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separate load functionality from inference client to loader client. Call loader client from inference to get the model.

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remove dummy dlls, remove resource loader from c#.

TODO: Load dlls separately by Loader UI and loader client

WIP
This commit is contained in:
Alex Bezdieniezhnykh
2025-06-06 20:04:03 +03:00
parent 500db31142
commit 7750025631
54 changed files with 353 additions and 571 deletions
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Azaion.Inference/main.pyx
+9 -29
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@@ -4,10 +4,9 @@ from queue import Queue
cimport constants
from threading import Thread
import yaml
from annotation cimport Annotation
from inference cimport Inference
from loader_client cimport LoaderClient
from remote_command cimport RemoteCommand, CommandType
from remote_command_handler cimport RemoteCommandHandler
@@ -17,14 +16,16 @@ cdef class CommandProcessor:
cdef object inference_queue
cdef bint running
cdef Inference inference
cdef LoaderClient loader_client
def __init__(self, int zmq_port, str api_url):
def __init__(self, int zmq_port, str loader_zmq_host, int loader_zmq_port, str api_url):
self.remote_handler = RemoteCommandHandler(zmq_port, self.on_command)
self.inference_queue = Queue(maxsize=constants.QUEUE_MAXSIZE)
self.remote_handler.start()
self.running = True
self.loader_client = LoaderClient(loader_zmq_host, loader_zmq_port)
#TODO: replace api_client to azaion_loader.exe call
self.inference = Inference(self.api_client, self.on_annotation)
self.inference = Inference(self.loader_client, self.on_annotation)
def start(self):
while self.running:
@@ -41,14 +42,12 @@ cdef class CommandProcessor:
cdef on_command(self, RemoteCommand command):
try:
if command.command_type == CommandType.LOGIN:
self.api_client.set_credentials(Credentials.from_msgpack(command.data))
elif command.command_type == CommandType.LOAD:
self.load_file(command)
elif command.command_type == CommandType.INFERENCE:
if command.command_type == CommandType.INFERENCE:
self.inference_queue.put(command)
elif command.command_type == CommandType.AI_AVAILABILITY_CHECK:
self.build_tensor_engine(command.client_id)
self.inference.build_tensor_engine(lambda status: self.remote_handler.send(
command.client_id, RemoteCommand(CommandType.AI_AVAILABILITY_RESULT, None, status).serialize()))
self.remote_handler.send(command.client_id, RemoteCommand(CommandType.AI_AVAILABILITY_RESULT, None, 'enabled').serialize())
elif command.command_type == CommandType.STOP_INFERENCE:
self.inference.stop()
elif command.command_type == CommandType.EXIT:
@@ -59,25 +58,6 @@ cdef class CommandProcessor:
except Exception as e:
print(f"Error handling client: {e}")
cdef build_tensor_engine(self, client_id):
self.inference.build_tensor_engine(lambda status: self.build_tensor_status_updater(client_id, status))
self.remote_handler.send(client_id, RemoteCommand(CommandType.AI_AVAILABILITY_RESULT, None, 'enabled').serialize())
cdef build_tensor_status_updater(self, bytes client_id, str status):
self.remote_handler.send(client_id, RemoteCommand(CommandType.AI_AVAILABILITY_RESULT, None, status).serialize())
cdef load_file(self, RemoteCommand command):
cdef RemoteCommand response
cdef FileData file_data
cdef bytes file_bytes
try:
file_data = FileData.from_msgpack(command.data)
file_bytes = self.api_client.load_bytes(file_data.filename, file_data.folder)
response = RemoteCommand(CommandType.DATA_BYTES, file_bytes)
except Exception as e:
response = RemoteCommand(CommandType.DATA_BYTES, None, str(e))
self.remote_handler.send(command.client_id, response.serialize())
cdef on_annotation(self, RemoteCommand cmd, Annotation annotation):
cdef RemoteCommand response = RemoteCommand(CommandType.INFERENCE_DATA, annotation.serialize())
self.remote_handler.send(cmd.client_id, response.serialize())