Accepted as a NeurIPS 2025 Spotlight paper and rapidly approaching 6,000 GitHub stars, AI-Researcher from the Hong Kong University Data Science Lab delivers the first fully autonomous scientific research system — a multi-agent platform that takes a list of reference papers and returns a complete research contribution with working code, validated experiments, and a formatted academic manuscript. The pipeline orchestrates five distinct phases: a Resource Collector systematically gathers materials from arXiv, IEEE Xplore, ACM Digital Library, Google Scholar, GitHub, and Hugging Face; an Idea Generator performs gap analysis against semantic embeddings to produce 3-5 novel hypotheses with feasibility scores; an Algorithm Designer transforms concepts into functional implementations; a Validation Engine automates testing, performance evaluation, and iterative optimization; and a Manuscript Creator generates polished full-length papers with figures, tables, and citations. The Gradio-based web GUI provides intuitive tabs for environment configuration, example selection, and real-time monitoring of research progress, while the production deployment at novix.science offers immediate browser access without local setup. Scientist-Bench provides a standardized benchmark comprising state-of-the-art papers across diverse AI research domains for evaluating autonomous research capabilities. The system supports multiple LLM providers including OpenAI, Anthropic, Google Gemini, and OpenRouter models with per-task routing for cost optimization. Deploy via Python with pip dependencies or Docker containerization. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Execute comprehensive multi-angle investigations across scientific journals and web repositories using Local Deep Research, an autonomous intelligence engine designed for researchers, analysts, and knowledge workers. Users can submit complex analytical questions through a self-hosted web console to initiate agentic research cycles powered by LangGraph workflows. The application dynamically queries search providers including SearXNG, arXiv, PubMed, Wikipedia, and Google, iteratively evaluating discovered content to formulate targeted follow-up queries. Discovered academic papers and web sources can be indexed into an encrypted personal library to combine internal documentation with external search intelligence. Reports are synthesized with structured outlines, section headings, and verifiable academic citations that link directly to source references. Individual research sessions, system logs, and user credentials remain isolated in per-user SQLCipher databases protected by AES-256 encryption. Automated subscriptions deliver scheduled news digests and topic monitoring summaries directly to connected notification channels. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

A question goes in; a cited, long-form report comes out - GPT Researcher is an open-source autonomous research agent. A planner agent decomposes the query into sub-questions, execution agents crawl 20+ web sources in parallel with JavaScript-enabled scraping, and a publisher aggregates findings into a 2,000+ word report with inline citations, exportable to PDF, Word, and Markdown. The Deep Research mode extends this recursively: each result yields follow-up questions that are explored to configurable breadth and depth in a tree pattern, while accumulated learnings, citations, and visited URLs are shared across branches. It also researches local documents (PDF, CSV, Word) alongside the web. LLM and search providers are pluggable, including OpenAI, Anthropic, Google, DeepSeek, and Ollama for models, and Tavily, Google, Bing, DuckDuckGo, and SearXNG for retrieval. It ships as a Python package, a FastAPI server with web frontend, a Docker image, and an MCP server for use inside Claude or Cursor. MIT-licensed.

The most feature-complete open-source alternative to Google's NotebookLM — a self-hosted research platform where you upload PDFs, videos, audio files, and web pages into organized notebooks, then chat with your content, generate multi-speaker podcasts, and run semantic search across everything without sending a single byte to Google's servers. The podcast engine supports 1-4 fully customizable speakers with backstories, personalities, and expertise profiles, generating professional audio dialogue through OpenAI, ElevenLabs, Google TTS, or completely local text-to-speech via Kokoro for maximum privacy. Content processing uses token-based chunking with RAG-powered retrieval grounded in your uploaded sources, while both full-text keyword search and semantic vector search via SurrealDB enable conceptual discovery across all notebooks. The 18+ supported AI providers include OpenAI, Anthropic, Google Gemini, Groq, Ollama, LM Studio, and more — configurable per task so you can route cheap models to summarization and powerful models to analysis. Content transformations extract insights, generate summaries, create study guides, and produce structured outputs from any source material. The MCP integration connects Open Notebook to Claude Desktop, VS Code, and other MCP clients for seamless workflow integration. A full REST API on port 5055 enables complete automation of notebook management, source upload, and podcast generation. Deploy via Docker Compose with the application container, SurrealDB v2 on RocksDB, and optional TTS containers. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Positioned as the open-source NotebookLM alternative for AI agents, SurfSense delivers a live web research platform where your agents access structured data from Reddit, YouTube, Instagram, TikTok, Amazon, Walmart, Google Maps, Google Search, Indeed, and any page on the open web through one REST API or MCP server. Scheduled and event-triggered agents transform findings into briefs, alerts, podcasts, and presentations, while a built-in knowledge base keeps every discovery searchable with Perplexity-style cited answers using hybrid semantic and full-text search powered by PostgreSQL with pgvector. Upload PDFs, Office documents, images, and audio files, or sync Google Drive, OneDrive, and Dropbox — 50+ file formats supported with AI file sorting that auto-organizes documents by source, date, and topic. The MCP server exposes scrapers, knowledge base, and workspaces as native tools for Claude, Cursor, and any MCP-compatible agent. Cross-country proxy rotation handles Reddit, TikTok, and Google Search scraping with geo-aware sticky sessions and captcha-aware anti-bot handling. The platform features collaborative chats, multi-format document export, git-native knowledge base with Open Knowledge Format export, and a desktop quick-ask panel with global shortcut. Docker Compose deployment manages nine services including Caddy proxy, PostgreSQL, Redis, FastAPI backend, Celery workers, zero-cache real-time sync, and Next.js frontend with automatic Watchtower updates. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

A self-hosted "second brain": Khoj indexes your own files and answers questions from them, parsing Markdown (whole Obsidian vaults included), org-mode, PDF, Word, plain text, Notion pages, GitHub repositories, and images described by a vision model, then embedding everything with sentence-transformers into a vector index for semantic search and RAG with cited sources. Any LLM backend works: local models like Llama, Qwen, or Mistral via Ollama, or cloud models like GPT, Claude, and Gemini. You can build custom agents, each with its own persona, scoped knowledge base, chat model, and tools such as web search and code execution. Scheduled automations run recurring research and deliver newsletters or notifications to your inbox, and research mode performs multi-hop web searches with inline citations. Access it from a browser, the Obsidian plugin, Emacs, desktop, or WhatsApp - all clients connect to the same self-hosted instance, making Khoj one of the few AI assistants Emacs users can point at decades of org files. Semantic search means recall works without exact keywords: "that paper about forecasting with transformers" surfaces the right PDF even when you cannot remember its title. Switching LLM backends never requires re-indexing your documents, and with a local model via Ollama, even inference stays on hardware you control - journals, research, and private notes are never sent anywhere. Python/FastAPI stack, AGPL-licensed, with PostgreSQL storage.

Chat with your own documents: AnythingLLM, from Mintplex Labs, wraps retrieval-augmented generation (RAG) in an open-source application anyone can run. You organize content into workspaces, each an isolated namespace with its own documents, vector embeddings, chat history, and settings, so one instance can hold several separate knowledge bases. Upload PDFs, DOCX, TXT, and other formats, or scrape web pages; the built-in collector parses and chunks them into a vector database (LanceDB by default, with Pinecone, Chroma, Qdrant, and others supported). Answers cite their source documents. It works with both cloud LLMs (OpenAI, Anthropic, Gemini) and local ones via Ollama or LM Studio, and the embedding model is separately configurable. Beyond RAG chat, it includes AI agents that can browse the web and run tools, an embeddable chat widget for your website, a developer API, and multi-user mode with admin, manager, and default roles plus per-workspace access control. Context assembly is smarter than naive RAG: pinned documents, attached files, vector search hits, and recent chat history are combined under a token budget so the model's context window is filled efficiently, and each workspace supports multiple independent conversation threads against the same knowledge base. Because the embedding model, vector store, and chat LLM are all independently swappable, you can move between providers without re-ingesting a single document. The stack is Node.js with a React frontend, MIT-licensed.

Kotaemon is a document QA platform that combines advanced RAG techniques with a clean Gradio-based web interface for chatting with your documents. Built by Cinnamon, the Python backend supports any LLM provider including OpenAI, Azure OpenAI, Cohere, Groq, and local models via Ollama and llama-cpp-python, with a model management panel for configuring LLM and embedding providers from the UI. The default hybrid RAG pipeline combines full-text keyword retrieval with vector similarity search and applies re-ranking to ensure optimal result quality, while multi-modal document parsing extracts content from tables and figures alongside text. Advanced citations link every answer to specific source passages with relevance scores, viewable directly in the built-in PDF viewer with highlighted text spans. GraphRAG indexing via NanoGraphRAG, LightRAG, or Microsoft GraphRAG builds knowledge graphs from document collections for relationship-aware retrieval. Agent-based reasoning supports question decomposition for multi-hop queries using ReAct and ReWOO strategies. Multi-user authentication organizes documents into private and public collections with sharing and collaboration features. The platform supports Docker deployment in lite, full, and Ollama-bundled variants, runs on port 7860, and stores application data in a persistent volume. MCP tool integration enables external system connections for extended retrieval capabilities. On RepoCloud, deploy Kotaemon on a dedicated VPS with Docker, root SSH access, and complete control over your document AI infrastructure, all under the Apache 2.0 license.

Adobe Acrobat and Smallpdf, answered by a self-hosted Java web application: Stirling PDF processes every file with its 60+ tools on your own server and deletes it after the task completes. Nothing is uploaded to a third party, which is the whole point for contracts, invoices, and medical records. The toolbox covers page operations (merge, split at page numbers or scanned dividers, rotate, reorder, crop, extract), conversion in both directions between PDF and Word, Excel, PowerPoint, images, HTML, and Markdown, OCR that turns scans into searchable PDFs via Tesseract/OCRmyPDF (including PDF/A archival conversion), and security tools for passwords, permissions, watermarks, signatures, and true UI-driven text redaction. A built-in viewer handles annotation, drawing, and text or image insertion, and V2 added stateful processing - upload once, chain multiple tools - plus undo/redo history. For automation, nearly every tool has a REST API endpoint, no-code pipelines combine operations into custom logic chains, and watched folders process files automatically. Enterprise deployments get SSO, user management, and audit logging; the interface ships in 40+ languages. With 84K+ GitHub stars it is the most popular PDF tool in self-hosting, replacing $20/month Acrobat subscriptions with flat infrastructure cost.

PdfDing turns a scattered folder of PDFs into a proper library you can read, annotate, sign, and share from any browser. The viewer remembers exactly where you stopped in every document, so a manual opened on your desktop resumes mid-page on your phone, and progress bars in the library show how far you have read at a glance. Workspaces and collections group related documents, multi-level tags classify them, and starring, archiving, and bulk actions keep even a large archive tidy. Inside the viewer you can add text, highlights, and freehand drawings, then review and export your highlights and comments from dedicated sections and attach Markdown notes to a document. A signature you create once is stored on your server and waits for you on every device, ready to drop onto contracts and forms. Sharing a collection or a single PDF takes a link or a QR code, with optional access control over who can open it and for how long. Accounts are protected by OIDC single sign-on and two-factor authentication with TOTP or WebAuthn, and dark mode, an inverted color mode, and multiple layouts keep long reading sessions comfortable. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

Every line an indentable bullet, every bullet a first-class block that can be referenced, embedded, and queried anywhere: Logseq is a privacy-first, local-first knowledge platform built around the block outliner. The daily journal is the system's beating heart - each day opens a fresh date-stamped page where tasks, meeting notes, and fleeting ideas land as blocks without filing decisions, then connect later through [[wikilinks]] with automatic bidirectional backlinks and ((block references)) that transclude any bullet into any page. Everything persists as plain Markdown or Org-mode files on disk - git-friendly, greppable, and owned forever, with sync via iCloud, Dropbox, Syncthing, Git, or an optional end-to-end encrypted service. Built-in tooling goes beyond notes: TODO/DOING task states with scheduling, native PDF annotation with area highlights, spaced-repetition flashcards, whiteboards for visual thinking, Zotero integration for researchers, and Datalog-powered queries that build dynamic views across the entire graph. A marketplace of hundreds of community plugins and themes adds AI chat, Ollama local-model integration, and custom workflows. Written in Clojure/ClojureScript, AGPL-3.0 licensed with 320+ contributors, and completely free - the local-first Roam for people who refuse subscriptions and lock-in.

Exploratory data work, teaching material, and research code all live in the same browser tab with JupyterLab, the web workspace of Project Jupyter. Notebooks combine runnable code cells, Markdown, and rich output such as images, JSON, and Vega charts, and they use the same notebook format as the classic Jupyter Notebook. Any Jupyter kernel can execute the code, so Python, R, and other languages share one interface, and code inside plain text files such as Markdown or LaTeX can be run interactively as well. Tabs and splitters arrange documents side by side, and a notebook's cell outputs can be mirrored into their own tab to build a simple dashboard with interactive controls. Code consoles serve as scratchpads linked to a notebook kernel, while full terminals run system shells such as bash on the server. A visual debugger offers breakpoints, a call stack, and a variable explorer for kernels that support the Jupyter debug protocol. Markdown, CSV, and Vega documents show a live preview as they are edited, and built-in viewers handle images, JSON, and PDF files. The Extension Manager installs themes, editors, and renderers from PyPI, and real-time collaboration becomes available by adding the jupyter-collaboration extension. Access is protected by a generated token unless a password is set. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. BSD-3-Clause licensed.

For research teams that need to show what was recorded and when, eLabFTW® is an electronic lab notebook that keeps experiments, lab inventory, and equipment bookings in one shared, searchable system. Each experiment holds rich-text notes, tables, images, checkable steps, custom metadata fields, tags, statuses, and attached files. Templates turn a protocol you repeat into a one-click starting point. A separate resource database catalogs antibodies, plasmids, cell lines, chemicals, and instruments, and typing # in an experiment links straight to any of them. Compounds import from PubChem by CID or CAS number, arriving with formulas, identifiers, and hazard data. The inventory tree maps buildings and their sub-locations, records where each container is stored, and tracks quantity and unit. Book a microscope by dragging a slot on the scheduler, and permissions decide who may reserve what. Entries can be signed with Ed25519 keys and timestamped through RFC 3161 authorities such as DFN, Digicert, and GlobalSign, or anchored on the Bloxberg blockchain; a timestamp archive can never be edited or deleted. Export to PDF, ZIP, CSV, JSON, or .eln archives, and import .eln or CSV files when moving from spreadsheets or another notebook. Users sign in locally or through SAML2 or LDAP, and an API with per-user keys lets instruments and scripts read and write entries. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

With DSpace, a library or research office can give every thesis, journal article, and dataset its own permanent web address, a searchable metadata record, and files visitors download from the archive. Content sits in a tree of communities and collections, and each collection decides who may deposit and how many review steps follow; reviewers accept a submission or reject it with a note that sends it back to the author. Embargoes hold files back until a set date, access policies limit other files to chosen groups, and sign-in works through LDAP, Shibboleth, SAML, OpenID Connect, or ORCID. Search covers metadata and the extracted full text of uploaded files, facets narrow the results, and browse pages sort by title, issue date, author, or subject. Editors can correct a published item through the submission form. Administrators inspect an audit trail and rewrite homepage news from an admin form. Entity types for people, organizations, projects, journals, and datasets link each publication to the work behind it, and DOIs can be registered through Crossref. Optional settings let authors keep an email address private on their researcher profile and download their own restricted files. Usage reports count visits, downloads, and top countries per item. REST, OAI-PMH, SWORD, and Google Scholar metadata connect the archive to harvesters, deposit tools, and search engines. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. BSD-3-Clause licensed.

In TeXlyre, two coauthors edit the same LaTeX or Typst file at once, and the PDF compiles inside the browser tab instead of on someone else's server. Start from a template: arXiv preprint, IEEE paper, Tufte book, Beamer deck. pdfTeX, XeTeX, and LuaTeX compile with BibTeX and Biber. Errors turn into readable cards that jump to the failing line. Live cursors show who is typing where. A shared link brings coauthors in, no accounts needed. Chat sits beside the editor, and comments can be discussed and resolved. Tracked insertions and deletions land in a review panel to accept or reject. Draw.io and TikZ editors open inside the project for shared diagrams. MathLive edits a formula under the cursor with a virtual keyboard. A bibliography panel tidies BibTeX, matches DOIs, and imports from Zotero and OpenAlex. Large files travel straight from one collaborator's browser to another. Projects export as ZIP, sync to a local folder, or back up to GitHub, GitLab, Gitea, and Codeberg. Vim, Emacs, and Helix keybindings are one setting away. The app installs as a progressive web app and works offline. Language servers like LTeX LS Plus, Harper, and Tinymist plug in through recipes beside your own signaling and TeX Live package servers. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.