Merge pull request #2 from Ulas-Scan/develop

Develop

.github/workflows/deploy.yml

@@ -57,34 +57,3 @@ jobs:
         run: |
           docker build -t $GCP_REGION-docker.pkg.dev/$GCP_PROJECT_ID/ulascan/$APP_NAME:latest .
           docker push $GCP_REGION-docker.pkg.dev/$GCP_PROJECT_ID/ulascan/$APP_NAME:latest
-
-  deploy:
-    needs: build
-    runs-on: ubuntu-latest
-
-    steps:
-      - name: Install SSH client
-        run: sudo apt-get install -y ssh
-
-      - name: Set up SSH
-        run: |
-          echo "$SSH_PRIVATE_KEY" > ssh_key
-          chmod 600 ssh_key
-
-      - name: Deploy to GCE
-        run: |
-          ssh -o StrictHostKeyChecking=no \
-            -i ssh_key \
-            ulascan@$GCE_INSTANCE_IP \
-            "gcloud --quiet auth configure-docker $GCP_REGION-docker.pkg.dev \
-            && docker pull $GCP_REGION-docker.pkg.dev/$GCP_PROJECT_ID/ulascan/$APP_NAME:latest \
-            && docker stop $APP_NAME || true \
-            && docker rm --force $APP_NAME || true \
-            && docker run -d \
-                --name $APP_NAME \
-                -p 5000:5000 \
-                $GCP_REGION-docker.pkg.dev/$GCP_PROJECT_ID/ulascan/$APP_NAME:latest \
-            && docker image prune -f"
-
-      - name: Cleanup SSH key
-        run: rm ssh_key

app.py

@@ -1,4 +1,4 @@
-from flask import Flask, request
+from flask import Flask, request, jsonify
 from utils import get_model, get_tokenizer, predict_sentiment
 
 app = Flask(__name__)
@@ -10,15 +10,22 @@
 tokenizer = get_tokenizer(MODEL_NAME)
 model = get_model(PRETRAINED_PATH)
 
-@app.route("/predict/", methods=['GET'])
+@app.route("/predict", methods=['POST'])
 def predict():
-    statements = request.json.get("statements")
+    data = request.json
+    if data is None:
+        return jsonify({"error": "Invalid JSON"}), 400
+
+    statements = data.get("statements")
+    if statements is None:
+        return jsonify({"error": "No statements provided"}), 400
+
     # statements: list of reviews
     report = {'Positive': 0, 'Negative': 0}
     for statement in statements:
         sentiment = predict_sentiment(statement, tokenizer, model, MAX_LENGTH)
         report[sentiment] += 1
-    return report
+    return jsonify(report)
 
 if __name__ == "__main__":
-    app.run(host='0.0.0.0', port=5000)
+    app.run(host='0.0.0.0', port=5000)