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๐Ÿค– InQuest Interview Application

Introduction

InQuest Interview is an AI-driven interview application designed to enhance the interview process by leveraging advanced technologies. The application utilizes FastAPI for the backend, Docker for containerization, and is deployed on Google Cloud Platform (GCP). It features a Retrieval-Augmented Generation (RAG) framework using Langchain, Qdrant, and Redis to provide better interview responses based on job descriptions and resumes. Additionally, it integrates Azure Speech AI for text-to-speech and Whisper for speech-to-text capabilities, making it a comprehensive tool for conducting audio-enabled interviews.

Features

  • ๐Ÿค– AI-driven interview responses: Improves responses by utilizing job descriptions and resumes.
  • ๐Ÿ” RAG Framework: Enhances interview accuracy using Langchain, Qdrant for vector storage, and Redis for chat memory.
  • ๐ŸŽค Audio Functionality: Integrates text-to-speech with Azure Speech AI and speech-to-text with Whisper.
  • ๐Ÿณ Containerized Deployment: Uses Docker for easy deployment and scalability.
  • โ˜๏ธ Cloud Deployment: Hosted on Google Cloud Platform (GCP) for reliable and scalable performance.

Tech Stack

  • Backend: FastAPI
  • Containerization: Docker
  • Cloud Provider: Google Cloud Platform (GCP)
  • Framework: Langchain
  • Vector Storage: Qdrant
  • Chat Memory: Redis
  • Text-to-Speech: Azure Speech AI
  • Speech-to-Text: Whisper
  • Frontend: Next.js

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