Medium close using NEXTJS ,REACT, TYPESCRIPT , tailwindcss and sanity CMS [GROQ]

Concept Real Estate Agent lead generation website with CRUD integration. Built with React, JavaScript, Sanity.io CMS, GraphQL, TailwindCSS

This is my portfolio

Personal website to showcase my works and experiences.

Este repositório contém um aplicativo web desenvolvido com Streamlit que utiliza os modelos de linguagem Mixtral e Groq para diversas tarefas de processamento de linguagem natural (PLN

Movie finder app with semantic search and sentiment analysis using OpenAI GPT-3.5 Turbo, Groq, and Qdrant

Built with Next.js, Sanity.io, Tailwind & Vercel

NextJS, ReactJS, TypeScript, SanityCMS, TailwindCSS, Turborepo, GROQ, API Routes, Form Validation Hook

The Lightning ⚡️ AI Style Guide Assistant & Code Translator is a specialized adaptation of the Lightning Chatbot, designed to assist in maintaining consistency and accuracy in style guides. Leveraging Groq LPUs, it provides real-time style and grammar recommendations, making it an essential tool for editors and writers.

This Chrome Extension offers users powerful AI-driven features to summarize, translate, correct English, and pronounce text directly from any webpage.

Code for Sanity.io CMS for my developer portfolio content.

Super Fast 0-Shot AI assistant in the terminal

A cross-platform ChatGPT/Gemini UI (Web / PWA / Linux / Win / MacOS). 一键拥有你自己的跨平台 ChatGPT/Gemini 应用。

A Sanity plugin that lets you store and have quick access to frequently used or complex GROQ queries within your Sanity Studio.

My Sanity Blog

A fully functional Ecommerce web app using Next.js | Sanity | Stripe | Postgres | Drizzle | React-hot-toast | & more

Hands on some LLMs

In this end to end project I have built a RAG app using ObjectBox Vector Databse and LangChain. With Objectbox you can do OnDevice AI, without the data ever needing to leave the device.

This repository provides a framework to integrate internet search capabilities with a Language Learning Model (LLM), specifically using Gemini 1.5 API. This allows the LLM to fetch and use real-time data from the internet to enhance its responses to user queries.