uploading some test files, not necessarily final

cloudbuild.yaml

@@ -0,0 +1,21 @@
+steps:
+  # build the container image
+  - name: "gcr.io/cloud-builders/docker"
+    args: ["build", "-t", "gcr.io/$PROJECT_ID/shakti0:$COMMIT_SHA", "."]
+  # push the container image to Container Registry
+  - name: "gcr.io/cloud-builders/docker"
+    args: ["push", "gcr.io/$PROJECT_ID/shakti0:$COMMIT_SHA"]
+  # Deploy container image to Cloud Run
+  - name: "gcr.io/cloud-builders/gcloud"
+    args:
+      - "run"
+      - "deploy"
+      - "shakti0"
+      - "--image"
+      - "gcr.io/$PROJECT_ID/shakti0:$COMMIT_SHA"
+      - "--region"
+      - "us-east1"
+      - "--platform"
+      - "managed"
+images:
+  - "gcr.io/$PROJECT_ID/shakti0:$COMMIT_SHA"

test1.py

@@ -0,0 +1,33 @@
+import os
+
+from flask import Flask, jsonify
+from gcp_utils.googlebucket import gcs_download_file
+from joblib import load
+
+app = Flask(__name__)
+
+model = None
+
+
+@app.before_request
+def load_resources():
+    '''Flask template is currently only for scikit-learn models'''
+    if not model:
+        model_path = gcs_download_file(os.environ.get("MODEL_PATH"))
+        model = load(model_path)
+
+
+def transform_data(input_data):
+    # no transform by default
+    return input_data
+
+
+@app.route('/')
+def predict(input_data):
+    transformed_data = transform_data(input_data)
+    prediction = model.predict(transformed_data)
+    return jsonify({"prediction": prediction})
+
+
+if __name__ == "__main__":
+    app.run(host='0.0.0.0', port=int(os.environ.get('PORT', 8080)))