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Muhammad Suleman's Projects

go-html-server icon go-html-server

very basic project in go lang for the go server with form submission

htmltopdf icon htmltopdf

Provide the Url or html, it will convert it into PDF

mcqgen icon mcqgen

This project aims to automate the process of generating multiple-choice questions (MCQs) using Generative AI techniques. Users can upload a text file containing relevant content, and our system utilizes Streamlit for the frontend, Python for backend processing, LangChain, LLM (Large Language Model)

mcqwithwebsite icon mcqwithwebsite

Website-to-MCQs is an application built in Python that utilizes generative AI, Langchain, embedding techniques, and ChatGPT to automatically generate multiple-choice questions (MCQs) from website content.

mern icon mern

MongoDB Express React Node

nodejs-restapi-with-restify-mongoose-jwt icon nodejs-restapi-with-restify-mongoose-jwt

create a real REST API with database integration and token authentication using Node.js with Restify, Mongoose/MongoDB and JWT json web token. In this part we will create basic database CRUD and in the next we will implement users and authentication

ollamaraglocallargelanguage icon ollamaraglocallargelanguage

how to create a local RAG (Retrieval Augmented Generation) pipeline that processes and allows you to chat with your PDF file(s) using Ollama and LangChain!

pagedapi icon pagedapi

how to implement fake api testing with IEnumerableDisposable<out T> : IEnumerable<T>, IDisposable, Generics

qasimilaritysearch icon qasimilaritysearch

Question and Answer Similarity Search Application using pinecone vector database

qasimilaritysearchchroma icon qasimilaritysearchchroma

This project is dedicated to creating a robust Question and Answer (Q&A) similarity search application using Python including Jupyter Notebook, Chroma Database, Vector Database, LangChain, large language models, RetrievalQA, ChatGPT, OpenAI Embeddings, PyPDFDirectoryLoader, and RecursiveCharacterTextSplitter

realtimedatastreaming icon realtimedatastreaming

This project is an end-to-end data engineering pipeline that orchestrates data ingestion, processing, and storage using a suite of powerful tools and technologies. The pipeline is designed for ease of deployment and scalability, leveraging Docker to containerize all components.

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