Automated Service Note Transformation System
Transforming Technical Complexity into Customer Clarity
Client
Developed for a physical security company to reconcile customer accounts.
My Role
Full-Stack Development
Project Overview
This script is a critical component of a larger customer communication system that addresses the challenge of converting internal technical documentation into customer-appropriate messaging. It leverages the open-source Llama 3.5 model and implements several sophisticated features:
Core Functionality
- Advanced Language Model Integration: Utilizes Llama 3.5, a state-of-the-art open-source LLM, for transforming technical jargon and internal notes into clear, professional customer communications
- Context-Aware Processing: Implements specialized handling for specific alert types (e.g., device offline scenarios) with predefined response templates
- Database Integration: Maintains seamless connectivity with a MySQL database for persistent storage and retrieval of both original and transformed communications
- Professional Tone Enforcement: Employs specific prompt engineering to ensure communications maintain an authoritative and confident tone while avoiding apologetic language
Implementation Details
- Open-Source AI Integration: Leverages the Llama 3.5 model, demonstrating proficiency with cutting-edge open-source AI technologies
- Structured Data Processing: Implements XML-style tagging for subject and description separation, ensuring clean data organization
- Error Handling: Includes comprehensive exception management for both model interactions and database operations
- Version Control: Maintains revision tracking through an integrated counter system in the database
Business Value
This script serves as a crucial bridge between technical operations and customer communications, providing several key benefits:
- Ensures consistent, professional communication regardless of the internal note quality
- Reduces the time required to transform technical documentation into customer-ready format
- Maintains technical accuracy while improving accessibility of information
- Demonstrates cost-effective use of open-source AI technology for business process automation
Prompt
if ‘Vox devices offline’ in subject or ‘Vox devices offline’ in description:
special_prompt = “When we receive an alert that Vox devices are offline we need tell the customer minimal information and let them know we are running diagnostics.”
elif ‘device(s) down’ in subject or ‘device(s) down’ in description:
special_prompt = “When we receive an alert that devices are down we need to tell the customer minimal information and let them know we are running diagnostics.”
else:
special_prompt = “”prompt = (f”Transform the following technical subject and description into simple, customer-friendly language. {special_prompt}”
f”The customer is a property management company that manages multiple large apartment complexes. “
f”The following data is for a large appartment complex. Dishes and point-to-points describe wifi network devices. “
f”Don’t be appologetic or use words like ‘unfortunately’, ‘sorry’ or ‘apologize’. You are authoritative and confident. “
f”We will never ask the customer to fill out a form, links to forms are for internal use only.\n\n”
f”If a form is being mentioned it should be assumed that our technical team has completed it.”
f”Place the transformed subject within ‘<subject>’ and ‘</subject>’ tags, “
f”and the transformed description within ‘<description>’ and ‘</description>’ tags. “
f”Ensure the explanations are clear, concise, and non-alarming, even if they mention potential issues. “
f”Aim for a tone that is informative and reassuring.\n\n”
f”Technical Subject: {subject}\n”
f”Technical Description: {description}\n\n”
f”Customer-Friendly Version:”)