import gradio as gr from bs4 import BeautifulSoup import requests from acogsphere import acf from bcogsphere import bcf import math import sqlite3 import huggingface_hub import pandas as pd import shutil import os import datetime from apscheduler.schedulers.background import BackgroundScheduler import random import time import requests DB_FILE = "./reviews1.db" TOKEN = os.environ.get('HF_KEY') repo = huggingface_hub.Repository( local_dir="data", repo_type="space", clone_from="CogSphere/aCogSphere", use_auth_token=TOKEN ) repo.git_pull() # Set db to latest #shutil.copyfile("./data/reviews0.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, rate INTEGER, celsci TEXT) ''') db.commit() db.close() def get_latest_reviews(db: sqlite3.Connection): reviews = db.execute("SELECT * FROM reviews ORDER BY id DESC limit 100").fetchall() total_reviews = db.execute("Select COUNT(id) from reviews").fetchone()[0] reviews = pd.DataFrame(reviews, columns=["id", "date_created", "name", "rate", "celsci"]) return reviews, total_reviews def ccogsphere(name: str, rate: int, celsci: str): db = sqlite3.connect(DB_FILE) cursor = db.cursor() cursor.execute("INSERT INTO reviews(name, rate, celsci) VALUES(?,?,?)", [name, rate, celsci]) db.commit() reviews, total_reviews = get_latest_reviews(db) db.close() #demo.load() return reviews, total_reviews def run_actr(): from python_actr import log_everything #code1="tim = MyAgent()" #code2="subway=MyEnv()" #code3="subway.agent=tim" #code4="log_everything(subway)"] from dcogsphere import RockPaperScissors from dcogsphere import ProceduralPlayer #from dcogsphere import logy env=RockPaperScissors() env.model1=ProceduralPlayer() env.model1.choice=env.choice1 env.model2=ProceduralPlayer() env.model2.choice=env.choice2 env.run() #print (response) #resu=logy() #return resu def load_data(): db = sqlite3.connect(DB_FILE) reviews, total_reviews = get_latest_reviews(db) db.close() return reviews, total_reviews css="footer {visibility: hidden}" with gr.Blocks() as demo: with gr.Row(): with gr.Column(): #with gr.Box(): #gr.Markdown("Based on dataset [here](https://huggingface.co/datasets/freddyaboulton/gradio-reviews)") data = gr.Dataframe() count = gr.Number(label="Rates!") with gr.Row(): with gr.Column(): name = gr.Textbox(label="a") #, placeholder="What is your name?") rate = gr.Textbox(label="b") #, placeholder="What is your name?") #gr.Radio(label="How satisfied are you with using gradio?", choices=[1, 2, 3, 4, 5]) celsci = gr.Textbox(label="c") #, lines=10, placeholder="Do you have any feedback on gradio?") submit = gr.Button(value=".") submit.click(ccogsphere, [name, rate, celsci], [data, count]) demo.load(load_data, None, [data, count]) @name.change(inputs=name, outputs=celsci,_js="window.location.reload()") @rate.change(inputs=rate, outputs=name,_js="window.location.reload()") @celsci.change(inputs=celsci, outputs=rate,_js="window.location.reload()") def secwork(name): #if name=="abc": #run_code() load_data() #return "Hello " + name + "!" with gr.Row(): with gr.Column(): run_actr() def backup_db(): shutil.copyfile(DB_FILE, "./reviews.2db") db = sqlite3.connect(DB_FILE) reviews = db.execute("SELECT * FROM reviews").fetchall() pd.DataFrame(reviews).to_csv("./reviews1.csv", index=False) print("updating db") repo.push_to_hub(blocking=False, commit_message=f"Updating data at {datetime.datetime.now()}") def load_data2(): db = sqlite3.connect(DB_FILE) reviews, total_reviews = get_latest_reviews(db) #db.close() return reviews, total_reviews scheduler = BackgroundScheduler() scheduler.add_job(func=backup_db, trigger="interval", seconds=240) scheduler.start() #scheduler2 = BackgroundScheduler() #scheduler2.add_job(func=load_data2, trigger="interval", seconds=10) #scheduler2.start() demo.launch()