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import gradio as gr |
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import pandas as pd |
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from sklearn.feature_extraction.text import TfidfVectorizer |
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from sklearn.metrics.pairwise import cosine_similarity |
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data = { |
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'event_id': [101, 102, 103, 104, 105], |
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'title': ['Hiking Meetup', 'Book Club Discussion', 'Gardening Workshop', 'Coding Class', 'Yoga Session'], |
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'description': ['Explore local trails', 'Discuss "The Great Gatsby"', 'Learn basic gardening', 'Python programming basics', 'Relaxing yoga practice'], |
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'tags': ['hiking, nature, outdoors', 'books, literature, reading', 'gardening, plants, nature', 'coding, programming, python', 'yoga, fitness, relaxation'] |
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} |
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events_df = pd.DataFrame(data) |
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def recommend_activities(interests, num_recommendations=3): |
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if not interests: |
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return "Please enter your interests." |
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user_interests = interests.lower() |
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tfidf = TfidfVectorizer() |
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tfidf_matrix_events = tfidf.fit_transform(events_df['tags']) |
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tfidf_matrix_user = tfidf.transform([user_interests]) |
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similarities = cosine_similarity(tfidf_matrix_user, tfidf_matrix_events) |
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top_indices = similarities.argsort()[0][-num_recommendations:][::-1] |
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recommendations = events_df.iloc[top_indices][['title', 'description']].values.tolist() |
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return recommendations |
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def create_event(title, description, location, date_time, tags): |
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print(f"Event created: {title}, {description}, {location}, {date_time}, {tags}") |
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return "Event created successfully!" |
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with gr.Blocks() as demo: |
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gr.Markdown("# AI Community Builder") |
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with gr.Row(): |
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with gr.Column(): |
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interests_input = gr.Textbox(label="Your Interests (comma-separated)", lines=2, placeholder="e.g., hiking, reading, cooking") |
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num_recs_input = gr.Slider(label="Number of Recommendations", minimum=1, maximum=5, value=3, step=1) |
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recommend_button = gr.Button("Get Recommendations") |
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with gr.Column(): |
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recommendations_output = gr.Dataframe(headers=["Title", "Description"], datatype=["str", "str"], interactive=True) |
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recommend_button.click(fn=recommend_activities, inputs=[interests_input, num_recs_input], outputs=recommendations_output) |
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with gr.Accordion("Create a New Event", open=False): |
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with gr.Row(): |
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title_input = gr.Textbox(label="Event Title", placeholder="Enter event title") |
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description_input = gr.Textbox(label="Description", lines=3, placeholder="Enter a brief description") |
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with gr.Row(): |
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location_input = gr.Textbox(label="Location", placeholder="Enter location details") |
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datetime_input = gr.Textbox(label="Date & Time (YYYY-MM-DD HH:MM)", placeholder="Enter date and time") |
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tags_input = gr.Textbox(label="Tags (comma-separated)", placeholder="Enter relevant tags") |
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create_event_button = gr.Button("Create Event") |
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create_event_button.click(fn=create_event, inputs=[title_input, description_input, location_input, datetime_input, tags_input], outputs=gr.Textbox(label="Result")) |
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demo.launch() |
