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This project automates helpdesk ticket response generation using Selenium for ticket scraping, BART for summarizing email threads, and Ollama for generating professional responses. It also utilizes TF-IDF for finding similar past tickets to suggest relevant solutions. The goal is to streamline helpdesk workflows by providing accurate solutions

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donneypr/helpdesk_llama

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IT Ticket Reply Automation System

This project automates the process of generating responses for IT helpdesk tickets. By leveraging Natural Language Processing (NLP) models, the system scrapes ticket data, summarizes email threads, and creates AI-generated replies to enhance the efficiency of IT support workflows.

Features

  • Automated Ticket Scraping and Summarization: Extracts ticket data and summarizes email threads using a BART model for quick and accurate response generation.
  • AI-Powered Reply Generation: Utilizes a LLaMA model to craft responses based on the summarized email content and similar past resolutions.
  • Response Similarity Scoring: Measures the similarity between AI-generated replies and previous resolutions using TF-IDF vectorization and cosine similarity.
  • Interactive User Prompts: Allows users to accept the AI response, modify it with custom input, or regenerate a response.

Installation

  1. Clone the Repository:
    git clone https://github.com/donneypr/it-ticket-reply-automation.git
    cd it-ticket-reply-automation

Youtube Demo

https://www.youtube.com/watch?v=3kAdUtIVyyI

About

This project automates helpdesk ticket response generation using Selenium for ticket scraping, BART for summarizing email threads, and Ollama for generating professional responses. It also utilizes TF-IDF for finding similar past tickets to suggest relevant solutions. The goal is to streamline helpdesk workflows by providing accurate solutions

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