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	`1`	`+import requests`
	`2`	`+`
	`3`	`+api_key = '78c68b12139482d7e0784209bd15f555'`
	`4`	`+`
	`5`	`+user_input = input("Enter city: ")`
	`6`	`+`
	`7`	`+weather_data = requests.get(`
	`8`	`+ f"https://api.openweathermap.org/data/2.5/weather?q={user_input}&units=imperial&APPID={api_key}")`
	`9`	`+`
	`10`	`+if weather_data.json()['cod'] == '404':`
	`11`	`+ print("No City Found")`
	`12`	`+else:`
	`13`	`+ weather = weather_data.json()['weather'][0]['main']`
	`14`	`+ temp = round(weather_data.json()['main']['temp'])`
	`15`	`+`
	`16`	`+ print(f"The weather in {user_input} is: {weather}")`
	`17`	`+ print(f"The temperature in {user_input} is: {temp}oF")`

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	`1`	`+import requests`
	`2`	`+from bs4 import BeautifulSoup`
	`3`	`+`
	`4`	`+# Get the HTML text`
	`5`	`+url = "https://quotes.toscrape.com/"`
	`6`	`+response = requests.get(url)`
	`7`	`+text = response.text`
	`8`	`+`
	`9`	`+# Parse the text with Beautiful Soup`
	`10`	`+soup = BeautifulSoup(text, "lxml")`
	`11`	`+`
	`12`	`+# Extract authors`
	`13`	`+authors = soup.find_all("small", class_="author")`
	`14`	`+author_set = set(author.text.strip() for author in authors)`
	`15`	`+`
	`16`	`+# Extract quotes`
	`17`	`+quotes = soup.find_all("span", class_="text")`
	`18`	`+quote_list = [quote.text.strip() for quote in quotes]`
	`19`	`+`
	`20`	`+# Extract top ten tags`
	`21`	`+top_tags = soup.find("div", class_="tags-box")`
	`22`	`+tags = top_tags.find_all("a")`
	`23`	`+tag_list = [tag.text.strip() for tag in tags]`
	`24`	`+`
	`25`	`+# Loop through all pages to get unique authors (if applicable)`
	`26`	`+def get_page_authors(page_url):`
	`27`	`+ # Your implementation here`
	`28`	`+ pass`

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	`1`	`+import nltk`
	`2`	`+from nltk.tokenize import word_tokenize`
	`3`	`+`
	`4`	`+# Download NLTK data`
	`5`	`+nltk.download('punkt')`
	`6`	`+`
	`7`	`+# Define chatbot responses`
	`8`	`+responses = {`
	`9`	`+ "hi": "Hello! How can I assist you?",`
	`10`	`+ "how are you": "I'm just a program, so I don't have feelings, but I'm here to help!",`
	`11`	`+ # Add more predefined responses here`
	`12`	`+}`
	`13`	`+`
	`14`	`+def preprocess_input(user_input):`
	`15`	`+ tokens = word_tokenize(user_input.lower())`
	`16`	`+ # Additional preprocessing steps if needed`
	`17`	`+ return tokens`
	`18`	`+`
	`19`	`+def chatbot_response(user_input):`
	`20`	`+ tokens = preprocess_input(user_input)`
	`21`	`+ for query, response in responses.items():`
	`22`	`+ if any(token in query for token in tokens):`
	`23`	`+ return response`
	`24`	`+ return "I didn't understand. Can you please rephrase?"`
	`25`	`+`
	`26`	`+if __name__ == "__main__":`
	`27`	`+ while True:`
	`28`	`+ user_query = input("You: ")`
	`29`	`+ if user_query.lower() == "exit":`
	`30`	`+ print("Chatbot: Goodbye!")`
	`31`	`+ break`
	`32`	`+ print("Chatbot:", chatbot_response(user_query))`

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	`1`	`+from PyPDF2 import PdfFileReader, PdfFileWriter`
	`2`	`+`
	`3`	`+def split_pdf(input_pdf, output_folder):`
	`4`	`+ pdf_reader = PdfFileReader(input_pdf)`
	`5`	`+ total_pages = pdf_reader.numPages`
	`6`	`+`
	`7`	`+ for page_num in range(total_pages):`
	`8`	`+ pdf_writer = PdfFileWriter()`
	`9`	`+ pdf_writer.addPage(pdf_reader.getPage(page_num))`
	`10`	`+`
	`11`	`+ output_file = f"{output_folder}/page_{page_num + 1}.pdf"`
	`12`	`+ with open(output_file, "wb") as output_pdf:`
	`13`	`+ pdf_writer.write(output_pdf)`
	`14`	`+`
	`15`	`+ print(f"Page {page_num + 1} saved as {output_file}")`
	`16`	`+`
	`17`	`+`

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