SidJain1412

import requests
url = "http://127.0.0.1:8000/campaign/?prompt=Pepsi"
response = requests.get(
    url,
    stream=True,
    headers={"accept": "application/json"},
)

for chunk in response.iter_content(chunk_size=1024):
    if chunk:

SidJain1412

from fastapi import FastAPI, Query
import openai
import os
import sys

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY", "")
if not len(OPENAI_API_KEY):
    print("Please set OPENAI_API_KEY environment variable. Exiting.")
    sys.exit(1)

SidJain1412

# Run using `uvicorn simple_app:app --reload`
# Visit 127.0.0.1:8000/docs for documentation and testing the API
from fastapi import FastAPI, Query

app = FastAPI(
    title="FastAPI Example",
    description="### Hello world",
    version=1.0,
)

SidJain1412

import random

# How many times each ad was clicked
ad_rewards = [0] * bandits
# How many times each ad was selected
ad_selection = [0] * bandits

# N: Number of users
N = df.shape[0]
# bandits: Number of ads

SidJain1412

def calculate_upper_bound(wins, num_selections, n):
    average_reward = wins / num_selections
    delta_i = math.sqrt(3/2 * math.log(n + 1) / num_selections)
    upper_bound = average_reward + delta_i
    return upper_bound


import math
import random

SidJain1412

from scipy.stats import beta
import random

ads_selected = []
# d = number of ads
number_of_wins = [0] * d
number_of_losses = [0] * d

total_reward = 0

SidJain1412

import numpy as np
def random_color():
    ltemp = np.random.randint(0, 255, 3)
    return "#%02x%02x%02x" % tuple(ltemp)

# col = random_color()
# print(col)
# '#eb4de9'