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ZimoLiaoAI-native research terminal for AI agents
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Summary
ScholarAIO provides a knowledge infrastructure for AI agents, transforming research papers into a structured, searchable format. It enables agents to perform advanced tasks like reproducing methods, verifying claims, and drafting manuscripts, streamlining the AI-powered research loop.
How It Works
ScholarAIO parses PDFs into structured Markdown, preserving figures and LaTeX, then enriches metadata via APIs. It employs hybrid search (keyword FTS5 + semantic FAISS) for retrieval and integrates with AI agents via standardized skills or direct repo usage, allowing agents to leverage the processed knowledge base.
Quick Start & Requirements
Install via git clone, pip install -e ".[full]", and scholaraio setup, then run claude in the repo root. Alternatively, use as a Claude Code plugin. Requires Python 3.10+, an LLM API key (e.g., Anthropic, OpenAI, Google, DeepSeek), and optionally a MINERU_API_KEY. An embedding model (~1.2 GB) auto-downloads. See docs/getting-started/agent-setup.md for details.
Highlighted Details
Maintenance & Community
Licensed under MIT, the project appears primarily maintained by Zi-Mo Liao. No specific community channels or external sponsorships are detailed.
Licensing & Compatibility
The MIT License is permissive for commercial use and integration into closed-source projects.
Limitations & Caveats
Full functionality requires LLM API keys. Advanced PDF parsing relies on the optional MINERU_API_KEY or self-hosting MinerU. Agent integration methods vary by agent type.
3 days ago
Inactive
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