Delete app.py

app.py

@@ -1,95 +0,0 @@
-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(openai_api_key)
-repo = huggingface_hub.Repository(
-    local_dir="data",
-    repo_type="dataset",
-    clone_from="Kilos1/my-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()