Private r8 standard Gradio browser baseline, synthetic tests only

README.md

@@ -6,9 +6,9 @@ python_version: "3.10"
 app_file: app.py
 ---
 
-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-Not yet verified in the hosted Linux runtime; do not publish as a stable release.
+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.

RELEASE_MANIFEST.json

@@ -5,8 +5,8 @@
     "GODOT_LICENSE": "fb2b3bb82c60f1e76841ba2122eb902f8e39c151476fe21ce10c9a05d1045304",
     "IMPORTER_BUILD_RECEIPT.json": "4ba5c533cc617105478e4d85c83f456a7dfa68b1388049624619871ba9e42e9d",
     "LICENSE": "53d5851b6440feeae36f72a5f57fcab37858c48b7084765ece4b0c54b9a28ed8",
-    "README.md": "48b536eb04507f65e4ea4101e30d34368f26719f75a2a294b75523f7c0225c37",
-    "app.py": "77c5b760c7c74bdd9c143165f80321f9d8a6407d7d60c2d2035cf25704f3c071",
+    "README.md": "905cadea3a2fe0042254d6b21093c256e3113e9a19592b7abf9a58d873c7c97c",
+    "app.py": "47605919270f695afd4a5b1ec477ab845014d4b95c57cf22855eba4d34233695",
     "app_release.py": "40cef7e65bbcf9798eaa1374a2c7be4bb45a5d4e70e981a1eeb8b0b2f2a00c35",
     "assets/formula_template.json": "80f745df82bb7be45af52785fd582460bcddc63c5a4e1d8375d85b3122db4c6b",
     "bin/altd-sim": "2f2f2144ae14b0ef599ca8510f95712da00243c6875881491d384b394e7499f7",
@@ -16,6 +16,7 @@
     "delivery.py": "4f5a4e45df92e5cbfdef6eb449ede9ba26217fe24da376fafddae5cbbb73847a",
     "gpu_tickets.py": "9e2cf757ddc46ca30b49cd6de07e5d84f328a858240afaad2e72453d24803f5a",
     "index.html": "caeafcd208a638cd8c4235ca282b5b6451b81eb0e363fcfbb2ee02ed021a4db0",
+    "make_test_inputs.py": "3c80813d63787877c071d0ba322dc444fea8a392705867a6965e16a30e104496",
     "requirements.txt": "9b532747e51bd052e82090ece860d6dafe027407f4512dc74272c148ea104c22",
     "server.py": "6375fb9f0a6ed39be0d7ce3cbe5c4c820e412e91417f424ad10a1b5f6f94062f",
     "vendor/gradio-client/LICENSE": "c71d239df91726fc519c6eb72d318ec65820627232b2f796219e87dcf35d0ab4",

app.py

@@ -1,107 +1,62 @@
-"""Undeployed 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
+"""Standard Gradio browser baseline: synthetic inputs only, no custom sessions."""
 import os
 os.environ['GRADIO_ANALYTICS_ENABLED']='False'
+import hashlib
+import tempfile
 import gradio as gr
 import spaces
-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():
+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__':
     verify_package()
     for name in ('altd-sim','extract_saved_track'):(ROOT/'bin'/name).chmod(0o755)
-
-    @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()
+    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)

make_test_inputs.py

@@ -0,0 +1,27 @@
+"""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-')))