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tlysanhuoLLM-driven research paper recommendation system
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Summary
This repository offers a personalized paper recommendation system for OpenClaw/Feishu, powered by AMiner, arXiv, and LLMs. It targets researchers and users seeking efficient academic paper discovery, providing a natural-language-first interface with scholar-aware cold starts and unified profile building for enhanced relevance.
How It Works
The system accepts scholar or topic-based inputs, unifying them into a ResearchProfile. It then performs retrieval, AMiner enrichment, summarization, and card rendering. The core novelty lies in its natural-language-first approach, scholar-aware cold starts leveraging AMiner signals, and graceful degradation when optional internal components are unavailable, ensuring robustness.
Quick Start & Requirements
pip install -r requirements.txt within a Python virtual environment.config.example.yaml to config.yaml, setting aminer.token and LLM API details. Environment variables can also be used.python3 scripts/handle_trigger.py --base-dir . --config config.yaml --text "<query>".~/.openclaw/skills/aminer-rec5.Highlighted Details
Maintenance & Community
This is a public-shareable cut of an internal system. No specific community links or contributor details are provided. A Star History link is available.
Licensing & Compatibility
Limitations & Caveats
This public version omits internal secrets and local artifacts. Functionality dependent on optional internal hooks will degrade gracefully. The sole supported external interface is scripts/handle_trigger.py; other scripts are internal and subject to change.
3 weeks ago
Inactive
Future-House