https://github.com/manojtharindu11/itp_sl_via_experta
The intelligent travel planner uses an Experta-based expert system to recommend optimal routes through Sri Lanka based on your preferences.
https://github.com/manojtharindu11/itp_sl_via_experta
expert-system experta prolog
Last synced: 2 months ago
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The intelligent travel planner uses an Experta-based expert system to recommend optimal routes through Sri Lanka based on your preferences.
- Host: GitHub
- URL: https://github.com/manojtharindu11/itp_sl_via_experta
- Owner: manojtharindu11
- Created: 2025-10-27T13:01:37.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-11-12T17:44:59.000Z (9 months ago)
- Last Synced: 2025-12-27T21:21:54.431Z (7 months ago)
- Topics: expert-system, experta, prolog
- Language: Python
- Homepage: https://intelligent-travel-planning-str.streamlit.app/
- Size: 34.2 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# ITP-SL — Intelligent Travel Planning (Sri Lanka)
A compact expert-system-backed travel recommender for Sri Lanka using Experta. It recommends destinations and routes based on season and budget preferences and computes shortest paths between cities.
## Quick start
Prerequisites
- Python 3.8+
Install dependencies (recommended in a virtual environment):
```powershell
python -m venv .venv
.\.venv\Scripts\Activate.ps1
pip install -r requirements.txt
```
Run the Streamlit app:
```powershell
streamlit run app.py
```
Open http://localhost:8501 in your browser. Press Ctrl+C to stop.
Run tests:
```powershell
pytest -q
```
## Project layout
- `app/experta_kb.py` — Experta knowledge base and rules
- `app/query.py` — Helper/adaptor functions used by the UI and tests
- `app.py` — Streamlit UI
- `test/` — unit and integration tests
## Environment variables
Copy `.env.example` to `.env` to configure:
- `USE_MAPBOX` — `true` to enable Mapbox tiles
- `MAPBOX_TOKEN` — Mapbox access token (if `USE_MAPBOX=true`)
- `MAPBOX_STYLE` — optional Mapbox style URI
- `OSM_TILE_URL` — optional custom OSM tile URL
## Notes
- The canonical knowledge base is `app/experta_kb.py`. Extend rules or data there.
- README simplified to remove outdated details.