github.com/OpenSourceAGI/qwksearch-research-agent @v1.2.4

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🚀 Demo 📑 Docs 🎯 API

🧠💻 Reimagine the Internet as Self-Organizing Mind Map

Critical times call for critical thinkers to create a crowdsourced argument reasoning dataset, for AI models to recommend research quotes, to evolve crowdsourced chain-of-thought reasoning, to unlock faster ways to read long articles, to monitor developments by topic modeling a knowledge base graph, and to provide a public service of answers to research.

Language Models can distill the essence of collective thought into a vector space where every point has a weighted value representing its contribution to the overall decision-making process. AI will show its reasoning based on what sentences and cites it used from the collective research, so that people can see it is aligned with our interests. Research Agents recommend articles for human researchers working alongside AI to develop a summarized topic outline as a public service. The agents monitor for any related articles via web searches for keywords associated with that Topic Model. Imagine uploading a research paper, then the app extracts full text of reference cites and creates topic model and keyword summaries, then monitors that literature base and stores highlights. People will make personal knowledge bases of what influences them to create AI assistants cloning their mind-uploaded perspective and interests in a self-organizing mind map.

# Download Source
bunx git0 vtempest/ai-research-agent

# Import Self-Hosted API
bun i ai-research-agent

# Import API Client 
bun i qwksearch-api-client

🤖🔎 STREAM: Search with Top Result Extraction & Answer Model

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Reimagine The Web as Self-Organizing Mind Map

• 🔍 Web Search - 100+ popular sites search across 10 categories: Web Search, Academic, Videos, Images, Files, News, etc
• 📝 Article Preview - Extract and summarize articles before reading them
• 🤖 User Choice of LLM - OpenAI, Claude, Gemini, Groq, Ollama, Anthropic, etc
• 📄 File Upload Support - Ask questions about PDFs, URLs, DOCX, Google Docs, and Youtube
• 📚 Search History - All searches saved locally for privacy
• ❓ Follow-up Questions - Generate follow-up questions to ask language models

REASON Writing Agent

Research Editor for Annotated Summaries in Outline Notation

<img width="400px" src="https://i.imgur.com/pDvMC1Q.png" />

• 📂 Nested Document Tree: organize research notes with a nested document organizer with drag-and-drop, tabs, and custom storage sources
• 🖱️ Context Menu Operations: right-click to access quick actions for seamless document management
• 🔍 Full-Text Search: instantly find documents by title or content with full-text search
• ✨ AI Rewriting: leverage AI to rewrite and improve your text directly within the editor
• 👥 Team Management: collaborate with team members and manage access rights
• 🔄 View Modes: switch between Formatted, parsing HTML, and Markdown views for versatile editing
• 🛠️ Find & Replace: powerful search and replace functionality with match highlighting
• 📥 Google Docs Integration: seamless export, import, and sharing capabilities
• 💾 Persistent Storage: reliable SQLite storage ensures your data is safe and accessible
• ⌨️ Keyboard Navigation: efficient keyboard shortcuts for power users
• 💬 Research Quotes: capture and organize key quotes and insights from your research
• 🏗️ Built with: Claude Code, Lexical Editor, shadcn/ui, Cloudflare, Next.js, Google Docs API

🚜📜 Tractor the Text Extractor

1. Main Content Detection: Extract the main content from a URL by combining Mozilla Readability and Postlight Mercury algorithms, utilizing over 100 custom adapters for major sites for article, author, date HTML classes.
2. YouTube Transcript Processing: When a YouTube video URL is detected, retrieve the complete video transcript including both manual captions and auto-generated subtitles, maintaining proper timestamp synchronization.
3. PDF to HTML: Extracts formatted text from PDF with parsing of linebreaks , page headers, footnotes, and section headings. Supports fonts, links, bold, italics, lists, headings, headers, footnotes, and Table of Contents, Quotes, and Code Blocks. Removes repeated headers, links footnote anchors to the footnote, and preserves number of the PDF page with invisible I element. This function uses pdfjs-serverless to work in more environments than PDF.js-based tools: Cloudflare workers, serverless, node.js, and front-end only.
4. Basic HTML Standardization: Transform complex HTML into a simplified reading-mode format of basic HTML, making it ideal for research note archival and focused reading, with headings, images and links.
5. Cite: Identify and extract citation metadata including author names, publication dates, sources, and titles using HTML meta tags and common class name patterns. The system validates author names against a comprehensive database of 90,000 first and last names, distinguishing between personal and organizational authors to properly format citations.

Further Research

• ThoughtSource Reasoning Datasets
• Awesome-LLMs-Datasets
• GPT Researcher
• NLP Papers Latest Updates
• Anthropic Persuation Overview
• NLP Research Progress
• NLP Datasets
• Google Search Algorithm
• Can LLMs Generate Novel Research Ideas?
• Graph Algorithms Playground
• CommonCrawl C4 Download
• Knowledge Graphs Prompts Papers
• Paper - Iterative Research Idea Generation
• Open Deep Search
• LangChain Hub

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