I want to edit this specification : Overview
Emailer is an email management application that leverages Large Language Models (LLMs) to provide intelligent email classification, analysis, and reporting. Specifically Llama 3.1 served via the Ollama server on localhost, Emailer ensures data security while providing robust features for users to manage their emails efficiently.
Scope
Emailer is intended for individual users and organizations seeking an intelligent solution to manage large volumes of emails. The application provides features such as real-time email processing, customizable classification, detailed reporting, and secure data handling.
Features
1.	User Account Management
Create Account: Users can sign up by selecting their email provider, entering a username, email, and password.
2.	Email Integration
Email Fetching: Support for multiple email providers (Gmail, Outlook, etc.) using IMAP and POP3 protocols.
Real-Time Processing: Immediate fetching and processing of incoming emails.
3.	Email Pre-processing
Parsing: Extraction of email headers, body content, and attachments for thorough analysis.
4.	User Customization
Custom Classification Categories: Users can define their own categories for email classification.
User-Defined Filters: Filters based on sender, date, subject, and topic.
Manager Mail Addition: Ability to add manager email addresses for report distributions.
5.	Intelligent Classification & Analysis
LLM Integration: Utilization of Llama 3.1 for email classification.
6.	Data Storage
Database Management: Use of SQLite to store user profiles, emails, and classification results securely.
7.	User Interface
Email Display: Emails displayed with classification tags for easy identification.
Visualization: Use of tables and charts to represent classification results.
8.	Reporting & Notifications
Scheduled Reports: Automatic generation and sending of email classification summaries to manager emails.
Urgent Email Reminders: Notifications for emails marked as urgent, negative, or important based on user-defined thresholds.
Technology Stack
	Programming Language: Python
	Large Language Model (LLM): Llama 3.1
	Model Server: Ollama
	Database: SQLite
	Email Protocols: IMAP, POP3 (based on email provider support)
	Frontend Framework: PyQt6
System Architected 
 
Data Management
	User Profiles: Store user information securely in the SQLite database.
	Email Data: Store fetched emails, including headers, body, and attachments.
	Classification Results: Store classification tags and analysis data linked to each email.
	Data Backup: Implement regular backups of the SQLite database to prevent data loss.
User Interface Requirements
Dashboard: Overview of email statistics, recent classifications, and notifications.
Email Viewer: Interface to view individual emails with classification tags.
Filters and Search: Tools to filter and search emails based on user-defined criteria.
Customization Settings: Sections for users to define classification categories and filters.
Reporting Section: Access to generated reports and notification settings.
Account Management: Interface for users to manage their account details and preferences.
Integration and APIs
Email Providers Integration: Utilize IMAP and POP3 protocols to fetch emails from supported providers.
LLM Integration: Interface with the Ollama server to access and utilize Llama 3.1 for classification tasks.
Reporting Services: Integrate with email services to send scheduled reports and urgent notifications.
Deployment
Local Deployment: The application is designed to run locally on user machines, ensuring data remains secure.
Environment Requirements:
	Python environment with necessary dependencies.
	Ollama server setup for Llama 3.1.
	SQLite database setup.


Installation Process:
	Package the application with an installer that sets up the Python environment, dependencies, Ollama server, and FastAPI server. 
	Provide configuration guides for connecting to email providers.
 the new editing:  Classification following the provider or the subject, … etc.

Analyze the email and classify following the urgency or the severity

Smart & Nice presentation following:
 the date (time, day, week, month, year …) 
Provider and subjects
History
…

Gradian: follow the communication of an employee on certain account (customer or 
       any critical account) and be warned in case of urgent situation

Emailer classifier Search emails from <PRESIDIO_ANONYMIZED_EMAIL_ADDRESS>
@@ Year=2023 to 2024
 result : email sorted and classification score Search emails from <PRESIDIO_ANONYMIZED_EMAIL_ADDRESS>
@@ subject = Ougarit
 result : email sorted and classification score Emailer gardian Gardian of the email of  <PRESIDIO_ANONYMIZED_EMAIL_ADDRESS>
@@ subject = Samsung
Shared with the Manager: <PRESIDIO_ANONYMIZED_EMAIL_ADDRESS> 
 with the urgent score