300 lines
11 KiB
Python
300 lines
11 KiB
Python
import os
|
|
import tempfile
|
|
from typing import Any, Dict, List, Optional
|
|
|
|
# Create custom processor for connector files using Langflow
|
|
from models.processors import LangflowConnectorFileProcessor
|
|
from services.langflow_file_service import LangflowFileService
|
|
from utils.logging_config import get_logger
|
|
|
|
from .base import BaseConnector, ConnectorDocument
|
|
from .connection_manager import ConnectionManager
|
|
|
|
logger = get_logger(__name__)
|
|
|
|
|
|
class LangflowConnectorService:
|
|
"""Service to manage connector documents and process them via Langflow"""
|
|
|
|
def __init__(
|
|
self,
|
|
task_service=None,
|
|
session_manager=None,
|
|
):
|
|
self.task_service = task_service
|
|
self.session_manager = session_manager
|
|
self.connection_manager = ConnectionManager()
|
|
|
|
# Initialize LangflowFileService for processing connector documents
|
|
self.langflow_service = LangflowFileService()
|
|
|
|
async def initialize(self):
|
|
"""Initialize the service by loading existing connections"""
|
|
await self.connection_manager.load_connections()
|
|
|
|
async def get_connector(self, connection_id: str) -> Optional[BaseConnector]:
|
|
"""Get a connector by connection ID"""
|
|
return await self.connection_manager.get_connector(connection_id)
|
|
|
|
async def process_connector_document(
|
|
self,
|
|
document: ConnectorDocument,
|
|
owner_user_id: str,
|
|
connector_type: str,
|
|
jwt_token: str = None,
|
|
owner_name: str = None,
|
|
owner_email: str = None,
|
|
) -> Dict[str, Any]:
|
|
"""Process a document from a connector using LangflowFileService pattern"""
|
|
|
|
logger.debug(
|
|
"Processing connector document via Langflow",
|
|
document_id=document.id,
|
|
filename=document.filename,
|
|
)
|
|
|
|
from utils.file_utils import auto_cleanup_tempfile
|
|
|
|
suffix = self._get_file_extension(document.mimetype)
|
|
|
|
# Create temporary file from document content
|
|
with auto_cleanup_tempfile(suffix=suffix) as tmp_path:
|
|
# Write document content to temp file
|
|
with open(tmp_path, 'wb') as f:
|
|
f.write(document.content)
|
|
|
|
# Step 1: Upload file to Langflow
|
|
logger.debug("Uploading file to Langflow", filename=document.filename)
|
|
content = document.content
|
|
file_tuple = (
|
|
document.filename.replace(" ", "_").replace("/", "_")+suffix,
|
|
content,
|
|
document.mimetype or "application/octet-stream",
|
|
)
|
|
|
|
langflow_file_id = None # Initialize to track if upload succeeded
|
|
try:
|
|
upload_result = await self.langflow_service.upload_user_file(
|
|
file_tuple, jwt_token
|
|
)
|
|
langflow_file_id = upload_result["id"]
|
|
langflow_file_path = upload_result["path"]
|
|
|
|
logger.debug(
|
|
"File uploaded to Langflow",
|
|
file_id=langflow_file_id,
|
|
path=langflow_file_path,
|
|
)
|
|
|
|
# Step 2: Run ingestion flow with the uploaded file
|
|
logger.debug(
|
|
"Running Langflow ingestion flow", file_path=langflow_file_path
|
|
)
|
|
|
|
# Use the same tweaks pattern as LangflowFileService
|
|
tweaks = {} # Let Langflow handle the ingestion with default settings
|
|
|
|
ingestion_result = await self.langflow_service.run_ingestion_flow(
|
|
file_paths=[langflow_file_path],
|
|
jwt_token=jwt_token,
|
|
tweaks=tweaks,
|
|
owner=owner_user_id,
|
|
owner_name=owner_name,
|
|
owner_email=owner_email,
|
|
connector_type=connector_type,
|
|
)
|
|
|
|
logger.debug("Ingestion flow completed", result=ingestion_result)
|
|
|
|
# Step 3: Delete the file from Langflow
|
|
logger.debug("Deleting file from Langflow", file_id=langflow_file_id)
|
|
await self.langflow_service.delete_user_file(langflow_file_id)
|
|
logger.debug("File deleted from Langflow", file_id=langflow_file_id)
|
|
|
|
return {
|
|
"status": "indexed",
|
|
"filename": document.filename,
|
|
"source_url": document.source_url,
|
|
"document_id": document.id,
|
|
"connector_type": connector_type,
|
|
"langflow_result": ingestion_result,
|
|
}
|
|
|
|
except Exception as e:
|
|
logger.error(
|
|
"Failed to process connector document via Langflow",
|
|
document_id=document.id,
|
|
error=str(e),
|
|
)
|
|
# Try to clean up Langflow file if upload succeeded but processing failed
|
|
if langflow_file_id is not None:
|
|
try:
|
|
await self.langflow_service.delete_user_file(langflow_file_id)
|
|
logger.debug(
|
|
"Cleaned up Langflow file after error",
|
|
file_id=langflow_file_id,
|
|
)
|
|
except Exception as cleanup_error:
|
|
logger.warning(
|
|
"Failed to cleanup Langflow file",
|
|
file_id=langflow_file_id,
|
|
error=str(cleanup_error),
|
|
)
|
|
raise
|
|
|
|
def _get_file_extension(self, mimetype: str) -> str:
|
|
"""Get file extension based on MIME type"""
|
|
mime_to_ext = {
|
|
"application/pdf": ".pdf",
|
|
"application/vnd.openxmlformats-officedocument.wordprocessingml.document": ".docx",
|
|
"application/msword": ".doc",
|
|
"application/vnd.openxmlformats-officedocument.presentationml.presentation": ".pptx",
|
|
"application/vnd.ms-powerpoint": ".ppt",
|
|
"text/plain": ".txt",
|
|
"text/html": ".html",
|
|
"application/rtf": ".rtf",
|
|
"application/vnd.google-apps.document": ".pdf", # Exported as PDF
|
|
"application/vnd.google-apps.presentation": ".pdf",
|
|
"application/vnd.google-apps.spreadsheet": ".pdf",
|
|
}
|
|
return mime_to_ext.get(mimetype, ".bin")
|
|
|
|
async def sync_connector_files(
|
|
self,
|
|
connection_id: str,
|
|
user_id: str,
|
|
max_files: int = None,
|
|
jwt_token: str = None,
|
|
) -> str:
|
|
"""Sync files from a connector connection using Langflow processing"""
|
|
if not self.task_service:
|
|
raise ValueError(
|
|
"TaskService not available - connector sync requires task service dependency"
|
|
)
|
|
|
|
logger.debug(
|
|
"Starting Langflow-based sync for connection",
|
|
connection_id=connection_id,
|
|
max_files=max_files,
|
|
)
|
|
|
|
connector = await self.get_connector(connection_id)
|
|
if not connector:
|
|
raise ValueError(
|
|
f"Connection '{connection_id}' not found or not authenticated"
|
|
)
|
|
|
|
logger.debug("Got connector", authenticated=connector.is_authenticated)
|
|
|
|
if not connector.is_authenticated:
|
|
raise ValueError(f"Connection '{connection_id}' not authenticated")
|
|
|
|
# Collect files to process (limited by max_files)
|
|
files_to_process = []
|
|
page_token = None
|
|
|
|
# Calculate page size to minimize API calls
|
|
page_size = min(max_files or 100, 1000) if max_files else 100
|
|
|
|
while True:
|
|
# List files from connector with limit
|
|
logger.debug(
|
|
"Calling list_files", page_size=page_size, page_token=page_token
|
|
)
|
|
file_list = await connector.list_files(page_token, limit=page_size)
|
|
logger.debug(
|
|
"Got files from connector", file_count=len(file_list.get("files", []))
|
|
)
|
|
files = file_list["files"]
|
|
|
|
if not files:
|
|
break
|
|
|
|
for file_info in files:
|
|
if max_files and len(files_to_process) >= max_files:
|
|
break
|
|
files_to_process.append(file_info)
|
|
|
|
# Stop if we have enough files or no more pages
|
|
if (max_files and len(files_to_process) >= max_files) or not file_list.get(
|
|
"nextPageToken"
|
|
):
|
|
break
|
|
|
|
page_token = file_list.get("nextPageToken")
|
|
|
|
# Get user information
|
|
user = self.session_manager.get_user(user_id) if self.session_manager else None
|
|
owner_name = user.name if user else None
|
|
owner_email = user.email if user else None
|
|
|
|
processor = LangflowConnectorFileProcessor(
|
|
self,
|
|
connection_id,
|
|
files_to_process,
|
|
user_id,
|
|
jwt_token=jwt_token,
|
|
owner_name=owner_name,
|
|
owner_email=owner_email,
|
|
)
|
|
|
|
# Use file IDs as items
|
|
file_ids = [file_info["id"] for file_info in files_to_process]
|
|
|
|
# Create custom task using TaskService
|
|
task_id = await self.task_service.create_custom_task(
|
|
user_id, file_ids, processor
|
|
)
|
|
|
|
return task_id
|
|
|
|
async def sync_specific_files(
|
|
self,
|
|
connection_id: str,
|
|
user_id: str,
|
|
file_ids: List[str],
|
|
jwt_token: str = None,
|
|
) -> str:
|
|
"""Sync specific files by their IDs using Langflow processing"""
|
|
if not self.task_service:
|
|
raise ValueError(
|
|
"TaskService not available - connector sync requires task service dependency"
|
|
)
|
|
|
|
connector = await self.get_connector(connection_id)
|
|
if not connector:
|
|
raise ValueError(
|
|
f"Connection '{connection_id}' not found or not authenticated"
|
|
)
|
|
|
|
if not connector.is_authenticated:
|
|
raise ValueError(f"Connection '{connection_id}' not authenticated")
|
|
|
|
if not file_ids:
|
|
raise ValueError("No file IDs provided")
|
|
|
|
# Get user information
|
|
user = self.session_manager.get_user(user_id) if self.session_manager else None
|
|
owner_name = user.name if user else None
|
|
owner_email = user.email if user else None
|
|
|
|
processor = LangflowConnectorFileProcessor(
|
|
self,
|
|
connection_id,
|
|
file_ids,
|
|
user_id,
|
|
jwt_token=jwt_token,
|
|
owner_name=owner_name,
|
|
owner_email=owner_email,
|
|
)
|
|
|
|
# Create custom task using TaskService
|
|
task_id = await self.task_service.create_custom_task(
|
|
user_id, file_ids, processor
|
|
)
|
|
|
|
return task_id
|
|
|
|
async def _get_connector(self, connection_id: str) -> Optional[BaseConnector]:
|
|
"""Get a connector by connection ID (alias for get_connector)"""
|
|
return await self.get_connector(connection_id)
|