Create sample.csv

sample.csv

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+import pandas as pd
+import numpy as np
+from sklearn.preprocessing import LabelEncoder, StandardScaler
+from sklearn.model_selection import train_test_split
+from sklearn.linear_model import LogisticRegression, LinearRegression
+from sklearn.metrics import accuracy_score, classification_report, confusion_matrix
+import gradio as gr
+
+def auto_eda(file):
+    # Load dataset
+    df = pd.read_csv(file.name)
+    output = []
+
+    # Show head, shape, and dtypes
+    output.append("📌 **First 5 Rows:**")
+    output.append(df.head().to_markdown())
+
+    output.append(f"\n📊 **Shape of Dataset:** {df.shape}")
+    output.append("\n🧾 **Data Types:**")
+    output.append(df.dtypes.to_markdown())
+
+    return "\n\n".join(output)
+
+# Gradio UI
+demo = gr.Interface(
+    fn=auto_eda,
+    inputs=gr.File(label="Upload CSV File"),
+    outputs=gr.Markdown(label="Dataset Info"),
+    title="📈 AutoEDA Agent - Step 1",
+    description="Upload your dataset to begin automatic EDA."
+)
+
+demo.launch()