Create app.py

app.py

@@ -0,0 +1,71 @@
+import gradio as gr
+import pandas as pd
+import seaborn as sns
+import matplotlib.pyplot as plt
+from transformers import pipeline
+import tempfile
+import os
+
+def load_and_clean_data():
+    url = "https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv"
+    df = pd.read_csv(url)
+    df['Age'].fillna(df['Age'].median(), inplace=True)
+    df['Embarked'].fillna(df['Embarked'].mode()[0], inplace=True)
+    df.drop(columns=['Cabin', 'Ticket', 'Name'], inplace=True)
+    return df
+
+def generate_plot_images(df):
+    temp_files = []
+    for plot_func in [plot_survival_count, plot_survival_by_gender]:
+        fig, ax = plt.subplots()
+        plot_func(df, ax)
+        tmp = tempfile.NamedTemporaryFile(suffix=".png", delete=False)
+        fig.savefig(tmp.name)
+        temp_files.append(tmp.name)
+        plt.close(fig)
+    return temp_files
+
+def plot_survival_count(df, ax):
+    sns.countplot(x='Survived', data=df, ax=ax)
+
+def plot_survival_by_gender(df, ax):
+    sns.countplot(x='Sex', hue='Survived', data=df, ax=ax)
+
+summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
+
+def summarize_eda(df):
+    try:
+        text = f"""
+        Titanic dataset has {len(df)} rows. Missing values in Age and Embarked were filled.
+        Columns Cabin, Ticket, and Name were dropped. Females had higher survival rates.
+        Most passengers embarked from {df['Embarked'].mode()[0]}.
+        """
+        summary = summarizer(text, max_length=100, min_length=30, do_sample=False)[0]['summary_text']
+        return summary
+    except Exception as e:
+        return f"Summarization failed: {str(e)}"
+
+def run_titanic_eda():
+    try:
+        df = load_and_clean_data()
+        plots = generate_plot_images(df)
+        summary = summarize_eda(df)
+        return df.head().to_markdown(), plots[0], plots[1], summary
+    except Exception as e:
+        return "Data load failed", None, None, f"Error: {str(e)}"
+
+demo = gr.Interface(
+    fn=run_titanic_eda,
+    inputs=[],
+    outputs=[
+        gr.Markdown(label="Cleaned Data Sample"),
+        gr.Image(label="Survival Count"),
+        gr.Image(label="Survival by Gender"),
+        gr.Textbox(label="LLM Summary of EDA")
+    ],
+    title="🚢 Titanic EDA + LLM Summary",
+    description="Cleaned dataset, EDA plots, and LLM-generated summary — all in one page."
+)
+
+if __name__ == "__main__":
+    demo.launch()