LangGraphProjects

This code example shows how to make a chatbot for semantic search over documents using Streamlit, LangChain, and various vector databases. The chatbot lets users ask questions and get answers from a document collection. The code is in Python and can be customized for different scenarios and data.

This is a project that uses the LangChain library and OpenAI's ChatGPT API to perform data analysis on a dataset. Disclaimer: This project was made before OpenAI released Code Interpreter on ChatGPT Plus. With similar functions.

This Python project demonstrates semantic search using MongoDB and two different LLM frameworks: LangChain and LlamaIndex. The goal is to load documents from MongoDB, generate embeddings for the text data, and perform semantic searches using both LangChain and LlamaIndex frameworks.

This is the repository for a Streamlit application that helps with job applications. This app integrates OpenAI LLMs for building tailored resume and cover letter for a Job description.

This repository contains an innovative chat application integrating the power of OpenAI's GPT-3.5 model with Langchain's ConversationalRetrievalChain for intelligent and context-aware interactions. The application is built using the Flet framework, enabling a seamless cross-platform chat interface for web, desktop, and mobile platforms.

This is a Python - based application that allows the user to search for information and open URLs.