Restore private TiGa file workflow with HF wrapper guidance

README.md

@@ -6,9 +6,9 @@ python_version: "3.10"
 app_file: app.py
 ---
 
-Private standard-Gradio browser baseline, synthetic tests only. No user upload interface.
-No custom login, job access keys, or user result store in this diagnostic entrypoint.
-Run explicitly through the Hugging Face Space page; GPU uses the visitor allowance.
-Simulator by Zorro909: https://github.com/Zorro909/driving_sim_rs
-HF implementation and UI by TiGa: https://github.com/seeker-cyber-maker/driving_sim_rs
-Not a public release or a full trainer. Earlier custom-interface snapshots are preserved.
+Private CPU/ZeroGPU integration candidate. Custom interface with Gradio Server on port 7860.
+Simulator: https://github.com/Zorro909/driving_sim_rs
+Hosting adaptation and UI: TiGa https://github.com/seeker-cyber-maker/driving_sim_rs
+CPU is the default; GPU requests explicitly use ZeroGPU. No automatic fallback. No bundled tracks or networks.
+One server process; no persistent storage. See DATA_POLICY.md for retention limits.
+Not yet verified in the hosted Linux runtime; do not publish as a stable release.

RELEASE_MANIFEST.json

@@ -5,18 +5,17 @@
     "GODOT_LICENSE": "fb2b3bb82c60f1e76841ba2122eb902f8e39c151476fe21ce10c9a05d1045304",
     "IMPORTER_BUILD_RECEIPT.json": "4ba5c533cc617105478e4d85c83f456a7dfa68b1388049624619871ba9e42e9d",
     "LICENSE": "53d5851b6440feeae36f72a5f57fcab37858c48b7084765ece4b0c54b9a28ed8",
-    "README.md": "905cadea3a2fe0042254d6b21093c256e3113e9a19592b7abf9a58d873c7c97c",
-    "app.py": "47605919270f695afd4a5b1ec477ab845014d4b95c57cf22855eba4d34233695",
+    "README.md": "48b536eb04507f65e4ea4101e30d34368f26719f75a2a294b75523f7c0225c37",
+    "app.py": "f45a2e3b11f906650696c0173c96305ae4c9e08f656a6223c7296eb43d98f970",
     "app_release.py": "40cef7e65bbcf9798eaa1374a2c7be4bb45a5d4e70e981a1eeb8b0b2f2a00c35",
     "assets/formula_template.json": "80f745df82bb7be45af52785fd582460bcddc63c5a4e1d8375d85b3122db4c6b",
     "bin/altd-sim": "2f2f2144ae14b0ef599ca8510f95712da00243c6875881491d384b394e7499f7",
     "bin/extract_saved_track": "3a7733c45b4301a786fcbfe92660a1c484749272da5f608d62f34878bd4ff31a",
     "bin/libaltd_gpu.so": "279d6353b4c691686d6aeeae6abfd4a82b959e9b604f079a6c45f9823b48a87a",
-    "client.js": "d0a338ff461ef5115019e0362e33a12a15569f135dc4e9573daa74045b31de72",
+    "client.js": "6862b79a6a97639372a4946456cf8f24e37f38bfc12e1eb48a08cf6ba8f3e26b",
     "delivery.py": "4f5a4e45df92e5cbfdef6eb449ede9ba26217fe24da376fafddae5cbbb73847a",
     "gpu_tickets.py": "9e2cf757ddc46ca30b49cd6de07e5d84f328a858240afaad2e72453d24803f5a",
-    "index.html": "caeafcd208a638cd8c4235ca282b5b6451b81eb0e363fcfbb2ee02ed021a4db0",
-    "make_test_inputs.py": "3c80813d63787877c071d0ba322dc444fea8a392705867a6965e16a30e104496",
+    "index.html": "91977f278a2568b5d2b217f9d8108f209568cd4491c8ee629f66d7c86efcd7fd",
     "requirements.txt": "9b532747e51bd052e82090ece860d6dafe027407f4512dc74272c148ea104c22",
     "server.py": "6375fb9f0a6ed39be0d7ce3cbe5c4c820e412e91417f424ad10a1b5f6f94062f",
     "vendor/gradio-client/LICENSE": "c71d239df91726fc519c6eb72d318ec65820627232b2f796219e87dcf35d0ab4",

app.py

@@ -1,62 +1,107 @@
-"""Standard Gradio browser baseline: synthetic inputs only, no custom sessions."""
+"""Private ZeroGPU integration candidate. Never enable on CPU-only hosting.
+
+Browser must invoke /gpu_train with @gradio/client for caller quota propagation.
+The queue carries only an opaque ticket; result bytes stay in the existing store.
+"""
+import asyncio
+import base64
+from contextlib import asynccontextmanager
+import json
+import threading
 import os
 os.environ['GRADIO_ANALYTICS_ENABLED']='False'
-import hashlib
-import tempfile
 import gradio as gr
 import spaces
-from app_release import ROOT,verify_package
-from make_test_inputs import make
-from worker import run_native
-
-@spaces.GPU(duration=30)
-def gpu_calculation():
-    import torch
-    value=torch.arange(16,device='cuda',dtype=torch.float32).sum().item()
-    if value!=120:raise RuntimeError('Unexpected GPU result')
-    return {'status':'PASS','test':'GPU arithmetic','sum':value,
-        'device':torch.cuda.get_device_name(0),'custom_sessions':False}
-
-def simulator(gpu=False):
-    with tempfile.TemporaryDirectory(prefix='tiga-synthetic-') as directory:
-        p=make(directory)
-        payload,report=run_native((p/'synthetic.track').read_bytes(),
-            (p/'synthetic.evolution').read_bytes(),binary=ROOT/'bin/altd-sim',
-            importer=ROOT/'bin/extract_saved_track',scene_template=ROOT/'assets/formula_template.json',
-            gpu_library=ROOT/'bin/libaltd_gpu.so' if gpu else None,with_report=True)
-        receipt={'status':'PASS','test':'synthetic simulator','report':report,
-            'candidate_sha256':hashlib.sha256(payload).hexdigest(),'candidate_bytes':len(payload),
-            'custom_sessions':False,'user_uploads':False}
-    return receipt
-
-@spaces.GPU(duration=90)
-def gpu_simulator():
-    return simulator(True)
-
-def cpu_simulator():
-    return simulator(False)
-
-def build_demo():
-    with gr.Blocks(analytics_enabled=False) as demo:
-        gr.Markdown('''# AI Learns To Drive — browser baseline
-Simulator by [Zorro909](https://github.com/Zorro909/driving_sim_rs).
-HF implementation and UI by TiGa (seeker-cyber-maker).
-
-Private diagnostic stage: standard Gradio interface, no custom login or job sessions.
-Use this page inside Hugging Face while signed in. No personal token is requested.
-No user uploads: the simulator generates disposable synthetic inputs and returns only a receipt.
-GPU tests use your HF allowance. Nothing runs automatically. This is not the full trainer.
-''')
-        result=gr.JSON(label='Test receipt')
-        for label,fn,name in [('1. Test GPU connection',gpu_calculation,'gpu_calculation'),
-                              ('2. Test CPU simulator',cpu_simulator,'cpu_simulator'),
-                              ('3. Test GPU simulator',gpu_simulator,'gpu_simulator')]:
-            gr.Button(label).click(fn,outputs=result,api_name=name,
-                concurrency_limit=1,concurrency_id='baseline')
-    return demo
-
-if __name__=='__main__':
+from fastapi import HTTPException,Request
+from fastapi.responses import FileResponse,JSONResponse
+from app_release import ROOT,cpu_worker,verify_package
+from gpu_tickets import InputTickets
+from server import create_app
+from worker import run_native,track_input,network_input
+
+def build_app(cuda_call):
+    base=create_app(worker=cpu_worker)
+    tickets=InputTickets()
+    admission=threading.BoundedSemaphore(1)
+
+    @asynccontextmanager
+    async def lifespan(app):
+        async def expire():
+            while True:
+                await asyncio.sleep(1)
+                tickets.expire()
+        async with base.router.lifespan_context(base):
+            task=asyncio.create_task(expire())
+            try:yield
+            finally:
+                task.cancel()
+                try:await task
+                except asyncio.CancelledError:pass
+                tickets.clear()
+
+    app=gr.Server(lifespan=lifespan,docs_url=None,redoc_url=None,openapi_url=None)
+
+    @app.middleware('http')
+    async def no_framework_file_storage(request,call_next):
+        # This UI sends bounded bytes through prepare, never Gradio file uploads.
+        path=request.url.path
+        if path.startswith(('/gradio_api/upload','/gradio_api/file=',
+                            '/gradio_api/stream/','/gradio_api/run/','/gradio_api/runs')):
+            return JSONResponse({'detail':'File storage and run history are disabled'},status_code=404)
+        return await call_next(request)
+
+    @app.get('/api/capabilities')
+    def capabilities():
+        return {'cpu':True,'gpu':True,'default':'cpu','gpu_transport':'gradio-ticket'}
+
+    @app.get('/gradio-client.js')
+    def javascript_client():
+        return FileResponse(ROOT/'vendor/gradio-client/dist/index.min.js',media_type='text/javascript')
+
+    @app.post('/api/gpu/prepare')
+    async def prepare(request:Request):
+        data=bytearray()
+        async for chunk in request.stream():
+            if len(data)+len(chunk)>3*1024*1024:raise HTTPException(413,'Request too large')
+            data.extend(chunk)
+        try:
+            body=json.loads(data)
+            track=base64.b64decode(body['track'],validate=True)
+            network=base64.b64decode(body['network'],validate=True)
+            track_input(track);network_input(network)
+            ticket=tickets.put(track,network,body.get('automatic',True))
+            return {'ticket':ticket,'expires_in_seconds':120}
+        except RuntimeError:raise HTTPException(429,'GPU input capacity reached') from None
+        except Exception:raise HTTPException(400,'Invalid GPU input') from None
+        finally:data.clear()
+
+    @app.api(name='gpu_train',concurrency_limit=1,concurrency_id='gpu',api_visibility='undocumented')
+    def gpu_train(ticket:str)->dict:
+        if not admission.acquire(blocking=False):raise ValueError('GPU worker busy')
+        try:
+            track,network,automatic=tickets.take(ticket)
+            payload,report=cuda_call(track,network)
+            return {**base.state.results.publish(payload,automatic),'backend':'gpu','report':report}
+        finally:admission.release()
+
+    # Existing download/status/ACK/delete and CPU routes use the same result store.
+    for route in base.router.routes:
+        if getattr(route,'path',None)!='/api/capabilities':app.router.routes.append(route)
+    for middleware in base.user_middleware:
+        app.add_middleware(middleware.cls,*middleware.args,**middleware.kwargs)
+    return app
+
+def main():
     verify_package()
     for name in ('altd-sim','extract_saved_track'):(ROOT/'bin'/name).chmod(0o755)
-    build_demo().queue(max_size=1).launch(server_name='0.0.0.0',server_port=7860,
-        run_history=False,enable_monitoring=False,show_error=False)
+
+    @spaces.GPU(duration=90)
+    def cuda(track,network):
+        return run_native(track,network,binary=ROOT/'bin/altd-sim',
+            importer=ROOT/'bin/extract_saved_track',scene_template=ROOT/'assets/formula_template.json',
+            gpu_library=ROOT/'bin/libaltd_gpu.so',with_report=True)
+
+    build_app(cuda).launch(server_name='0.0.0.0',server_port=7860,run_history=False,
+        enable_monitoring=False,show_error=False)
+
+if __name__=='__main__':main()

client.js

@@ -6,6 +6,8 @@ let localResult = null;
 let capabilitiesReady = false;
 let gpuTransport = null;
 let gradioClient = null;
+// Navigation guard only, not an authentication or authorization check.
+const hostedStandalone = location.hostname.endsWith('.hf.space') && window.self === window.top;
 const say = text => { $('status').textContent = text; };
 function buttons() {
   $('run').disabled = busy || !!job || !capabilitiesReady;
@@ -47,6 +49,7 @@ $('run').onclick = async () => {
   try {
     const body={track:await encoded($('track').files[0]),network:await encoded($('network').files[0]),automatic:$('automatic').checked,backend:$('backend').value};
     if(body.backend==='gpu' && gpuTransport==='gradio-ticket'){
+      if(hostedStandalone)throw new Error('For GPU, open the Hugging Face Space page while signed in. CPU remains available here.');
       // Official client preserves the caller's ZeroGPU quota context.
       if(!gradioClient){
         const {Client}=await import('/gradio-client.js');
@@ -123,14 +126,15 @@ async function connect(){
     const capabilities=await (await request('/api/capabilities',{signal:controller.signal})).json();
     if(capabilities.cpu!==true)throw new Error('CPU unavailable');
     gpuTransport=capabilities.gpu_transport??null;
-    $('gpuOption').disabled=!capabilities.gpu;
-    $('backendNote').textContent=capabilities.gpu?'CPU uses no GPU allowance. GPU requires available allowance. No automatic switching.':'CPU available. GPU is not connected on this deployment; no GPU allowance is needed for CPU.';
+    $('gpuOption').disabled=!capabilities.gpu || hostedStandalone;
+    if(hostedStandalone && $('backend').value==='gpu')$('backend').value='cpu';
+    $('backendNote').textContent=capabilities.gpu?(hostedStandalone?'CPU available here. For GPU, open the Hugging Face Space page above to use your signed-in allowance.':'CPU uses no GPU allowance. GPU uses your HF allowance; stay inside the HF Space page. No automatic switching.'):'CPU available. GPU is not connected on this deployment; no GPU allowance is needed for CPU.';
     capabilitiesReady=true; buttons();
     say('Connected. Choose your track and network, then run the test.');
   } catch(error) {
     capabilitiesReady=false; buttons();
     $('backendNote').textContent='Connection unavailable — training is disabled.';
-    say('Private HF access may be blocked inside the embedded page. Use “Open app in its own tab” above, or retry. No run was started.');
+    say('Could not reach this app. Confirm HF access and retry. Private embedded access can depend on browser cookie settings. No run was started.');
   } finally {clearTimeout(timeout);$('retry').disabled=false;}
 }
 $('retry').onclick=()=>{if(!busy&&!job)connect();};

index.html

@@ -7,7 +7,7 @@
 <p>Game by ActivationFunction · <a href="https://store.steampowered.com/app/3312030/AI_Learns_To_Drive/">Steam store</a></p>
 <p>Simulator by <a href="https://github.com/Zorro909/driving_sim_rs">Zorro909</a> · UI and HF implementation by <a href="https://github.com/seeker-cyber-maker/driving_sim_rs">TiGa (seeker-cyber-maker)</a></p>
 <p class="hint">Private release integration · bounded training test. No app account needed; private hosting may require access.</p>
-<p><a id="standalone" href="" target="_blank" rel="noopener noreferrer">Open app in its own tab — recommended for private HF access</a><br><small>Uses this page’s existing HF access link. No privacy-setting changes needed. Select files again in the new tab; do not share private access links.</small></p>
+<p><a href="https://huggingface.co/spaces/TiGa-RCE/ald-tao-gpu" target="_blank" rel="noopener noreferrer">Open the Hugging Face Space page</a><br><small>For GPU, use the app inside that page while signed in to HF. A standalone app tab may not receive your account allowance. CPU does not use GPU allowance. No personal token or separate app login is requested.</small></p>
 <div class="grid"><section class="card"><h2>Simulation</h2><p>4 vehicles · 1 generation · 60 requested ticks. Formula networks, steering and acceleration; speed and raycast sensors. This is not yet the full trainer.</p>
 <p><label for="backend">Compute</label><select id="backend" disabled><option value="cpu">CPU — no GPU allowance</option><option id="gpuOption" value="gpu" disabled>GPU — uses GPU allowance</option></select></p><p id="backendNote" class="hint">Checking available backends…</p>
 <button id="retry" type="button">Retry connection</button>

make_test_inputs.py

@@ -1,27 +0,0 @@
-"""Write disposable synthetic inputs, never copy a campaign track or trained network.
-
-Track layout matches upstream print_saved_fixture's fixed generator output.
-Tile IDs reference upstream resources: their provenance remains a release gate.
-"""
-import gzip
-import json
-from pathlib import Path
-import tempfile
-
-def make(directory):
-    directory=Path(directory); directory.mkdir(parents=True,exist_ok=True)
-    cells=[(0,0,2,3),*( (x,0,5,0) for x in range(1,5)),(5,0,2,2),
-           (5,1,102,0),*((x,1,105,0) for x in range(4,0,-1)),(0,1,102,1)]
-    tiles={}
-    for x,y,atlas,alternative in cells:
-        coord=f'Vector2i({x}, {y})'
-        tiles[coord]={'Block':{'TileSetId':{'AtlasId':atlas,'AlternativeId':alternative}},'Coords':coord}
-    track={'Tiles':tiles,'StartTileCoords':'Vector2i(0, 0)',
-           'StartTileConnection':{'Side':3,'Index':1,'Type':0}}
-    network={'Name':'Synthetic smoke input','Type':0,'Outputs':[0,1],'Sensors':[{'$type':'speed'}],
-        'NeuralNetwork':{'Shape':[1,2],'Weights':[[[0.,0.]]],'Biases':[[0.,1.]]}}
-    for name,obj in [('synthetic.track',track),('synthetic.evolution',network)]:
-        (directory/name).write_bytes(gzip.compress(json.dumps(obj).encode(),mtime=0))
-    return directory
-
-if __name__=='__main__': print(make(tempfile.mkdtemp(prefix='tiga-browser-fixtures-')))