import sqlite3 import huggingface_hub import gradio as gr import pandas as pd import shutil import os import datetime from apscheduler.schedulers.background import BackgroundScheduler DB_FILE = "./reviews.db" TOKEN = os.environ.get('HUB_TOKEN') repo = huggingface_hub.Repository( local_dir="data", repo_type="dataset", clone_from="freddyaboulton/gradio-reviews", use_auth_token=TOKEN ) repo.git_pull() # Set db to latest shutil.copyfile("./data/reviews.db", DB_FILE) # Create table if it doesn't already exist db = sqlite3.connect(DB_FILE) try: db.execute("SELECT * FROM reviews").fetchall() db.close() except sqlite3.OperationalError: db.execute( ''' CREATE TABLE reviews (id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL, created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP NOT NULL, name TEXT, review INTEGER, comments TEXT) ''') db.commit() db.close() def get_latest_reviews(db: sqlite3.Connection): reviews = db.execute("SELECT * FROM reviews ORDER BY id DESC limit 10").fetchall() total_reviews = db.execute("Select COUNT(id) from reviews").fetchone()[0] reviews = pd.DataFrame(reviews, columns=["id", "date_created", "name", "review", "comments"]) return reviews, total_reviews def add_review(name: str, review: int, comments: str): db = sqlite3.connect(DB_FILE) cursor = db.cursor() cursor.execute("INSERT INTO reviews(name, review, comments) VALUES(?,?,?)", [name, review, comments]) db.commit() reviews, total_reviews = get_latest_reviews(db) db.close() return reviews, total_reviews def load_data(): db = sqlite3.connect(DB_FILE) reviews, total_reviews = get_latest_reviews(db) db.close() return reviews, total_reviews with gr.Blocks() as demo: with gr.Row(): with gr.Column(): name = gr.Textbox(label="Name", placeholder="What is your name?") review = gr.Radio(label="How satisfied are you with using gradio?", choices=[1, 2, 3, 4, 5]) comments = gr.Textbox(label="Comments", lines=10, placeholder="Do you have any feedback on gradio?") submit = gr.Button(value="Submit Feedback") with gr.Column(): data = gr.Dataframe(label="Most recently created 10 rows") count = gr.Number(label="Total number of reviews") submit.click(add_review, [name, review, comments], [data, count]) demo.load(load_data, None, [data, count]) def backup_db(): shutil.copyfile(DB_FILE, "./data/reviews.db") db = sqlite3.connect(DB_FILE) reviews = db.execute("SELECT * FROM reviews").fetchall() pd.DataFrame(reviews).to_csv("./data/reviews.csv", index=False) print("updating db") repo.push_to_hub(blocking=False, commit_message=f"Updating data at {datetime.datetime.now()}") scheduler = BackgroundScheduler() scheduler.add_job(func=backup_db, trigger="interval", seconds=60) scheduler.start() demo.launch()