rbughao commited on
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091a415
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1 Parent(s): 28ce00e

Update app.py

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  1. app.py +54 -54
app.py CHANGED
@@ -1,64 +1,64 @@
1
  import gradio as gr
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- from huggingface_hub import InferenceClient
 
 
 
3
 
 
 
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  """
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- For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
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- """
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- client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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-
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-
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- def respond(
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- message,
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- history: list[tuple[str, str]],
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- system_message,
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- max_tokens,
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- temperature,
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- top_p,
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- ):
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- messages = [{"role": "system", "content": system_message}]
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-
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- for val in history:
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- if val[0]:
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- messages.append({"role": "user", "content": val[0]})
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- if val[1]:
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- messages.append({"role": "assistant", "content": val[1]})
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- messages.append({"role": "user", "content": message})
 
 
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- response = ""
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- for message in client.chat_completion(
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- messages,
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- max_tokens=max_tokens,
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- stream=True,
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- temperature=temperature,
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- top_p=top_p,
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- ):
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- token = message.choices[0].delta.content
 
 
 
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- response += token
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- yield response
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-
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-
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- """
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- For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
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- """
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- demo = gr.ChatInterface(
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- respond,
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- additional_inputs=[
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- gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
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- gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
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- gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
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- gr.Slider(
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- minimum=0.1,
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- maximum=1.0,
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- value=0.95,
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- step=0.05,
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- label="Top-p (nucleus sampling)",
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- ),
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- ],
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- )
61
 
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  if __name__ == "__main__":
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- demo.launch()
 
1
  import gradio as gr
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+ import requests
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+ import time
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+ import pandas as pd
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+ from datetime import datetime
6
 
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+ DEFAULT_SYSTEM_PROMPT = """
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+ This is Banyan Group's Ads Checker, the tool guides you to the different possible paid ads a brand is sponsoring.
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  """
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ results = []
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+ results.append(['Website','Speed in Seconds'])
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+ vLogDate = datetime.today().strftime('%Y/%m/%d')
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+ websites = [
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+ "https://www.banyantree.com",
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+ "https://www.angsana.com",
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+ "https://www.cassia.com",
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+ "https://www.dhawa.com",
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+ "https://www.garrya.com",
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+ "https://www.hommhotels.com",
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+ "https://www.foliohotels.com",
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+ "https://www.raffles.com",
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+ "https://www.aman.com",
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+ "https://www.rosewoodhotels.com",
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+ "https://www.fourseasons.com",
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+ "https://www.radissonhotels.com",
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+ "https://www.millenniumhotels.com",
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+ "https://www.mandarinoriental.com",
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+ "https://www.ritzcarlton.com",
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+ "https://www.hyatt.com",
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+ "https://www.ihg.com"
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+ ]
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+ def check_site_speed(url):
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+ try:
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+ headers = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"}
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+ start_time = time.time()
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+ response = requests.get(url, headers=headers, timeout=10)
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+ response.raise_for_status()
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+ end_time = time.time()
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+ return round(end_time - start_time, 5) # Response time in seconds
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+ except requests.exceptions.RequestException as e:
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+ print(f"Error checking {url}: {e}")
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+ return None
46
 
47
+ def runchecks(message,history):
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+ for site in websites:
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+ print(f"Checking site speed for {site}...")
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+ speed = check_site_speed(site)
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+ time.sleep(11)
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+ if speed is not None:
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+ print(f"Response time for {site}: {speed} seconds")
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+ results.append([site,speed])
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+ df_log = pd.DataFrame(results)
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+ return df_log
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+
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+ Conversing = gr.ChatInterface(runchecks, chatbot=gr.Chatbot(height=600,label = "Enter Domain to evaluate (no 'https://www')"), theme=gr.themes.Monochrome(),
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+ title = 'BT ECommerce AdsChecker Tool', description = DEFAULT_SYSTEM_PROMPT, css='footer {visibility: hidden}').launch()
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+ #"Algorithm for this site is based on Readability Wiki - https://en.wikipedia.org/wiki/Readability "
 
 
 
 
 
 
 
 
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62
 
63
  if __name__ == "__main__":
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+ Conversing.launch()