S0ra-ai

S0ra-ai / academic_paper_generation

Public

This project aims to assist researchers in quickly generating high-quality academic papers or reports. By integrating multiple academic literature retrieval sources and large language models (LLM), and combining Retrieval-Augmented Generation (RAG) technology, it enables the full-process automation from literature collection to report writing.

19
1
69% credibility
Found Feb 08, 2026 at 14 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A web-based tool that automatically generates academic papers and reports from a user-provided topic by searching literature databases and integrating optional local documents and custom templates.

How It Works

1
🔍 Discover the tool

You find this helpful web app that can create academic reports from a simple research idea.

2
🚀 Open the web page

You start the friendly web interface on your computer to begin making reports.

3
💡 Type your research topic

You enter a topic like 'AI in medicine' into the simple form to tell it what to research.

4
Add extra info?
✅
Yes, upload files

Drag in PDFs or Word files so it includes your notes and data.

➡️
No, just generate

Skip ahead and let it search the web for info on its own.

5
✨ Hit generate

You click the button and watch as it gathers smart info and writes a full report for you.

6
📋 Review your report

You see the complete report with sections, references, and download it right away.

🎉 Done!

You now have a polished academic report ready to use or share with your team.

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Star Growth

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AI-Generated Review

What is academic_paper_generation?

This Python-based full-stack tool automates generating academic papers and reports from a research topic. Drop in a query, upload local docs or custom templates, and it pulls literature from Crossref, OpenAlex, ArXiv, and Semantic Scholar via RAG-enhanced LLMs, spitting out structured Markdown reports with citations. Like a project GitHub repo for researchers, it handles the full flow—search to writing—in a clean Vue.js web app with Flask backend and Docker Compose for one-command deploys.

Why is it gaining traction?

It stands out by blending multi-source academic search with local knowledge bases and template control, delivering cited, multi-language reports without manual lit reviews. Developers dig the concurrent retrieval for speed and RAG accuracy over plain LLM hallucinations, plus easy API endpoints like POST /api/generate-report for integration. In a sea of generic GitHub Copilot alternatives, its focus on academic aims vs objectives—precise structure matching project aims examples—hooks science devs needing reproducible outputs.

Who should use this?

Academic researchers drafting lit reviews or grant proposals, PhD students in math and science chasing project aims slides, or lab managers automating report generation from experiment data. Ideal for anyone tired of piecing together ArXiv PDFs into coherent narratives, especially with local doc uploads for proprietary project GitHub Python repos.

Verdict

Grab it if you're in academia and want a quick RAG booster—solid docs and Docker make setup painless despite 16 stars signaling early maturity. Credibility score of 0.699999988079071% reflects niche appeal, but test with your project aims and objectives for real wins.

(198 words)

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