feat: Add new API endpoints and HTML pages for ML model management

- Implemented HTML pages for datasets, models, training, testing, and results.
- Created API endpoints for managing repositories, results, tests, and training sessions.
- Added functionality for streaming training progress via Server-Sent Events (SSE).
- Introduced a Dockerfile for the ML runner with necessary dependencies.
- Developed an SDK for user code execution within the runner container.
- Enhanced CSS styles for improved UI layout and navigation.
- Established a layout template for consistent HTML structure across pages.
- Added JavaScript for dynamic interactions on the models page.
- Implemented WebSocket handling for real-time communication with kiosk devices and controllers.
- Implemented model registration and management API at /api/models
- Added Gitea proxy API for repository interactions at /api/repos
- Created results API for listing and comparing training results at /api/results
- Developed training management API for enqueueing and retrieving training jobs at /api/trainings
- Introduced SSE endpoint for live training progress updates
- Added HTML pages for models, datasets, and training management
- Created a Dockerfile for the ML runner with necessary dependencies
- Developed SDK for user code execution within the runner container
- Enhanced CSS styles for improved UI/UX
- Implemented WebSocket communication for real-time device and controller interactions in the kiosk system

ml/routers/pages.py

@@ -0,0 +1,75 @@
+"""Pagine HTML servite direttamente da ml.mebboat.it.
+
+Layout:
+  /           redirect a /datasets (o landing console)
+  /datasets   lista/upload dataset
+  /models     registro modelli
+  /train      avvia training
+  /test       esegue test su modello trainato
+  /results    storico e confronto risultati
+"""
+from __future__ import annotations
+
+from pathlib import Path
+
+from fastapi import APIRouter, Depends, Request
+from fastapi.responses import HTMLResponse, RedirectResponse
+from fastapi.templating import Jinja2Templates
+
+from core.auth import _verify
+from core.config import settings
+
+router = APIRouter(tags=["pages"])
+
+TEMPLATES_DIR = Path(__file__).resolve().parent.parent / "templates"
+templates = Jinja2Templates(directory=str(TEMPLATES_DIR))
+
+
+def _user_or_redirect(request: Request):
+    """Per le pagine, se non autenticato redirect al login. Ritorna user dict o RedirectResponse."""
+    token = request.cookies.get("auth_token")
+    auth = request.headers.get("authorization")
+    if not token and auth and auth.startswith("Bearer "):
+        token = auth[7:]
+    user = _verify(token)
+    if not user:
+        target = str(request.url)
+        return RedirectResponse(url=f"{settings.auth_login_url}?redirect={target}", status_code=302)
+    return user
+
+
+def _render(request: Request, template: str, **ctx):
+    user = _user_or_redirect(request)
+    if isinstance(user, RedirectResponse):
+        return user
+    return templates.TemplateResponse(template, {"request": request, "user": user, **ctx})
+
+
+@router.get("/", response_class=HTMLResponse)
+async def home(request: Request):
+    return RedirectResponse(url="/datasets")
+
+
+@router.get("/datasets", response_class=HTMLResponse)
+async def page_datasets(request: Request):
+    return _render(request, "datasets.html", page="datasets")
+
+
+@router.get("/models", response_class=HTMLResponse)
+async def page_models(request: Request):
+    return _render(request, "models.html", page="models")
+
+
+@router.get("/train", response_class=HTMLResponse)
+async def page_train(request: Request):
+    return _render(request, "train.html", page="train")
+
+
+@router.get("/test", response_class=HTMLResponse)
+async def page_test(request: Request):
+    return _render(request, "test.html", page="test")
+
+
+@router.get("/results", response_class=HTMLResponse)
+async def page_results(request: Request):
+    return _render(request, "results.html", page="results")