Python SDK for Milvus Vector Database
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Updated
May 29, 2025 - Python
Python SDK for Milvus Vector Database
A Model Context Protocol (MCP) server that enables AI assistants to interact with HubSpot CRM data, providing built-in vector storage and caching mechanisms help overcome HubSpot API limitations while improving response times.
An AI agent that writes SEO-optimised blog posts and outputs a properly formatted markdown document.
A tool for summarizing search results and website content using FAISS, LLMs, and the Retrieval-Augmented Generation (RAG) technique.
This is a RAG project to chat with your uploaded PDF , made using Langchain and Anthropic Claude 3 used as LLM , hosted using Streamlit
Webapp to answer questions about my resume leveraging Langchain, OpenAI, Streamlit
LLM graph-RAG SQL generator for large databases with poor documentation
Q&A System using BERT and Faiss Vector Database
AI Lawyer is an intelligent reasoning legal assistant powered by DeepSeek , Ollama RAG and LangChain, designed to streamline legal research and document analysis. By leveraging retrieval-augmented generation (RAG), it provides precise legal insights, and contract summarization. With an intuitive Streamlit-based UI, analyze legal documents.
It allows users to upload PDFs and ask questions about the content within these documents.
Advanced RAG pipeline using Re-Ranking after initial retrieval
This repo is for advanced RAG systems, each branch will represent a project based on RAG.
BankLLM is an AI-driven recommendation engine for banking, using OpenAI's models to analyze customer data and generate personalized product suggestions. It integrates LangChain, FAISS, and LangServe, with a FastAPI backend and Streamlit frontend, following an LLMOps approach for scalable deployment.
Implementing LangChain concepts and building meaningful stuffs
Generative AI projetc using LangChain for similarity search. Input 3 articles urls and ask something about the topic
RAG-based Local PDF Chatbot: Supports multiple PDFs and concurrent users. Powered by Mistral 7B LLM, LangChain, Ollama, FAISS vector store, and Streamlit for an interactive experience.
ChatPDF leverages Retrieval Augmented Generation (RAG) to let users chat with their PDF documents using natural language. Simply upload a PDF, and interactively query its content with ease. Perfect for extracting information, summarizing text, and enhancing document accessibility.
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In this project I have built an app that can answer questions from your multiple PDFs using Google's gemini-1.5-flash model.
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