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app.py

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+import gradio as gr
+import pandas as pd
+
+movies = pd.read_csv('100_niche_movies.csv')
+
+def recommend(query):
+    query = query.lower()
+    if "sci-fi" in query: genre = "Sci-Fi"
+    elif "horror" in query: genre = "Horror" 
+    elif "comedy" in query: genre = "Comedy"
+    else: return movies.sample(3)
+    
+    return movies[movies['genres'].str.contains(genre)].sample(3)
+
+with gr.Blocks() as demo:
+    gr.Markdown("# 🎬 Your Personal Movie Assistant")
+    query = gr.Textbox(label="What kind of movies?")
+    output = gr.JSON(label="Recommendations")
+    query.submit(
+        fn=lambda q: recommend(q).to_dict('records'),
+        inputs=query,
+        outputs=output
+    )
+
+if __name__ == "__main__":
+    demo.launch()