adding new files

app.py

@@ -1,30 +1,47 @@
 import gradio as gr
 import pandas as pd
-import seaborn as sns
-import matplotlib.pyplot as plt
-
-
-def plot_pens(category1, value1, category2, value2, category3, value3, category4, value4, category5, value5):
-    df_pens = pd.DataFrame(
-        {
-            "category": [category1, category2, category3, category4, category5],
-            "inventory": [value1, value2, value3, value4, value5],
-        }
-    )
-    fig, ax = plt.subplots()
-    ax.plot(df_pens['category'], df_pens['inventory'], marker='o', linestyle='-', color='b')
-    ax.set_xlabel('Category')
-    ax.set_ylabel('Inventory')
-    ax.set_title('Line Chart of Pens Inventory')
-    return fig
-
-
-iface = gr.Interface(
-    fn=plot_pens,
-    inputs=['textbox', 'number', 'textbox', 'number', 'textbox', 'number', 'textbox', 'number', 'textbox', 'number'],
-    outputs=['plot'],
-    title="Line Chart of Pens Inventory",
-    description="Visualize the inventory of pens with a line chart.",
-    article="Talk more about the pens here, shall we?",
-    theme='peach'
-).launch()
+from google.cloud import storage
+import io
+import os
+import json
+import tempfile
+
+gcs_bucket_name = "ow-stu-us-ce1-ai-platform"
+
+# File path in GCS bucket
+gcs_file_path = "deepak_6593/db.csv"
+
+
+# process of getting credentials
+def get_credentials():
+    creds_json_str = os.getenv("BOB") # get json credentials stored as a string
+    if creds_json_str is None:
+        raise ValueError("GOOGLE_APPLICATION_CREDENTIALS_JSON not found in environment")
+
+    # create a temporary file
+    with tempfile.NamedTemporaryFile(mode="w+", delete=False, suffix=".json") as temp:
+        temp.write(creds_json_str) # write in json format
+        temp_filename = temp.name 
+
+    return temp_filename
+    
+# pass
+os.environ["GOOGLE_APPLICATION_CREDENTIALS"]= get_credentials()
+
+# Ensure the GCS bucket exists
+gcs_client = storage.Client()
+gcs_bucket = gcs_client.bucket(gcs_bucket_name)
+
+def get_data():
+    blob = gcs_bucket.blob(gcs_file_path)
+    return pd.read_csv(io.BytesIO(blob.download_as_bytes()))
+
+with gr.Blocks() as demo:
+    gr.Markdown("# 📈 Real-Time Line Plot")
+    with gr.Row():
+        with gr.Column():
+            gr.DataFrame(get_data, every=1)
+        with gr.Column():
+            gr.LinePlot(get_data, every=1, x="category", y="score", y_title="score(marks)", overlay_point=True, width=500, height=500)
+
+demo.queue().launch()

requirements.txt

@@ -1,4 +1,5 @@
 gradio
 pandas
 seaborn
-matplotlib
+matplotlib
+google-cloud-storage