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API Documentation

Introducing PaperChat, a highly advanced plugin specifically designed for comprehensive browsing and navigation through a sizeable collection of the arXiv publications. Ideal for researchers, academics, and the perpetually curious, PaperChat harnesses cutting-edge technology to provide succinct and accurate answers to your inquiries, all drawn from the depths of the voluminous, peer-reviewed arXiv library. This tool systematically trawls through an extensive database of academic documents to retrieve factual, up-to-date information that corresponds to your query. What sets PaperChat apart is its exceptional ability to illustrate its search process, presenting the steps leading to the final response on a silver platter. Each information received comes with the source file, providing a seamless way to delve deeper into the chosen topics. In a digital world where data availability can often overshadow data accessibility, PaperChat brings the vast oceans of knowledge housed within arXiv publications to your fingertips in a controlled, easily comprehensible manner.




Example Prompts


"How can I convert an image to black and white using Python?"


"What's the code to calculate the factorial of a number in Java?"


"Can you show me an example of how to sort a list in C++?"


"I'm getting an error message saying 'index out of range' in my Python code, what could be causing it?"


"How can I implement a binary search algorithm in JavaScript?"

Description for AI

Plugin for searching through the arXiv publications to find answers to questions and retrieve relevant information. Use it whenever a user asks something that might be found in arXiv publications. Include source of the file you get information from. Answer questions as concisely and accurately as possible. Think step-by-step to show how you got to your answer.

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