Delete README.md

README.md

@@ -1,41 +0,0 @@
----
-title: PhishWatch Proxy
-emoji: 🛡️
-sdk: docker
----
-
-# Hugging Face Space - Phishing Text Classifier (Docker + FastAPI)
-
-This Space exposes two endpoints so the Flutter app can call them reliably:
-
-- `/predict` for text/email/SMS classification via Transformers
-- `/predict-url` for URL classification via your scikit-learn Random Forest model
-
-## Files
-- Dockerfile - builds a small FastAPI server image
-- app.py - FastAPI app that loads the model and returns `{ label, score }`.
-- requirements.txt - Python dependencies.
-
-## How to deploy
-1. Create a new Space on Hugging Face (type: Docker).
-2. Upload the contents of this `hf_space/` folder to the Space root (including Dockerfile).
-3. In Space Settings → Variables, add:
-   - MODEL_ID = Perth0603/phishing-email-mobilebert
-   - URL_REPO = Perth0603/Random-Forest-Model-for-PhishingDetection
-   - URL_FILENAME = url_rf_model.joblib  (set to your artifact filename)
-4. Wait for the Space to build and become green. Test:
-   - GET `/` should return `{ status: ok, model: ... }`
-   - POST `/predict` with `{ "inputs": "Win an iPhone! Click here" }`
-   - POST `/predict-url` with `{ "url": "https://example.com/login" }`
-
-## Flutter app config
-Set the Space URL in your env file so the app targets the Space instead of the Hosted Inference API:
-
-```
-{"HF_SPACE_URL":"https://<your-space>.hf.space"}
-```
-
-Run the app:
-```
-flutter run --dart-define-from-file=hf.env.json
-```