Updated code with new package versions, changed condition in workflow (…

…#2)

.github/workflows/workflow.yml

@@ -1,5 +1,5 @@
 # Documentation: https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepsuses
-name: github_worflow
+name: github_workflow
 run-name: GitHub Workflow
 
 env:
@@ -47,11 +47,11 @@ env:
   # Logging level
   PROD_LOG_LEVEL: ${{ vars.PROD_LOG_LEVEL }}
   # Kube configuration
-  PROD_KUBE_CONFIG: ${{ secrets.DEV_KUBE_CONFIG }}
+  PROD_KUBE_CONFIG: ${{ secrets.PROD_KUBE_CONFIG }}
 
 # Allow one concurrent deployment
 concurrency:
-  group: github_worflow
+  group: github_workflow
   cancel-in-progress: true
 
 on:
@@ -123,7 +123,7 @@ jobs:
   release:
     needs: test
     runs-on: ubuntu-latest
-    if: ${{ vars.RUN_CICD == 'true' && success() && (vars.DEPLOY_DEV == 'true' || vars.DEPLOY_PROD == 'true') }}
+    if: ${{ vars.RUN_CICD == 'true' && success() && (github.ref == 'refs/heads/main' || github.ref == 'refs/heads/prod') && (vars.DEPLOY_DEV == 'true' || vars.DEPLOY_PROD == 'true') }}
     steps:
       - name: Clone repository
         uses: actions/checkout@v3

model-serving/requirements-all.txt

@@ -19,9 +19,9 @@ contourpy==1.1.0
 coverage==7.2.7
 cycler==0.11.0
 dnspython==2.3.0
-email-validator==1.3.0
+email-validator==2.1.0.post1
 exceptiongroup==1.1.1
-fastapi==0.87.0
+fastapi==0.108.0
 flake8==5.0.4
 flatbuffers==1.12
 fonttools==4.40.0
@@ -60,7 +60,8 @@ protobuf==3.19.6
 pyasn1==0.5.0
 pyasn1-modules==0.3.0
 pycodestyle==2.9.1
-pydantic==1.10.9
+pydantic==2.5.3
+pydantic-settings==2.1.0
 pyflakes==2.5.0
 pyparsing==3.1.0
 pytest==7.2.0
@@ -80,7 +81,7 @@ scipy==1.11.0
 setuptools==67.6.1
 six==1.16.0
 sniffio==1.3.0
-starlette==0.21.0
+starlette==0.29.0
 tensorboard==2.9.1
 tensorboard-data-server==0.6.1
 tensorboard-plugin-wit==1.8.1
@@ -90,7 +91,7 @@ tensorflow-io-gcs-filesystem==0.32.0
 termcolor==2.3.0
 threadpoolctl==3.1.0
 tomli==2.0.1
-typing_extensions==4.6.3
+typing_extensions==4.9.0
 urllib3==1.26.16
 uvicorn==0.19.0
 Werkzeug==2.3.6

model-serving/src/main.py

@@ -5,9 +5,8 @@
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import RedirectResponse
 from common_code.config import get_settings
-from pydantic import Field
 from common_code.http_client import HttpClient
-from common_code.logger.logger import get_logger
+from common_code.logger.logger import get_logger, Logger
 from common_code.service.controller import router as service_router
 from common_code.service.service import ServiceService
 from common_code.storage.service import StorageService
@@ -18,6 +17,7 @@
 from common_code.service.enums import ServiceStatus
 from common_code.common.enums import FieldDescriptionType, ExecutionUnitTagName, ExecutionUnitTagAcronym
 from common_code.common.models import FieldDescription, ExecutionUnitTag
+from contextlib import asynccontextmanager
 
 # Imports required by the service's model
 import tensorflow as tf
@@ -35,8 +35,8 @@ class MyService(Service):
     """
 
     # Any additional fields must be excluded for Pydantic to work
-    model: object = Field(exclude=True)
-    logger: object = Field(exclude=True)
+    _model: object
+    _logger: Logger
 
     def __init__(self):
         super().__init__(
@@ -64,16 +64,16 @@ def __init__(self):
             ],
             has_ai=True
         )
-        self.model = tf.keras.models.load_model(os.path.join(os.path.dirname(__file__), "..", "ae_model.h5"))
-        self.logger = get_logger(settings)
+        self._model = tf.keras.models.load_model(os.path.join(os.path.dirname(__file__), "..", "ae_model.h5"))
+        self._logger = get_logger(settings)
 
     def process(self, data):
         raw = str(data["text"].data)[2:-1]
         raw = raw.replace('\\t', ',').replace('\\n', '\n').replace('\\r', '\n')
         X_test = pd.read_csv(io.StringIO(raw), dtype={"value": np.float64})
 
         # Use the model to reconstruct the original time series data
-        reconstructed_X = self.model.predict(X_test)
+        reconstructed_X = self._model.predict(X_test)
 
         # Calculate the reconstruction error for each point in the time series
         reconstruction_error = np.square(X_test - reconstructed_X).mean(axis=1)
@@ -97,6 +97,54 @@ def process(self, data):
         }
 
 
+service_service: ServiceService | None = None
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    # Manual instances because startup events doesn't support Dependency Injection
+    # https://github.com/tiangolo/fastapi/issues/2057
+    # https://github.com/tiangolo/fastapi/issues/425
+
+    # Global variable
+    global service_service
+
+    # Startup
+    logger = get_logger(settings)
+    http_client = HttpClient()
+    storage_service = StorageService(logger)
+    my_service = MyService()
+    tasks_service = TasksService(logger, settings, http_client, storage_service)
+    service_service = ServiceService(logger, settings, http_client, tasks_service)
+
+    tasks_service.set_service(my_service)
+
+    # Start the tasks service
+    tasks_service.start()
+
+    async def announce():
+        retries = settings.engine_announce_retries
+        for engine_url in settings.engine_urls:
+            announced = False
+            while not announced and retries > 0:
+                announced = await service_service.announce_service(my_service, engine_url)
+                retries -= 1
+                if not announced:
+                    time.sleep(settings.engine_announce_retry_delay)
+                    if retries == 0:
+                        logger.warning(f"Aborting service announcement after "
+                                       f"{settings.engine_announce_retries} retries")
+
+    # Announce the service to its engine
+    asyncio.ensure_future(announce())
+
+    yield
+
+    # Shutdown
+    for engine_url in settings.engine_urls:
+        await service_service.graceful_shutdown(my_service, engine_url)
+
+
 api_description = """
 Anomaly detection of a time series with an autoencoder.
 """
@@ -106,6 +154,7 @@ def process(self, data):
 
 # Define the FastAPI application with information
 app = FastAPI(
+    lifespan=lifespan,
     title="Autoencoder Anomaly Detection",
     description=api_description,
     version="1.0.0",
@@ -141,53 +190,3 @@ def process(self, data):
 @app.get("/", include_in_schema=False)
 async def root():
     return RedirectResponse("/docs", status_code=301)
-
-
-service_service: ServiceService | None = None
-
-
-@app.on_event("startup")
-async def startup_event():
-    # Manual instances because startup events doesn't support Dependency Injection
-    # https://github.com/tiangolo/fastapi/issues/2057
-    # https://github.com/tiangolo/fastapi/issues/425
-
-    # Global variable
-    global service_service
-
-    logger = get_logger(settings)
-    http_client = HttpClient()
-    storage_service = StorageService(logger)
-    my_service = MyService()
-    tasks_service = TasksService(logger, settings, http_client, storage_service)
-    service_service = ServiceService(logger, settings, http_client, tasks_service)
-
-    tasks_service.set_service(my_service)
-
-    # Start the tasks service
-    tasks_service.start()
-
-    async def announce():
-        retries = settings.engine_announce_retries
-        for engine_url in settings.engine_urls:
-            announced = False
-            while not announced and retries > 0:
-                announced = await service_service.announce_service(my_service, engine_url)
-                retries -= 1
-                if not announced:
-                    time.sleep(settings.engine_announce_retry_delay)
-                    if retries == 0:
-                        logger.warning(f"Aborting service announcement after "
-                                       f"{settings.engine_announce_retries} retries")
-
-    # Announce the service to its engine
-    asyncio.ensure_future(announce())
-
-
-@app.on_event("shutdown")
-async def shutdown_event():
-    # Global variable
-    global service_service
-    my_service = MyService()
-    for engine_url in settings.engine_urls:
-        await service_service.graceful_shutdown(my_service, engine_url)