🧠 Multimodal Retrieval-Augmented Generation that "weaves" together text and images seamlessly. 🪡

It allows users to upload PDFs and ask questions about the content within these documents.

Metallum/Metal-Archives scrapers, datasets, analysis and recommendations website

This project uses the CrewAI framework to automate stock analysis, enabling AI agents to collaborate and execute complex tasks efficiently. Example stock: Nvidia. Technologies include Python, CrewAI, Unstructured, PyOWM, Tools, Wikipedia, yFinance, SEC-API, tiktoken, faiss-cpu, python-dotenv, langchain-community, langchain-core, and OpenAI.

Budget Buddy is a finance chatbot built using Chainlit and the LLaMA language model. It analyzes PDF documents, such as bank statements and budget reports, to provide personalized financial advice and insights. The chatbot is integrated with Hugging Face for model management, offering an interactive way to manage personal finances.

Efficiently search and retrieve information from PDF documents using a Retrieval-Augmented Generation (RAG) approach. This project leverages DeepSeek-R1 (1.5B) for advanced language understanding, FAISS for high-speed vector search, and Hugging Face’s ecosystem for enhanced NLP capabilities. With an intuitive Streamlit interface and Ollama for mode

FOXO Agentic RAG assistant for document QA, weather-food tips, Fitbit CSV, life & nutrition.

This is a reasoning AI chatbot that uses Deepseek R1

AI-Powered Document Q&A Bot Stack: Python, LangChain, OpenAI, FAISS, Streamlit, FastAPI Highlights: Upload PDF → Chunk → Vectorize → Search → Answer using GPT Shows LLM, vector DB, chatbot flow Production-quality backend with LangChain and caching

Developed an intelligent AI chatbot utilizing the DeepSeek LLM, designed for efficient interaction with large documents such as textbooks and study materials. Integrated Docling for parsing and processing large files, and implemented a Retrieval-Augmented Generation (RAG) pipeline using FAISS and Sentence Transformers to optimize context retrieval

This is a chatbot finetuned to give answer to medical related questions

AnyBioinfoma is a Streamlit-based application that allows users to interact with a bioinformatics knowledge base. It uses Google Generative AI and FAISS for document embedding and retrieval.

A semantic movie recommendation system using NLP via (sentence-transformers + FAISS index).

CICD Answering-Question Chatbot for RAG (Retrieval-Augmented Generation) using Streamlit

Museo.ai is an AI-powered chatbot designed for efficient and seamless museum ticket booking. Built using HTML for the frontend and Python for the backend, Museo.ai provides an engaging user interface and powerful backend logic to handle booking requests, manage user interactions, and streamline the ticket purchasing process.

An easy way to understand vector store working and creation.

Creating basic microservices project structure for basic RAG chatbot

A web app that converts audio to text and enhances transcription with Retrieval-Augmented Generation (RAG). Upload audio, get accurate transcriptions with contextual enrichment using external knowledge sources