Don't just read papers. Build knowledge from them.
An extensible AI workflow for extracting structured case studies from academic literature.
If you read 3+ papers a week and want to turn them into searchable, reusable knowledge assets — CaseForge is built for you.
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?"
CaseForge is not another paper chatbot.
It is a workflow engine for turning academic literature into structured knowledge.
Small. Simple. Extensible. Reusable.
📄 Paper (PDF / TXT / MD)
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📖 Reader ← pdfplumber / markitdown
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🧠 AI Extract ← 10-field deep extraction
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📊 Export ← HTML / Markdown / JSON / Word
python main.py --demogit 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- ✅ 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)
## 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。prompts/ ← Discipline-specific extraction templates
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▼
api_client.py ← Unified interface for 5 LLM providers
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exporters.py ← HTML / Markdown / JSON / Word output
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search.py ← Semantic Scholar / OpenAlex / CORE
Add a new discipline without touching any code:
prompts/
├── urban_design.md ← default
├── education.md ← contributed
├── medicine.md ← coming soon
└── law.md ← coming soon
- ✅ Markdown / JSON / Word / HTML export
- ✅ Multi-provider LLM support
- ✅ Prompt plugin system
- ✅ Academic search (3 databases)
- □ Prompt marketplace
- □ MCP / Skills integration
- □ Web UI
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.
