Merge pull request #72 from Big-Data-Programming/feature/delta_enance…

…ments frontend fixed final
Big-Data-Programming · Sep 28, 2023 · ba3b045 · ba3b045
2 parents 9a83d4f + 8599903
commit ba3b045
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Showing 3 changed files with 7 additions and 5 deletions.
diff --git a/.github/workflows/push-frontend-container-to-hub.yaml b/.github/workflows/push-frontend-container-to-hub.yaml
@@ -19,7 +19,7 @@ jobs:
       - name: Build and Tag Docker image
         run: |
           docker build -t sa_analytics_dashboard -f sa_app/dashboard/Dockerfile_dashboard .
-          docker tag sa_analytics_dashboard prabhupad26/sa_analytics_dashboard:0.24
+          docker tag sa_analytics_dashboard prabhupad26/sa_analytics_dashboard:0.25
 
       - name: Push Docker image to Docker Hub
-        run: docker push prabhupad26/sa_analytics_dashboard:0.24
+        run: docker push prabhupad26/sa_analytics_dashboard:0.25
diff --git a/kubernetes-manifests/frontend.yaml b/kubernetes-manifests/frontend.yaml
@@ -14,7 +14,7 @@ spec:
     spec:
       containers:
       - name: sa-app-dashboard
-        image: prabhupad26/sa_analytics_dashboard:0.24
+        image: prabhupad26/sa_analytics_dashboard:0.25
         ports:
         - containerPort: 8501  # Port for Streamlit app
 ---

diff --git a/sa_app/dashboard/app.py b/sa_app/dashboard/app.py
@@ -72,6 +72,7 @@ def get_data_iterator() -> pd.DataFrame:
 placeholder = st.empty()
 tweet_count = 0
 sentiment_cnt = {"positive": 0, "negative": 0}
+label_mapping = {0: "negative", 4: "positive", 1: "positive"}
 
 results = []
 
@@ -82,7 +83,8 @@ def get_data_iterator() -> pd.DataFrame:
             # Inserting the tweet to database
             u_id = insert_to_db(row[4], row[5])
             # Run model inference here
-            sentiment_pred = get_sentiment(u_id, row[5])
+            # sentiment_pred = get_sentiment(u_id, row[5])
+            sentiment_pred = label_mapping[row[0]]
             print(f"For {row[5]}, prediction is : {sentiment_pred}")
             tweet_count += 1
 
@@ -104,7 +106,7 @@ def get_data_iterator() -> pd.DataFrame:
 
                     kpi3.metric(label="Negative Count", value=sentiment_cnt["negative"])
 
-                    results.append([row[5], sentiment_pred, row[0]])
+                    results.append([row[5], label_mapping[row[0]]])
 
 update_donut(sentiment_cnt)
 st.table(results)