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This repository contains the implementation of the Response Generator system, which generates responses for non-sensitive emails using a Retrieval Augmented Generation (RAG) system.

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Angelos

This repository contains the implementation of the Response Generator system, which generates responses for non-sensitive emails using a Retrieval Augmented Generation (RAG) system. The RAG system retrieves relevant information from specific documents and websites to construct accurate and helpful replies.

Features

  • Automated Response Generation: Generates responses for non-sensitive emails using the RAG system.
  • Integration with Categorizer: Receives non-sensitive emails from the Email Categorizer system for processing.
  • Information Retrieval: Utilizes specific documents and websites to gather relevant information for responses.

Objectives

  • Improve response efficiency by automating replies to non-sensitive emails.
  • Ensure responses are accurate and contextually relevant by leveraging the RAG system.
  • Maintain a high standard of data privacy and user consent.

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This repository contains the implementation of the Response Generator system, which generates responses for non-sensitive emails using a Retrieval Augmented Generation (RAG) system.

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