Skip to content

Repository files navigation

⚒️ CaseForge

Don't just read papers. Build knowledge from them.

An extensible AI workflow for extracting structured case studies from academic literature.

Who is this for?

If you read 3+ papers a week and want to turn them into searchable, reusable knowledge assets — CaseForge is built for you.


Why CaseForge?

Most AI tools summarize papers.

CaseForge transforms papers into structured knowledge that can be searched, compared, and reused.

Instead of asking:

"What is this paper about?"

CaseForge asks:

"What knowledge can we extract from this paper?"


Philosophy

CaseForge is not another paper chatbot.

It is a workflow engine for turning academic literature into structured knowledge.

Small. Simple. Extensible. Reusable.


What It Does

  📄 Paper (PDF / TXT / MD)
        │
        ▼
  📖 Reader      ← pdfplumber / markitdown
        │
        ▼
  🧠 AI Extract  ← 10-field deep extraction
        │
        ▼
  📊 Export      ← HTML / Markdown / JSON / Word

Demo

CaseForge Demo

python main.py --demo

Quick Start

git clone https://github.com/modusensus/CaseForge.git
cd CaseForge
pip install -r requirements.txt
cp config.example.py config.py     # add any one API key
python main.py --demo

Features

  • ✅ 8-field structured case extraction
  • ✅ Export to HTML / Markdown / JSON / Word
  • ✅ Prompt-driven workflow (swap disciplines without changing code)
  • ✅ Multi-provider LLM support (5 APIs, including free tier)
  • ✅ Local TF-IDF fallback when API fails
  • ✅ Dedup cache (never pay twice for the same paper)
  • ✅ Academic search (Semantic Scholar / OpenAlex / CORE)

Example Output

## 案例标题

🌍 研究背景
城市湿地公园面临生态保护与开发的结构性张力...

🎯 研究对象/目的
分析杭州西溪湿地公园的开发争议与协调机制...

🧪 研究方法
案例研究法,数据来源包括政策文件、生态监测数据...

📈 核心发现
围栏式保护不可持续,需利益共享+多主体协商...

💡 创新点
将社区协调机制与规划管控相结合进行系统分析...

✨ 一句话总结
社区利益共享与协商机制需前置到规划阶段。

Architecture

prompts/           ← Discipline-specific extraction templates
    │
    ▼
api_client.py      ← Unified interface for 5 LLM providers
    │
    ▼
exporters.py       ← HTML / Markdown / JSON / Word output
    │
    ▼
search.py          ← Semantic Scholar / OpenAlex / CORE

Extensible by Design

Add a new discipline without touching any code:

prompts/
├── urban_design.md    ← default
├── education.md       ← contributed
├── medicine.md        ← coming soon
└── law.md             ← coming soon

Roadmap

  • ✅ Markdown / JSON / Word / HTML export
  • ✅ Multi-provider LLM support
  • ✅ Prompt plugin system
  • ✅ Academic search (3 databases)
  • □ Prompt marketplace
  • □ MCP / Skills integration
  • □ Web UI

Contributing

We welcome contributions — especially:

  • Prompt templates for new disciplines
  • Readers for new input formats
  • Exporters for new output formats
  • Tests and documentation

See CONTRIBUTING.md.


MIT License · Changelog

About

Don't just read papers. Build knowledge from them. — Extensible AI workflow for extracting structured case studies from academic literature.

Topics

Resources

Contributing

Stars

Watchers

Forks

Releases

Packages

Contributors

Languages