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import requests
from bs4 import BeautifulSoup
import json
import os
from langchain.llms import OpenAI
from langchain.prompts import PromptTemplate
import gradio as gr
EVENTBRITE_API_KEY = os.environ['EVENTBRITE_API_KEY']
def get_event_id(url):
uid = url.split('?')[0]
uid = uid.split('/')[-1]
uid = uid.split('-')[-1]
return uid
def get_title_subtitle_from_event(event_url):
# Get the title and subtitle
res = requests.get(url=event_url)
soup = BeautifulSoup(res.content, 'html.parser')
tag_classes = {'title': 'event-title',
'subtitle': 'summary',
'details': 'has-user-generated-content'}
title = soup.find(class_ = tag_classes['title']).text
subtitle = soup.find(class_ = tag_classes['subtitle']).text
return title, subtitle
def get_event_details(event_url):
# Now get details:
event_id = get_event_id(event_url)
headers = {'Authorization': 'Bearer {}'.format(EVENTBRITE_API_KEY)}
params = {}
base_url = "https://www.eventbriteapi.com/v3/events/{id}/structured_content/"
r = requests.get(base_url.format(id=event_id), headers=headers, params=params)
effective_encoding = 'utf-8-sig' #r.apparent_encoding #
r.encoding = effective_encoding
res_tree = json.loads(r.text)
content = res_tree['modules'][0]['data']['body']['text']
content = content.replace('\ufeff', '') # Remove byte order mark for utf-8-sig decoding.
soup = BeautifulSoup(content, 'html.parser')
details = soup.get_text(separator=' ')
return details
def get_eventbrite_summary(event_url, top_level_prompt_stub):
title, subtitle = get_title_subtitle_from_event(event_url)
details = get_event_details(event_url)
temperature = 0.3
openai_modeltype = "text-davinci-003"
top_level_prompt = top_level_prompt_stub + """
Event Title:{title}
Event Subtitle: {subtitle}
Event Description:
{description}"""
prompt = PromptTemplate(
input_variables=['title', 'subtitle', 'description'],
template=top_level_prompt,
)
chat_prompt = prompt.format_prompt(title=title, subtitle=subtitle, description=details)
llm = OpenAI(model_name=openai_modeltype, temperature=temperature)
res = llm(chat_prompt.to_messages()[0].content)
return res.strip()
top_level_prompt_stub = """You are a journalist writing a calendar of events, and need to create succinct, fun, and energizing summaries of events in 1-2 sentences. You will be given a description of an event you need to summarize; please respond with your brief, fun, and engaging summary."""
prompt_textbox = gr.Textbox(value=top_level_prompt_stub)
url_textbox = gr.Textbox(value='https://www.eventbrite.com/e/greenermind-summit-2023-tickets-576308392917',
placeholder='full eventbrite url')
demo = gr.Interface(fn=get_eventbrite_summary,
inputs=[url_textbox, prompt_textbox],
outputs=['text']
)
demo.launch()
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