How piyush2676/graphloom works
GraphLoom builds knowledge graphs from study material and provides AI-assisted study tools. The principal flow is PDF upload, text extraction and chunking, indexing and graph creation, then graph inspection or retrieval-based study outputs. The tree and excerpts also indicate a Streamlit application with transcript and report capabilities, but its wiring is only partially visible; frontend-to-backend calls are not asserted where the sampled source does not establish them.
Main entry points: backend.py Knowledge API · Index.tsx Workspace page · App.tsx Web app shell · app.py Streamlit application
Components 19
Web interface
- Web app shell
frontend/src/App.tsx - Workspace page
frontend/src/pages/Index.tsx - Sources and settings
frontend/src/components/AppSidebar.tsx - Study workspace
frontend/src/components/MainContent.tsx - Knowledge graph
frontend/src/components/KnowledgeGraphPanel.tsx - Chat
frontend/src/components/ChatPanel.tsx - Summaries
frontend/src/components/SummaryPanel.tsx - Flashcards
frontend/src/components/FlashcardsPanel.tsx - AI mentor
frontend/src/components/AIMentorPanel.tsx
Knowledge services
- Knowledge API
backend.py - PDF extraction
backend.py - Chunking and graphing
backend.py - Vector index
backend.py
Streamlit application
- Streamlit application
app.py - Source extraction
app.py - Study and export tools
app.py
Other components
- Learner
- Language model
- Embedding model
Connections 15
- Learner → Web app shell: uses
- Web app shell → Workspace page: routes to
- Workspace page → Sources and settings: renders
- Workspace page → Study workspace: renders
- Learner → Knowledge API: uploads PDFs
- Knowledge API → PDF extraction: loads PDF
- PDF extraction → Chunking and graphing: passes text
- Chunking and graphing → Vector index: indexes chunks
- Chunking and graphing → Embedding model: creates embeddings
- Knowledge API → Vector index: retrieves context
- Knowledge API → Language model: requests generation
- Learner → Streamlit application: uses
- Streamlit application → Source extraction: extracts sources
- Source extraction → Study and export tools: provides content
- Study and export tools → Language model: requests generation