Research tools and examples

AI-Researcher is an LLM research automation framework and scientific workflow orchestrator designed to automate the end-to-end discovery process. It employs autonomous AI research agents to identify research gaps, formulate hypotheses, and execute scientific discovery workflows independently. The system integrates an automated literature review tool for gathering and analyzing academic papers and code repositories with an AI-driven manuscript generator that synthesizes research motivations and experimental results into full-length academic papers. The framework covers a modular research pipe

Zotero is reference management software designed for collecting, organizing, and citing bibliographic research sources and digital documents for academic work. It functions as a web bibliographic collector, a citation generator, and a collaborative research platform. The system integrates tools for capturing metadata and archiving web pages into a centralized research library. It provides a specialized environment for reading and marking up PDF and EPUB files with highlights and notes linked directly to research sources. The software covers a broad range of capabilities including bibliograph

This project is a desktop-based bibliographic reference manager designed to organize academic research libraries and automate citation workflows. It functions as a research assistant that integrates directly with word processors and text editors, enabling users to insert and format references while writing. The application is built on a Java-based portable runtime, allowing it to operate as a self-contained tool that stores preferences and data in local configuration files. The platform distinguishes itself through a modular plugin architecture and a commitment to human-readable, text-based f

GPT Researcher is an autonomous agent framework designed to automate the process of gathering, synthesizing, and documenting information from diverse web and local sources. It functions as a research-oriented execution environment that orchestrates specialized agents to perform complex, multi-branch research tasks, transforming raw data into structured, factual, and cited reports. The project distinguishes itself through a graph-based orchestration layer that manages state transitions and information flow between specialized agents. It employs recursive tree-search execution to explore comple

Local Deep Research is an autonomous research system consisting of an LLM research agent, a local model orchestrator, and a multi-engine search aggregator. It is designed to execute deep research by decomposing complex questions into atomic facts and synthesizing cited reports from academic, technical, and private document sources. The system features an encrypted research workspace that ensures zero-knowledge privacy through isolated, per-user encrypted databases. It utilizes a local RAG knowledge base to index research sources into searchable vector stores, allowing for retrieval-augmented

Open-deep-research is an autonomous research orchestrator and language model-based agent designed to execute multi-step investigations and automated web research workflows. It explores complex topics systematically by generating targeted search queries, processing multiple sources simultaneously, and recursively feeding synthesized findings back into search planning loops to expand its research scope. The system coordinates these tasks through a graph-based agent orchestration model that routes state between modular nodes for searching, reading, and reasoning. It accelerates data collection v

Open-deep-research is an automated research platform that utilizes autonomous agents to perform recursive web queries and synthesize information into structured reports. The system functions as an AI-powered research agent, capable of navigating complex topics by iteratively generating follow-up search queries and mapping interconnected findings. The platform distinguishes itself through a recursive orchestration model that allows for deep exploration of subjects beyond initial search results. It provides a unified interface for both cloud-based and local inference engines, enabling users to

This project is an LLM research orchestrator and autonomous AI agent framework designed to automate the scientific lifecycle. It functions as an end-to-end research pipeline and model training toolkit, managing everything from initial literature reviews and hypothesis testing to the final drafting of academic papers. The system is distinguished by its ability to convert unstructured academic PDFs into machine-executable knowledge layers, allowing agents to reproduce and extend research findings. It employs a two-loop orchestration architecture and a specialized research engineering skill libr

Deep research is an automated research generation system that uses large language models and web search engines to synthesize comprehensive reports and deep-dive analyses on complex topics. It combines real-time web search results with uploaded local documents to ground generated content in specific factual data. The system employs an iterative research workflow to refine reports through a step-by-step process of editing, updating, and restarting specific research stages. It can transform unstructured report data into knowledge graph visualizations to map relationships between different findi

Research paper summariser application for our hackathon and much more.

pdfplumber is a PDF data extraction library and layout analysis tool used to retrieve text, tables, and geometric objects from PDF files using precise coordinate-based analysis. It functions as a layout analyzer and table parser that identifies the bounding boxes and visual coordinates for every character and image on a page. The library distinguishes itself through visual debugging capabilities, allowing users to render PDF pages as images and draw annotations to verify the position of extracted data. It employs line and intersection analysis to identify cell structures and convert unstructu