Dashboard Guide
This project includes a Streamlit dashboard for presenting the current framework, experiment artifacts, and comparison outputs in a more visual and demo-friendly way.
Purpose
The dashboard is a presentation layer for the saved experiment artifacts.
It is designed to help the team:
- inspect individual runs
- review baseline-vs-defended comparisons
- present category, surface, and source breakdowns
- inspect case-level outcomes
- show a polished proof-of-concept during demos and reporting
Entry Point
dashboard/streamlit_app.py
What The Dashboard Shows
Hero and project snapshot
- active corpus size and sources
- selected run and selected comparison
- a spotlight on the latest real comparison artifact
Run Overview
- key metrics from
summary.json - mitigation pressure and manual-review counts
- attack-category, attack-surface, and source breakdowns
Comparison Lab
- saved comparison artifacts from
results/comparisons/*.json - overall metric deltas
- category, surface, and source deltas
- optional report-ready Markdown summaries when available
Case Explorer
- case-level results from
case_results.jsonl - request prompt
- execution context
- response text
- mitigation action and evaluation outcome
Manifest View
- model snapshot
- mitigation snapshot
- dataset snapshot
- run provenance
Installation
Install the dashboard extras:
pip install -e .[dashboard]
Run
From the repository root:
streamlit run dashboard/streamlit_app.py
Design Notes
The dashboard remains intentionally lightweight:
- no extra backend service
- no database
- no API layer
- reads repository artifacts directly
That keeps it aligned with capstone scope while still giving the project a strong visual interface.
Recommended Demo Flow
- Open the dashboard and show the hero/project snapshot.
- Select a real defended run in Run Overview.
- Show the category and source breakdowns.
- Open Comparison Lab and inspect a saved real baseline-vs-defended comparison.
- Use Case Explorer to show one concrete example.
- Use Manifest to explain reproducibility and experiment setup.