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import gradio as gr
import os
from pytrends.request import TrendReq
from openai import OpenAI
pytrends = TrendReq(
hl="en-US",
tz=360,
timeout=(10, 25),
proxies=[
"https://34.203.233.13:80",
],
retries=2,
backoff_factor=0.1,
requests_args={"verify": False},
)
kw_list = [""]
client = OpenAI(
# This is the default and can be omitted
api_key=os.getenv("openaikey"),
)
def fetch_clothing_themes_and_generate_banner_2(geo, start_date, end_date):
# Initialize pytrends and OpenAI client
pytrends = TrendReq(hl="en-US", tz=360)
# openai.api_key = "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"
# Define the keywords list for clothing related searches
kw_list = [""]
# Build payload for given geo and date range
timeframe = f"{start_date} {end_date}"
pytrends.build_payload(kw_list, timeframe=timeframe, geo=geo)
# Fetch related queries
all_top_queries = pytrends.related_queries()
# Extract top and rising queries
top_queries = all_top_queries[""]["top"]
rising_queries = all_top_queries[""]["rising"]
# Format the queries for the ChatGPT prompt
formatted_queries = ", ".join(
top_queries["query"].tolist() + rising_queries["query"].tolist()
)
# Create a prompt for ChatGPT
# prompt = f"From the following top and rising keywords in {geo} from {start_date} to {end_date}: {formatted_queries}, suggest the most fun and entertaining theme related to clothing. Select a topic based on one of the keywords. Just specify the theme with one sentence description of its fashion style. Make the description suitable for a metaverse avatar"
prompt = f"Out of all the follwing keywords, which one is the most fun for a clothing themed topic? {formatted_queries}. Ignore commonly used words or apps like 'weather', 'tiktok' or 'instagram'. Focus on events that could be popular. Reply with a small phrase"
print(prompt)
# Pass the prompt to ChatGPT API
chat_completion = client.chat.completions.create(
model="gpt-4-1106-preview",
messages=[
# {"role": "system", "content": "You are a fashion expert."},
{"role": "user", "content": prompt},
],
)
# Extract the theme suggestion
theme_suggestion = chat_completion.choices[0].message.content
return theme_suggestion, all_top_queries
def greet(city, start_date_yyyy_mm_dd, end_date_yyyy_mm_dd):
chat_completion = client.chat.completions.create(
messages=[
{
"role": "user",
"content": f"ISO 3166-2 code for {city}. Only reply with one word. Reply GLOBAL if invalid",
}
],
model="gpt-3.5-turbo-1106",
)
geo = chat_completion.choices[0].message.content.strip()
timeframe = f"{start_date_yyyy_mm_dd} {end_date_yyyy_mm_dd}"
pytrends.build_payload(kw_list, timeframe=timeframe, geo=geo)
all_top_queries = pytrends.related_queries()
top_queries = all_top_queries[""]["top"]
rising_queries = all_top_queries[""]["rising"]
return top_queries, rising_queries
demo = gr.Interface(
fn=greet,
inputs=["text", "text", "text"],
outputs=["dataframe", "dataframe"],
)
if __name__ == "__main__":
demo.launch()
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