Marky helps you convert things into Markdown 📝

Enhance GPT-3.5-Turbo output using Retrieval-Augmented Generation (RAG) with a user-friendly interface. Select between Wikipedia or integrate external documents to experience precise, context-aware responses.

This repo demonstrates how to use Document Loaders in LangChain to fetch data from sources like text, PDFs, directories, web pages, and CSV files, and convert it into a standard Document format with content and metadata for use with LLMs.

A comprehensive repository to learn and implement Retrieval-Augmented Generation (RAG) from scratch using LangChain. It covers the full RAG pipeline including Document Loaders, Text Splitters, Embeddings, Vector Databases, and Retrievers with practical examples and step-by-step explanations.

Step-by-step LangChain tutorials covering models, prompts, chains, retrievers, tools, and agents — theory to full implementation.

Load documents for RAG pipelines: PDF, DOCX, HTML, Markdown. Smart chunking, metadata extraction. LangChain compatible.

This repository covers all the code materials covered within Jose Portilla's Langchain with Python Bootcamp on Udemy.

Smart Quiz Generator is a Streamlit-based app that uses GPT-4 to create quizzes (MCQ, True/False, or Fill-in-the-Blank) from your own documents (PDF/TXT) or web pages. It processes content, stores it in a FAISS vector store for quick retrieval, and generates customized quizzes based on a chosen topic.

Successfully developed an LLM application which generates a summary, a list of citations and references and response to a user's query based on the research paper's content.

LangChain integration package for Synap DocuAnalyzer

RAG to talk to your code

LangChain integration for Ujeebu Extract API - extract clean, structured content from web articles for use with LLM agents and RAG pipelines.

Successfully developed a Multi-Domain AI Personal Assistant using LangChain, OpenAI, and Streamlit. The application seamlessly integrates multiple specialized capabilities, including document-based question answering (QA), Python code execution, debugging, explanation and optimization, web search, latest news retrieval, and currency conversion.

Examples of top-used LangChain document loaders including CSVLoader, DirectoryLoader, PyPDFLoader, TextLoader, and WebBaseLoader. These loaders standardize raw data into LangChain Document objects for further processing, splitting, embeddings, and RAG workflows.

A LangChain community document loader for Google Classroom. Extract coursework, materials, and Drive attachments for RAG pipelines.

LangChain integration for Ujeebu web scraping and content extraction APIs

A content navigator powered by GPT-3.5-Turbo to explore multiple documents uploaded using Streamlit UI. It uses `Document Array Memory` for small and `Pinecone` for large document pools and delivers concise, referenced search results.

Gen AI with framework Langchain

📄 Summarize research papers, extract citations, and answer queries with this AI-powered assistant built using LangChain and OpenAI's GPT model.