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binary-husky/gpt_academic

70,684PythonAudience · researcherComplexity · 3/5MaintainedLicenseSetup · moderate

TLDR

A Python web app for researchers and academics to interact with multiple AI models at once, with plugins for translating papers, proofreading, summarizing, and analyzing code.

Mindmap

mindmap
  root((repo))
    What it does
      Multi-model chat interface
      Academic task plugins
      LaTeX formula rendering
      Codebase analysis
    Key features
      One-click paper translation
      Grammar proofreading
      ArXiv summarization
      Code comment generation
    Tech stack
      Python
      Gradio web UI
      Docker support
      Multiple AI APIs
    Use cases
      Research workflows
      Paper polishing
      Code review
      Translation tasks
    Audience
      Researchers
      Graduate students
      Academics
      Developers

Things people build with this

USE CASE 1

Translate entire LaTeX academic papers while preserving formatting and structure.

USE CASE 2

Proofread and improve grammar in research papers and Markdown documents using AI.

USE CASE 3

Summarize ArXiv papers by pasting a URL to quickly understand key findings.

USE CASE 4

Analyze entire Python or C++ codebases to understand structure and generate documentation.

Tech stack

PythonGradioDockerOpenAI APIClaude API

Getting it running

Difficulty · moderate Time to first run · 30min

Requires API keys for OpenAI and Claude; Docker simplifies setup but not mandatory.

Use it freely, but any project you distribute that includes this code must also be GPL-licensed and open source.

In plain English

GPT Academic is a Python-based web application that provides a feature-rich interface for interacting with large language models, with a specific focus on academic and research workflows. The description and README are primarily in Chinese. The tool is designed to make tasks like reading, proofreading, translating, and writing academic papers faster and more convenient, while also supporting code analysis tasks. The application works as a Gradio-based web UI that you run locally or on a server. It connects to multiple AI models simultaneously, including GPT-3.5 and GPT-4 from OpenAI, Claude, Chinese models like Qwen, ChatGLM, DeepSeek Coder, and others, letting you query several at once for comparison. The plugin system is a key feature: one-click plugins handle specific tasks like translating entire LaTeX papers (preserving the formatting), summarizing ArXiv papers by URL, proofreading grammar in LaTeX documents, analyzing entire Python or C++ project codebases, translating or proofreading Markdown files, batch-generating code comments, and more. The interface renders mathematical formulas in both their raw LaTeX form and the typeset display form side by side, which is useful for academic work. You would use this tool if you are a researcher, graduate student, or academic who frequently reads and writes papers, especially in fields that use LaTeX, and wants to use AI assistance for translation, polishing, and summarization without tediously copying and pasting. It is also useful for developers who want to analyze codebases with AI. The tech stack is Python with Gradio for the web interface, supporting Docker deployment. Multiple API keys from different providers can be configured simultaneously.

Copy-paste prompts

Prompt 1
Set up GPT Academic locally with my OpenAI and Claude API keys so I can compare how both models proofread my research paper.
Prompt 2
Use the LaTeX translation plugin to translate my entire dissertation from English to Chinese while keeping all equations and formatting intact.
Prompt 3
Paste an ArXiv paper URL into GPT Academic and have it summarize the main contributions and methodology.
Prompt 4
Analyze my Python project codebase with GPT Academic to generate comments and documentation for all functions.
Prompt 5
Configure GPT Academic to use Qwen and ChatGLM models alongside GPT-4 so I can compare translations of my paper.
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Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.