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/core/api_client.py

@@ -0,0 +1,72 @@
+"""Client HTTP verso l'api-service (service-to-service via x-api-key).
+
+Espone accesso a:
+  /jobs              ciclo di vita job
+  /queue             stato coda
+  /pageconnections   registro sessioni di pagina (enforcement /test max 2)
+"""
+from __future__ import annotations
+
+from typing import Any, Optional
+
+import httpx
+
+from core.config import settings
+
+
+def _headers() -> dict:
+    return {"x-api-key": settings.internal_api_key, "Content-Type": "application/json"}
+
+
+async def _req(method: str, path: str, json: Optional[dict] = None, params: Optional[dict] = None) -> Any:
+    url = f"{settings.api_url}{path}"
+    async with httpx.AsyncClient(timeout=10.0) as c:
+        r = await c.request(method, url, json=json, params=params, headers=_headers())
+        r.raise_for_status()
+        if r.status_code == 204 or not r.content:
+            return None
+        return r.json()
+
+
+# ── jobs ────────────────────────────────────────────────────────────────────
+async def create_job(type_: str, created_by: str, payload: dict) -> dict:
+    return await _req("POST", "/jobs", json={"type": type_, "created_by": created_by, "payload": payload})
+
+
+async def update_job(job_id: str, **fields) -> dict:
+    return await _req("PATCH", f"/jobs/{job_id}", json=fields)
+
+
+async def get_job(job_id: str) -> dict:
+    return await _req("GET", f"/jobs/{job_id}")
+
+
+async def list_jobs(type_: Optional[str] = None, status: Optional[str] = None, limit: int = 50) -> list:
+    params = {"limit": str(limit)}
+    if type_:
+        params["type"] = type_
+    if status:
+        params["status"] = status
+    return await _req("GET", "/jobs", params=params) or []
+
+
+# ── queue ───────────────────────────────────────────────────────────────────
+async def queue_status(type_: str = "train") -> dict:
+    return await _req("GET", "/queue", params={"type": type_})
+
+
+# ── page connections ───────────────────────────────────────────────────────
+async def page_connect(page: str, user_id: str, session_id: str) -> dict:
+    return await _req("POST", "/pageconnections", json={"page": page, "user_id": user_id, "session_id": session_id})
+
+
+async def page_ping(session_id: str) -> dict:
+    return await _req("POST", f"/pageconnections/{session_id}/ping")
+
+
+async def page_disconnect(session_id: str) -> None:
+    await _req("DELETE", f"/pageconnections/{session_id}")
+
+
+async def page_count(page: str) -> dict:
+    return await _req("GET", f"/pageconnections/{page}")