AI-Powered Job Recommendation System An intelligent job recommendation system that analyzes PDF resumes and suggests the best job opportunities using NLP, FAISS, and Sentence Transformers.
Este projeto permite realizar perguntas em linguagem natural sobre o conteúdo de arquivos PDF. Utiliza a abordagem RAG (Retrieval-Augmented Generation)
It allows users to upload PDFs and ask questions about the content within these documents.
CICD Answering-Question Chatbot for RAG (Retrieval-Augmented Generation) using Streamlit
🧠 Multimodal Retrieval-Augmented Generation that "weaves" together text and images seamlessly. 🪡
A lightweight image search engine that lets you upload a dataset and find similar images using either text queries or image queries, powered by CLIP embeddings, FAISS vector search, FastAPI, and a Streamlit UI.
Creating basic microservices project structure for basic RAG chatbot
RAG-based chatbot for financial report analysis using LangChain, FAISS, and Groq LLM.
This is a reasoning AI chatbot that uses Deepseek R1
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
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
A Streamlit-based Retrieval-Augmented Generation (RAG) application that enables users to upload PDF or image files, extract text using Tesseract OCR for images and embedded images in PDFs, and query the content using the Kimi-K2-Instruct model from Moonshot AI via HuggingFace's InferenceClient.
Generate paper based on the past question paper
Survey & Experimental Analysis of Maximum Inner Product Search (MIPS) Methods
Successfully developed a Healthcare AI Clinical Decision Support System, leveraging LangGraph, GPT-4o-mini, and PubMed to deliver real-time patient risk stratification, evidence-based treatment recommendations, and personalized clinical road maps with integrated drug safety validations.
It is an ML_Chatbot that explains concepts and terminologies using open-source tools. Used Hugging Face for embeddings, FAISS CPU for vector storage, and Mistral with streamlit for a conversational interface.
A high-performance image deduplication pipeline using ResNet50 features, FAISS vector search, and Graph Clustering. Optimized for 100k+ datasets on Apple Silicon & CUDA.
Multi Document RAG Application
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