RUCKBReasoning/SoAy
Codes for paper SoAy: A Service-oriented APIs Applying Framework of Large Language Models
This project helps researchers and academics efficiently find specific information within academic databases using natural language questions. It takes your complex research questions, like "How many times has the most cited paper by Yann LeCun at New York University been cited?", and provides precise answers by intelligently using underlying API services from platforms like AMiner. The primary users are researchers, students, and librarians who need to quickly extract detailed facts from large academic datasets.
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Use this if you need to build or enhance a system that allows large language models to accurately answer detailed academic information queries by orchestrating multiple API calls to academic databases.
Not ideal if your primary goal is general conversational AI or if you are not working with structured API services for academic information retrieval.
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Language
Python
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Last pushed
Jul 14, 2025
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