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openaiembeddings

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Talk_with_PDF is a powerful, AI-driven solution designed to automate the extraction of information and generation of answers based on PDF documents. By integrating OpenAI's advanced language models and embeddings, this system provides accurate and contextually relevant responses, making it an invaluable tool for education, business, and research.

  • Updated May 22, 2024
  • Python

A ChatGPT-powered QA system using OpenAI, LangChain, FastAPI, and a vector database. It retrieves answers based on stored data, enhancing responses with relevant source links. The project enables efficient knowledge retrieval, making it ideal for AI-driven chat applications that require accurate and reference-backed responses.

  • Updated Mar 27, 2025
  • TypeScript

This Python Flask application is designed to process and rank resumes based on job descriptions. It uses Azure's Document Analysis Client for document processing, and a MongoDB database for storing job descriptions and resumes. The application also generates embeddings for the processed documents using AzureOpenAI.

  • Updated Mar 21, 2024
  • Python

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