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.

🎩 AIfred - Multi-Agent AI Assistant with TTS, RAG, Web Research & Voice capabilities. Supports Ollama, vLLM, TabbyAPI. Features AIfred/Sokrates/Salomo debate system.

IndexGPT: 本地 AI 科研助手（RAG + SFT + LoRA）| Local AI research assistant for PDF parsing, retrieval QA, SFT data generation, and LoRA training.

ArXiv Agent is a terminal-based intelligent assistant designed for researchers and engineers who want to stay on top of the latest AI trends without drowning in PDFs. It combines daily digests, RAG-powered chat, and automated implementation into a single, cohesive workflow.

Building AI Research Assistant: Multi-Agent RAG System Reading From Multiple Unstructured Sources

Extract equations and context from research papers for LLM coding assistants (arXiv, LaTeX, RAG)

The Canada Labour Research Assistant (CLaRA) is a privacy-first LLM-powered RAG AI assistant proposing Easily Verifiable Direct Quotations (EVDQ) to mitigate hallucinations in answering questions about Canadian labour laws, standards, and regulations. It works entirely offline and locally, guaranteeing the confidentiality of your conversations.

A conversational AI assistant for the openBIS research data management system. Uses RAG with Ollama to provide natural, accurate responses to queries about openBIS. Scrapes documentation, processes it into semantic chunks, and delivers helpful answers through a simple command-line interface.

This is your friendly research assistant multi-modal RAG application built with LLM

RAG-Based Research Assistant

AI-powered debate assistant using Groq, Gemini APIs, and SearchXNG for intelligent argumentation. Built with RAG (Retrieval-Augmented Generation) architecture to source academic research and data. Features real-time web search integration and upcoming Model UN debate simulation mode.

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AI-powered CLI assistant for system operations, research, and knowledge work with RAG and neurosymbolic reasoning.

AI research assistant that extracts structured patterns from papers using RAG, LangGraph, and Claude. Query across your research library with natural language.

Cyber Vision AI is an award-winning, open-source AI assistant for cybersecurity, document analysis, and knowledge management. Built with advanced RAG, MindMap, and multi-agent AI, it empowers security professionals and researchers with unrestricted, ethical, and insightful tools.

Research Assistant Agent is an AI-powered tool that retrieves, analyzes, and summarizes research papers using the Gemini API and RAG. It generates topic-based reports with related recommendations, summarizes PDFs with similar paper suggestions, and enables chat with research papers.

A multimodal RAG-based research assistant that extracts and understands text, tables, and images from PDFs using Gemini models. Built with LangChain, Chroma, and Streamlit to deliver accurate, context-aware answers from complex research documents.

AgenticRAG-ResearchAssistant is an advanced research assistant that uses an agentic RAG approach to answer research queries. It integrates a large language model with external tools for document retrieval, summarization, comparison, and citation analysis in a conversational interface.

This project implements a complete offline RAG-Fusion application for text generation and retrieval, leveraging efficient local resources.

An AI Research Paper Reading Assistant, using RAG and Arxiv API

AI-powered research assistant that not only processes academic papers and enables intelligent querying through RAG, but also automatically converts research methodologies into executable Python code implementations.

A context-aware RAG Research Assistant for deep analysis of dense technical documents. Optimized for academic workflows with structural awareness and persistent history.

AI Research Agent: An autonomous assistant that crawls arXiv papers and AI news, generates LLM summaries, performs RAG retrieval, and delivers insights via multi-platform bots.

An AI-powered Multi-Agent Research Assistant built with Generative AI, Agentic AI, LangGraph, RAG, Persistent Memory, FAISS, and FastAPI. It supports multi-format uploads, intelligent PDF analysis, and expert-like Q&A via Researcher, Summarizer, Critic, and Editor agents—offering deep, contextual, and interactive research insights.

AI Research Assistant is a multi-agent system built with LangChain, LangGraph, and LangSmith. It lets users ask research questions and returns search results, summaries, and synthesized reports in a ChatGPT-like Streamlit UI. Easily extendable with real APIs or RAG.

RAG-Research-Assistant

End-to-end Retrieval-Augmented Generation system using FastEmbed for embeddings, Gemini for LLM queries, Qdrant Cloud as vector DB, Prefect for ingestion pipelines, BigQuery for feedback storage, and Streamlit + Grafana for interactive dashboards.

基于RAG和LoRA微调的MRFO算法研究助手

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AI Research Assistant - RAG QA System