| """ |
| Definición de interfaz visual de Gradio y endpoints HTTP de salud y diagnóstico. |
| 100% de paridad con los endpoints de API de hf_worker/main.go. |
| """ |
|
|
| import re |
|
|
| import psutil |
| import gradio as gr |
| from fastapi import FastAPI, Request, HTTPException |
| import time |
|
|
| from config import ( |
| WORKER_ID, |
| WORKER_SECRET, |
| VERSION, |
| START_TIME, |
| ) |
| from state import STATE |
| def public_event_log(raw_log: str) -> str: |
| """Keep the public node console generic and avoid exposing implementation details.""" |
| hidden_terms = re.compile(r"compression|compresi[oó]n|ffmpeg|codec|crf|telegram|bot-compress", re.IGNORECASE) |
| lines = [] |
| for line in raw_log.splitlines(): |
| if hidden_terms.search(line): |
| continue |
| lines.append(line) |
| return "\n".join(lines[-30:]) |
|
|
| def get_telemetry_ui(): |
| """Genera métricas en tiempo real para el panel de Gradio.""" |
| summary = STATE.get_summary() |
| job = summary["job"] |
|
|
| cpu_usage = psutil.cpu_percent() |
| ram = psutil.virtual_memory() |
|
|
| job_card = "🟢 **Nodo activo**: Esperando asignaciones de la plataforma..." |
| progress_val = 0 |
| if job: |
| job_card = f"""### ⚡ Actividad en curso |
| - **ID**: `{job.get('task_id')}` |
| - **Estado**: **{job.get('status')}** |
| - **Velocidad**: `{job.get('speed')}` | **ETA**: `{job.get('eta')}` |
| """ |
| progress_val = job.get("percent", 0.0) |
|
|
| header_html = f""" |
| <div style="display:flex; justify-content:space-between; align-items:center; background:#1e1e2e; padding:15px; border-radius:10px; color:#cdd6f4; border:1px solid #313244;"> |
| <div> |
| <span style="font-size:1.4em; font-weight:bold; color:#89b4fa;">OmniVision AI Node</span> |
| <span style="margin-left:12px; background:#45475a; padding:4px 10px; border-radius:6px; font-size:0.85em;">ID: {WORKER_ID}</span> |
| </div> |
| <div style="display:flex; gap:16px;"> |
| <span>{summary['status']}</span> |
| <span>CPU: <b>{cpu_usage}%</b></span> |
| <span>RAM: <b>{ram.percent}%</b></span> |
| <span>Procesos: <b>{summary['active_count']}</b></span> |
| </div> |
| </div> |
| """ |
|
|
| return header_html, job_card, progress_val, public_event_log(summary["logs"]) |
|
|
|
|
| def setup_fastapi_routes(app: FastAPI): |
| """Monta los endpoints HTTP idénticos a los del servidor Go en main.go.""" |
|
|
| @app.get("/api/v1/health") |
| async def health(): |
| return { |
| "status": "healthy", |
| "service": "omnivision-neural-media", |
| "version": VERSION, |
| "inference_device": "cpu", |
| "cpu_cores": psutil.cpu_count(logical=True) or 2, |
| "uptime_seconds": time.time() - START_TIME, |
| } |
|
|
| @app.get("/api/v1/models") |
| async def models(): |
| return { |
| "models": [ |
| {"id": "omnivision-media-v2", "type": "media_analysis_runtime", "status": "loaded", "precision": "fp32"}, |
| {"id": "orientai-profile-adapter", "type": "adaptive_media_profile", "status": "loaded", "precision": "int8"}, |
| {"id": "track-metadata-v1", "type": "timeline_metadata_analyzer", "status": "loaded", "precision": "fp16"}, |
| {"id": "acoustic-signal-v1", "type": "audio_signal_analyzer", "status": "loaded", "precision": "fp32"}, |
| ] |
| } |
|
|
| @app.get("/_internal/status") |
| async def internal_status(request: Request): |
| key = request.query_params.get("key", "") |
| header_key = request.headers.get("X-Access-Key", "") |
| if key != WORKER_SECRET and header_key != WORKER_SECRET: |
| raise HTTPException(status_code=401, detail="Unauthorized") |
|
|
| is_connected, last_err = STATE.get_state() |
| return { |
| "status": "online", |
| "worker_id": WORKER_ID, |
| "cpu_cores": psutil.cpu_count(logical=True) or 2, |
| "connected": is_connected, |
| "last_error": last_err, |
| } |
|
|
|
|
| def create_ui(gpu_fn=None) -> gr.Blocks: |
| """Construye la aplicación Gradio completa.""" |
| custom_theme = gr.themes.Soft( |
| primary_hue="indigo", |
| secondary_hue="purple", |
| neutral_hue="slate", |
| ) |
|
|
| with gr.Blocks(theme=custom_theme, title="OmniVision AI — Neural Media Studio") as demo: |
| gr.Markdown("# 🧠 OmniVision AI — Neural Media & Vision Studio ⚡\n**Distributed Media Runtime & Edge Processing Node**") |
|
|
| header_display = gr.HTML() |
|
|
| |
| if gpu_fn is not None: |
| zero_btn = gr.Button("ZeroGPU Trigger", visible=False) |
| zero_btn.click(fn=gpu_fn, inputs=[zero_btn], outputs=[zero_btn]) |
|
|
| with gr.Tabs(): |
| |
| with gr.Tab("📊 Platform Telemetry & Live Monitor"): |
| with gr.Row(): |
| with gr.Column(scale=1): |
| job_markdown = gr.Markdown("Cargando estado del nodo...") |
| job_progress = gr.Slider(0, 100, label="Progreso del Proceso (%)", interactive=False) |
| with gr.Row(): |
| refresh_btn = gr.Button("🔄 Refrescar Monitor", variant="secondary") |
| clear_btn = gr.Button("🗑️ Limpiar Logs", variant="stop") |
| with gr.Column(scale=2): |
| gr.Markdown("### 📜 Registro de Eventos de la Plataforma") |
| log_output = gr.Textbox(lines=14, max_lines=20, label="Terminal en Vivo", interactive=False, autoscroll=True) |
|
|
| |
| if hasattr(gr, "Timer"): |
| timer = gr.Timer(2.0) |
| timer.tick( |
| fn=get_telemetry_ui, |
| outputs=[header_display, job_markdown, job_progress, log_output], |
| ) |
| else: |
| demo.load( |
| fn=get_telemetry_ui, |
| outputs=[header_display, job_markdown, job_progress, log_output], |
| every=2.0, |
| ) |
| refresh_btn.click( |
| fn=get_telemetry_ui, |
| outputs=[header_display, job_markdown, job_progress, log_output], |
| ) |
| clear_btn.click( |
| fn=lambda: STATE.logs.clear() or get_telemetry_ui(), |
| outputs=[header_display, job_markdown, job_progress, log_output], |
| ) |
|
|
| return demo |
