Update app.py

app.py

@@ -1,19 +1,39 @@
-import torch
 import gradio as gr
-from diffusers import StableDiffusionPipeline
-
-model_id = "runwayml/stable-diffusion-v1-5"  # You can change to your own model
-pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
-pipe = pipe.to("cuda")
-
-def generate(prompt):
-    image = pipe(prompt).images[0]
-    return image
-
-gr.Interface(
-    fn=generate,
-    inputs=gr.Textbox(label="Enter your prompt"),
-    outputs=gr.Image(type="pil"),
-    title="🎨 AI Image Generator",
-    description="Enter a prompt to generate images using Stable Diffusion",
-).launch()
+import pandas as pd
+import matplotlib.pyplot as plt
+
+# Sample population data (you can use a CSV instead)
+data = {
+    "Country": ["India", "China", "USA", "Indonesia", "Brazil"],
+    "Population": [1400000000, 1410000000, 331000000, 273000000, 213000000]
+}
+df = pd.DataFrame(data)
+
+def plot_chart(countries, chart_type):
+    filtered_df = df[df["Country"].isin(countries)]
+    plt.figure(figsize=(8, 5))
+
+    if chart_type == "Bar":
+        plt.bar(filtered_df["Country"], filtered_df["Population"], color="skyblue")
+        plt.ylabel("Population")
+    else:  # Pie chart
+        plt.pie(filtered_df["Population"], labels=filtered_df["Country"], autopct="%1.1f%%")
+    
+    plt.title("Population by Country")
+    plt.tight_layout()
+    return plt
+
+country_choices = df["Country"].tolist()
+
+with gr.Blocks() as demo:
+    gr.Markdown("## 🌍 World Population Chart")
+    with gr.Row():
+        country_select = gr.CheckboxGroup(label="Select Countries", choices=country_choices, value=["India", "China"])
+        chart_type = gr.Radio(label="Chart Type", choices=["Bar", "Pie"], value="Bar")
+    output = gr.Plot()
+
+    country_select.change(plot_chart, inputs=[country_select, chart_type], outputs=output)
+    chart_type.change(plot_chart, inputs=[country_select, chart_type], outputs=output)
+
+demo.launch()
+