Official code for ACL2025 "🔍 Retrieval Models Aren’t Tool-Savvy: Benchmarking Tool Retrieval for Large Language Models"
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Updated
Dec 22, 2025 - JavaScript
Official code for ACL2025 "🔍 Retrieval Models Aren’t Tool-Savvy: Benchmarking Tool Retrieval for Large Language Models"
🐸 KERMIT - A lightweight library to encode and interpret Universal Syntactic Embeddings
A CLI chatbot that uses RAG architecture for improving and adapting LLM to specific context. It allows users to ask questions and get response directly from open-source LLMs(OpenAI, MistralAI etc.) or from the information on a website which is provided as context using the RAG architecture.
The goal of this application is to generate suggestions based on the given resume of the candidate, store the candidate profile in Pinecone database, and shortlist candidates accroding to the skills matched with match score.
A full-stack AI chatbot built with React and Node.js, powered by Google's Gemini API. Supports normal conversational chat with streaming responses, and lets you upload a PDF to ask questions grounded in its content using Retrieval-Augmented Generation (RAG).
Prepverse.AI is an AI-powered internship discovery and preparation platform that parses resumes, smart internship recommendations, and sends real-time email and WhatsApp alerts. It also offers AI mock interviews, resume optimization, and quizzes to help students prepare for opportunities.
Graph-Enhanced Enterprise AI Automation Platform — GraphRAG 3.2 + Azure OpenAI + FastAPI + React
A production-ready RAG (Retrieval-Augmented Generation) chatbot built for ThinklyLabs
AI-powered full-stack smart wardrobe and outfit recommendation system built using React, Node.js, FastAPI, and ML embeddings.
Mini rag, small on purpose ;)
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