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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():
with gr.Box():
gr.Markdown("Most recently created 10 rows: See full dataset [here](https://huggingface.co/datasets/freddyaboulton/gradio-reviews)")
data = gr.Dataframe()
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() |