A basic sales agent application using Streamlit for the user interface and LangChain for the AI component. The agent should be able to: . Engage in basic conversations with potential customers, answering questions about products or services. . Provide product information based on customer inquiries.

AI-powered content research and writing assistant built with CrewAI and Streamlit.

Complete Streamlit cheat sheet with Code

[SKN 19기 2차 프로젝트 2팀] 흡연 이탈(흡연 → 비흡연) 예측 프로젝트

This project aims to predict house prices based on various features such as area, number of bedrooms, bathrooms, access to main road, and more. The model uses linear regression and standard scaling for input data.

Iris Classification Pipeline, Streamlit App & FastAPI

Chat with Multiple PDFs : VMchat with multiple PDFs by uploading files, extracting their text, and asking questions to get intelligent, context-aware answers.

Play with Duck DB and others

Summarize YouTube videos in seconds using AI.

This app is built to simplify the task of summarizing textual content from YouTube videos and websites. By integrating LangChain with the Groq API for natural language processing (NLP), it delivers concise and efficient summaries from a variety of content sources.

LLM-based AI Healthcare Assistant

🤖 Automate customer support with AI-driven agents using OpenAI AgentKit for seamless workflows and real-time performance monitoring.

Prepared for account Generation Process of iStudy

GenAI based search engine

This is a Streamlit web app that generates personalized diet plans based on user inputs like age, gender, weight, height, and activity level. It calculates BMI, daily calorie needs, and recommends meal plans to help maintain or achieve weight goals.

It performs few shot learning for me.