How suryanshraj2029/devhandover-ai works
DevHandover AI is a Streamlit handover and project-knowledge platform. The documented user journey is to manage a workspace, add project knowledge and interview records, assess continuity and successor readiness, then assemble a handover package. The README describes these as product capabilities; sampled code shows their implementation is concentrated in app.py, including SQLite persistence and Gemini-backed interview behavior. The frontend is an unrelated Vite starter, not the documented product UI. Several domain links below are documented rather than verified in unsampled code.
Main entry points: app.py Streamlit interface
Components 18
Workspace and Documents
- Streamlit interface
app.py - Project workspaces
app.py - PDF extraction
app.py
Knowledge and Interviews
- Knowledge assistant
app.py - Knowledge gaps
app.py - Knowledge interviews
app.py - Evidence verification
app.py - Project knowledge map
app.py
Continuity Planning
- Risk assessment
app.py - Domain expertise
app.py - Handover checkpoints
app.py - Successor readiness
app.py
Handover and Persistence
- Successor workspace
app.py - Handover package
app.py - SQLite database
app.py
Other components
- Team user
- Gemini AI
- PyMuPDF
Connections 21
- Team user → Streamlit interface: uses
README.md - Streamlit interface → Project workspaces: manages
README.md - Project workspaces → PDF extraction: uploads documents
README.md - PDF extraction → PyMuPDF: extracts text
README.md - PDF extraction → Knowledge assistant: provides knowledge
README.md - Knowledge assistant → Gemini AI: answers with
README.md - Streamlit interface → Knowledge gaps: identifies
README.md - Streamlit interface → Knowledge interviews: conducts
README.md - Knowledge interviews → Gemini AI: generates questions
app.py - Streamlit interface → Evidence verification: verifies evidence
README.md - Streamlit interface → Project knowledge map: organizes knowledge
README.md - Streamlit interface → Risk assessment: assesses
README.md - Streamlit interface → Domain expertise: tracks owners
README.md - Streamlit interface → Handover checkpoints: tracks tasks
README.md - Streamlit interface → Successor readiness: assesses successors
README.md - Successor workspace → Knowledge assistant: asks questions
README.md - Streamlit interface → Successor workspace: supports learning
README.md - Streamlit interface → Handover package: generates report
README.md - Streamlit interface → SQLite database: persists records
README.md - Knowledge interviews → SQLite database: saves records
app.py - Risk assessment → SQLite database: saves assessment
app.py