content_length": 5000,
"status": "PENDING",
"created_at": "2025-03-31T10:00:00",
@ -516,7 +515,7 @@ class DocsStatusesResponse(BaseModel):
"id": "doc_456",
"content_summary": "Processed document",
"scheme_name": "lightrag",
"multimodal_content": None,
"multimodal_content": [],
"content_length": 8000,
"status": "PROCESSED",
"created_at": "2025-03-31T09:00:00",
@ -878,6 +877,8 @@ async def pipeline_enqueue_file(
rag: LightRAG instance
file_path: Path to the saved file
track_id: Optional tracking ID, if not provided will be generated
scheme_name (str, optional): Processing scheme name for categorization.
Defaults to None
Returns:
tuple: (success: bool, track_id: str)
"""
@ -1346,6 +1347,8 @@ async def pipeline_index_file(
rag: LightRAG instance
file_path: Path to the saved file
track_id: Optional tracking ID
scheme_name (str, optional): Processing scheme name for categorization.
Defaults to None
"""
try:
success, returned_track_id = await pipeline_enqueue_file(
@ -1368,6 +1371,8 @@ async def pipeline_index_files(
rag: LightRAG instance
file_paths: Paths to the files to index
track_id: Optional tracking ID to pass to all files
scheme_name (str, optional): Processing scheme name for categorization.
Defaults to None
"""
if not file_paths:
return
@ -1482,8 +1487,11 @@ async def run_scanning_process(
Args:
rag: LightRAG instance
rag_anythingL: RAGAnything instance
doc_manager: DocumentManager instance
track_id: Optional tracking ID to pass to all scanned files
scheme_name (str, optional): Processing scheme name for categorization.
Defaults to None
"""
try:
new_files = doc_manager.scan_directory_for_new_files()
@ -2017,7 +2025,7 @@ def create_document_routes(
Args:
background_tasks: FastAPI BackgroundTasks for async processing
file (UploadFile): The file to be uploaded. It must have an allowed extension.
file (UploadFile): The file to be uploaded. It must have an allowed extension
schemeId (str): ID of the processing scheme to use for this file. The scheme
determines whether to use LightRAG or RAGAnything framework for processing.
@ -2544,6 +2552,7 @@ def create_document_routes(
DocStatusResponse(
id=doc_id,
content_summary=doc_status.content_summary,
multimodal_content=doc_status.multimodal_content,
content_length=doc_status.content_length,
status=doc_status.status,
created_at=format_datetime(doc_status.created_at),

16
lightrag/lightrag.py
View file

@ -881,6 +881,8 @@ class LightRAG:
Args:
input: Single document string or list of document strings
multimodal_content (list[dict[str, Any]] | list[list[dict[str, Any]]] | None, optional):
Multimodal content (images, tables, equations) associated with documents
split_by_character: if split_by_character is not None, split the string by character, if chunk longer than
chunk_token_size, it will be split again by token size.
split_by_character_only: if split_by_character_only is True, split the string by character only, when
@ -888,6 +890,7 @@ class LightRAG:
ids: single string of the document ID or list of unique document IDs, if not provided, MD5 hash IDs will be generated
file_paths: single string of the file path or list of file paths, used for citation
track_id: tracking ID for monitoring processing status, if not provided, will be generated
scheme_name (str | None, optional): Scheme name for categorizing documents
Returns:
str: tracking ID for monitoring processing status
@ -896,8 +899,8 @@ class LightRAG:
return loop.run_until_complete(
self.ainsert(
input,
split_by_character,
multimodal_content,
split_by_character,
split_by_character_only,
ids,
file_paths,
@ -963,13 +966,14 @@ class LightRAG:
self.move_file_to_enqueue(current_file_path)
else:
continue
await self.apipeline_process_enqueue_documents(
split_by_character, split_by_character_only
)
return track_id
def move_file_to_enqueue(self, file_path):
try:
enqueued_dir = file_path.parent / "__enqueued__"
@ -1093,7 +1097,9 @@ class LightRAG:
async def apipeline_enqueue_documents(
self,
input: str | list[str],
multimodal_content: list[dict[str, Any]] | None = None,
multimodal_content: list[dict[str, Any]]
| list[list[dict[str, Any]]]
| None = None,
ids: list[str] | None = None,
file_paths: str | list[str] | None = None,
track_id: str | None = None,
@ -1192,8 +1198,8 @@ class LightRAG:
"file_path": content_data[
"file_path"
], # Store file path in document status
"track_id": track_id,
"scheme_name": scheme_name, # Store track_id in document status
"track_id": track_id, # Store track_id in document status
"scheme_name": scheme_name,
}
for id_, content_data in contents.items()
}