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https://github.com/arc53/DocsGPT.git
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refactor: break up monolithic routes.py into modular domain structure
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225
application/api/user/base.py
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225
application/api/user/base.py
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"""
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Shared utilities, database connections, and helper functions for user API routes.
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"""
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import datetime
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import os
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import uuid
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from functools import wraps
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from typing import Optional, Tuple
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from bson.dbref import DBRef
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from bson.objectid import ObjectId
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from flask import current_app, jsonify, make_response, Response
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from pymongo import ReturnDocument
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from werkzeug.utils import secure_filename
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from application.core.mongo_db import MongoDB
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from application.core.settings import settings
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from application.storage.storage_creator import StorageCreator
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from application.vectorstore.vector_creator import VectorCreator
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storage = StorageCreator.get_storage()
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mongo = MongoDB.get_client()
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db = mongo[settings.MONGO_DB_NAME]
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conversations_collection = db["conversations"]
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sources_collection = db["sources"]
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prompts_collection = db["prompts"]
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feedback_collection = db["feedback"]
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agents_collection = db["agents"]
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token_usage_collection = db["token_usage"]
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shared_conversations_collections = db["shared_conversations"]
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users_collection = db["users"]
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user_logs_collection = db["user_logs"]
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user_tools_collection = db["user_tools"]
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attachments_collection = db["attachments"]
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try:
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agents_collection.create_index(
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[("shared", 1)],
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name="shared_index",
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background=True,
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)
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users_collection.create_index("user_id", unique=True)
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except Exception as e:
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print("Error creating indexes:", e)
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current_dir = os.path.dirname(
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os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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)
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def generate_minute_range(start_date, end_date):
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"""Generate a dictionary with minute-level time ranges."""
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return {
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(start_date + datetime.timedelta(minutes=i)).strftime("%Y-%m-%d %H:%M:00"): 0
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for i in range(int((end_date - start_date).total_seconds() // 60) + 1)
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}
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def generate_hourly_range(start_date, end_date):
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"""Generate a dictionary with hourly time ranges."""
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return {
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(start_date + datetime.timedelta(hours=i)).strftime("%Y-%m-%d %H:00"): 0
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for i in range(int((end_date - start_date).total_seconds() // 3600) + 1)
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}
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def generate_date_range(start_date, end_date):
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"""Generate a dictionary with daily date ranges."""
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return {
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(start_date + datetime.timedelta(days=i)).strftime("%Y-%m-%d"): 0
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for i in range((end_date - start_date).days + 1)
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}
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def ensure_user_doc(user_id):
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"""
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Ensure user document exists with proper agent preferences structure.
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Args:
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user_id: The user ID to ensure
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Returns:
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The user document
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"""
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default_prefs = {
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"pinned": [],
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"shared_with_me": [],
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}
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user_doc = users_collection.find_one_and_update(
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{"user_id": user_id},
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{"$setOnInsert": {"agent_preferences": default_prefs}},
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upsert=True,
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return_document=ReturnDocument.AFTER,
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)
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prefs = user_doc.get("agent_preferences", {})
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updates = {}
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if "pinned" not in prefs:
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updates["agent_preferences.pinned"] = []
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if "shared_with_me" not in prefs:
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updates["agent_preferences.shared_with_me"] = []
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if updates:
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users_collection.update_one({"user_id": user_id}, {"$set": updates})
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user_doc = users_collection.find_one({"user_id": user_id})
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return user_doc
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def resolve_tool_details(tool_ids):
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"""
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Resolve tool IDs to their details.
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Args:
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tool_ids: List of tool IDs
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Returns:
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List of tool details with id, name, and display_name
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"""
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tools = user_tools_collection.find(
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{"_id": {"$in": [ObjectId(tid) for tid in tool_ids]}}
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)
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return [
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{
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"id": str(tool["_id"]),
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"name": tool.get("name", ""),
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"display_name": tool.get("displayName", tool.get("name", "")),
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}
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for tool in tools
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]
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def get_vector_store(source_id):
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"""
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Get the Vector Store for a given source ID.
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Args:
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source_id (str): source id of the document
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Returns:
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Vector store instance
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"""
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store = VectorCreator.create_vectorstore(
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settings.VECTOR_STORE,
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source_id=source_id,
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embeddings_key=os.getenv("EMBEDDINGS_KEY"),
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)
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return store
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def handle_image_upload(
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request, existing_url: str, user: str, storage, base_path: str = "attachments/"
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) -> Tuple[str, Optional[Response]]:
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"""
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Handle image file upload from request.
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Args:
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request: Flask request object
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existing_url: Existing image URL (fallback)
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user: User ID
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storage: Storage instance
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base_path: Base path for upload
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Returns:
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Tuple of (image_url, error_response)
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"""
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image_url = existing_url
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if "image" in request.files:
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file = request.files["image"]
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if file.filename != "":
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filename = secure_filename(file.filename)
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upload_path = f"{settings.UPLOAD_FOLDER.rstrip('/')}/{user}/{base_path.rstrip('/')}/{uuid.uuid4()}_{filename}"
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try:
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storage.save_file(file, upload_path, storage_class="STANDARD")
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image_url = upload_path
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except Exception as e:
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current_app.logger.error(f"Error uploading image: {e}")
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return None, make_response(
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jsonify({"success": False, "message": "Image upload failed"}),
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400,
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)
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return image_url, None
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def require_agent(func):
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"""
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Decorator to require valid agent webhook token.
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Args:
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func: Function to decorate
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Returns:
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Wrapped function
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"""
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@wraps(func)
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def wrapper(*args, **kwargs):
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webhook_token = kwargs.get("webhook_token")
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if not webhook_token:
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return make_response(
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jsonify({"success": False, "message": "Webhook token missing"}), 400
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)
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agent = agents_collection.find_one(
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{"incoming_webhook_token": webhook_token}, {"_id": 1}
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)
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if not agent:
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current_app.logger.warning(
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f"Webhook attempt with invalid token: {webhook_token}"
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)
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return make_response(
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jsonify({"success": False, "message": "Agent not found"}), 404
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)
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kwargs["agent"] = agent
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kwargs["agent_id_str"] = str(agent["_id"])
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return func(*args, **kwargs)
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return wrapper
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