Create app.py

app.py

@@ -0,0 +1,95 @@
+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()