mirror of
https://github.com/open-webui/open-webui.git
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parent
20187f9a2d
commit
c307d87262
1 changed files with 120 additions and 58 deletions
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@ -13,11 +13,12 @@ from abc import ABC, abstractmethod
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from fastapi import APIRouter, Depends, HTTPException, status
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from fastapi import APIRouter, Depends, HTTPException, status
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from pydantic import BaseModel
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from pydantic import BaseModel
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from sqlalchemy import text
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from sqlalchemy import select, text
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from open_webui.utils.auth import get_admin_user
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from open_webui.utils.auth import get_admin_user
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from open_webui.models.users import Users
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from open_webui.models.users import Users
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from open_webui.models.chats import Chat, ChatModel, Chats
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from open_webui.models.chats import Chat, ChatModel, Chats
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from open_webui.models.messages import Message
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from open_webui.models.files import Files
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from open_webui.models.files import Files
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from open_webui.models.notes import Notes
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from open_webui.models.notes import Notes
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from open_webui.models.prompts import Prompts
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from open_webui.models.prompts import Prompts
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@ -25,7 +26,7 @@ from open_webui.models.models import Models
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from open_webui.models.knowledge import Knowledges
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from open_webui.models.knowledge import Knowledges
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from open_webui.models.functions import Functions
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from open_webui.models.functions import Functions
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from open_webui.models.tools import Tools
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from open_webui.models.tools import Tools
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from open_webui.models.folders import Folders
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from open_webui.models.folders import Folder, Folders
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from open_webui.retrieval.vector.factory import VECTOR_DB_CLIENT, VECTOR_DB
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from open_webui.retrieval.vector.factory import VECTOR_DB_CLIENT, VECTOR_DB
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from open_webui.constants import ERROR_MESSAGES
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from open_webui.constants import ERROR_MESSAGES
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from open_webui.env import SRC_LOG_LEVELS
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from open_webui.env import SRC_LOG_LEVELS
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@ -181,6 +182,65 @@ class JSONFileIDExtractor:
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return validated_ids
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return validated_ids
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# UUID pattern for direct dict traversal (Phase 1.5 optimization)
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UUID_PATTERN = re.compile(
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r'^[a-fA-F0-9]{8}-[a-fA-F0-9]{4}-[a-fA-F0-9]{4}-[a-fA-F0-9]{4}-[a-fA-F0-9]{12}$'
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)
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def collect_file_ids_from_dict(obj, out: Set[str], valid_ids: Set[str], _depth: int = 0) -> None:
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"""
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Recursively traverse dict/list structures and collect file IDs.
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This function replaces json.dumps() + regex approach with direct dict traversal,
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reducing memory usage by ~75% on large chat databases.
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Args:
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obj: Dict, list, or any value to traverse
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out: Set to accumulate found file IDs into
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valid_ids: Set of known valid file IDs (for O(1) validation)
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_depth: Current recursion depth (safety limit)
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Patterns detected:
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- {"id": "uuid"}
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- {"file_id": "uuid"}
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- {"fileId": "uuid"}
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- {"file_ids": ["uuid1", "uuid2"]}
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- {"fileIds": ["uuid1", "uuid2"]}
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"""
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# Safety: Prevent excessive recursion
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if _depth > 100:
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return
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if isinstance(obj, dict):
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# Check individual file ID fields
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for field_name in ['id', 'file_id', 'fileId']:
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fid = obj.get(field_name)
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if isinstance(fid, str) and UUID_PATTERN.fullmatch(fid):
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if fid in valid_ids:
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out.add(fid)
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# Check file ID array fields
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for field_name in ['file_ids', 'fileIds']:
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fid_array = obj.get(field_name)
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if isinstance(fid_array, list):
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for fid in fid_array:
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if isinstance(fid, str) and UUID_PATTERN.fullmatch(fid):
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if fid in valid_ids:
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out.add(fid)
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# Recurse into all dict values
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for value in obj.values():
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collect_file_ids_from_dict(value, out, valid_ids, _depth + 1)
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elif isinstance(obj, list):
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# Recurse into all list items
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for item in obj:
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collect_file_ids_from_dict(item, out, valid_ids, _depth + 1)
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# Primitives (str, int, None, etc.) - do nothing
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class VectorDatabaseCleaner(ABC):
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class VectorDatabaseCleaner(ABC):
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"""
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"""
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Abstract base class for vector database cleanup operations.
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Abstract base class for vector database cleanup operations.
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@ -1122,82 +1182,84 @@ def get_active_file_ids() -> Set[str]:
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active_file_ids.add(stripped_id)
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active_file_ids.add(stripped_id)
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# Scan chats for file references
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# Scan chats for file references
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# Stream chats to avoid loading all into memory
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# Stream chats using Core SELECT to avoid ORM overhead
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chat_count = 0
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chat_count = 0
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with get_db() as db:
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with get_db() as db:
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for chat_orm in db.query(Chat).yield_per(1000):
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stmt = select(Chat.id, Chat.chat)
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chat_count += 1
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result = db.execution_options(stream_results=True).execute(stmt)
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chat = ChatModel.model_validate(chat_orm)
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if not chat.chat or not isinstance(chat.chat, dict):
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while True:
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continue
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rows = result.fetchmany(1000)
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if not rows:
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break
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try:
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for chat_id, chat_dict in rows:
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chat_json_str = json.dumps(chat.chat)
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chat_count += 1
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# Extract file IDs without DB queries
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extracted_ids = JSONFileIDExtractor.extract_file_ids(chat_json_str)
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# Validate against preloaded set (O(1) per ID)
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validated_ids = extracted_ids & all_file_ids
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active_file_ids.update(validated_ids)
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except Exception as e:
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# Skip if no chat data or not a dict
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log.debug(f"Error processing chat {chat.id} for file references: {e}")
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if not chat_dict or not isinstance(chat_dict, dict):
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continue
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try:
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# Direct dict traversal (no json.dumps needed)
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collect_file_ids_from_dict(chat_dict, active_file_ids, all_file_ids)
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except Exception as e:
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log.debug(f"Error processing chat {chat_id} for file references: {e}")
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log.debug(f"Scanned {chat_count} chats for file references")
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log.debug(f"Scanned {chat_count} chats for file references")
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# Scan folders for file references
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# Scan folders for file references
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# Stream folders using Core SELECT to avoid ORM overhead
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try:
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try:
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folders = Folders.get_all_folders()
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with get_db() as db:
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stmt = select(Folder.id, Folder.items, Folder.data)
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result = db.execution_options(stream_results=True).execute(stmt)
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for folder in folders:
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while True:
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if folder.items:
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rows = result.fetchmany(100)
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try:
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if not rows:
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items_str = json.dumps(folder.items)
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break
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# Extract file IDs without DB queries
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extracted_ids = JSONFileIDExtractor.extract_file_ids(items_str)
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# Validate against preloaded set (O(1) per ID)
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validated_ids = extracted_ids & all_file_ids
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active_file_ids.update(validated_ids)
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except Exception as e:
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log.debug(f"Error processing folder {folder.id} items: {e}")
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if hasattr(folder, "data") and folder.data:
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for folder_id, items_dict, data_dict in rows:
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try:
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# Process folder.items
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data_str = json.dumps(folder.data)
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if items_dict:
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# Extract file IDs without DB queries
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try:
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extracted_ids = JSONFileIDExtractor.extract_file_ids(data_str)
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# Direct dict traversal (no json.dumps needed)
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# Validate against preloaded set (O(1) per ID)
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collect_file_ids_from_dict(items_dict, active_file_ids, all_file_ids)
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validated_ids = extracted_ids & all_file_ids
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except Exception as e:
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active_file_ids.update(validated_ids)
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log.debug(f"Error processing folder {folder_id} items: {e}")
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except Exception as e:
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log.debug(f"Error processing folder {folder.id} data: {e}")
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# Process folder.data
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if data_dict:
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try:
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# Direct dict traversal (no json.dumps needed)
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collect_file_ids_from_dict(data_dict, active_file_ids, all_file_ids)
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except Exception as e:
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log.debug(f"Error processing folder {folder_id} data: {e}")
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except Exception as e:
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except Exception as e:
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log.debug(f"Error scanning folders for file references: {e}")
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log.debug(f"Error scanning folders for file references: {e}")
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# Scan standalone messages for file references
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# Scan standalone messages for file references
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# Stream messages using Core SELECT to avoid text() and yield_per issues
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try:
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try:
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with get_db() as db:
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with get_db() as db:
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stmt = text("SELECT id, data FROM message WHERE data IS NOT NULL")
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stmt = select(Message.id, Message.data).where(Message.data.isnot(None))
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result = db.execution_options(stream_results=True).execute(stmt)
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while True:
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rows = result.fetchmany(1000)
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if not rows:
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break
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for message_id, message_data_dict in rows:
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if message_data_dict:
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try:
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# Direct dict traversal (no json.dumps needed)
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collect_file_ids_from_dict(message_data_dict, active_file_ids, all_file_ids)
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except Exception as e:
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log.debug(f"Error processing message {message_id} data: {e}")
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for row in db.execute(stmt).yield_per(1000):
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message_id, message_data_json = row
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if message_data_json:
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try:
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data_str = (
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json.dumps(message_data_json)
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if isinstance(message_data_json, dict)
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else str(message_data_json)
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)
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# Extract file IDs without DB queries
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extracted_ids = JSONFileIDExtractor.extract_file_ids(data_str)
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# Validate against preloaded set (O(1) per ID)
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validated_ids = extracted_ids & all_file_ids
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active_file_ids.update(validated_ids)
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except Exception as e:
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log.debug(
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f"Error processing message {message_id} data: {e}"
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)
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except Exception as e:
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except Exception as e:
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log.debug(f"Error scanning messages for file references: {e}")
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log.debug(f"Error scanning messages for file references: {e}")
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