Extracting Data from YouTube Comments
🔑 ID:
52562
👨💻
Python
🕒
21/06/2024
Free
Description:
This code reads a list of comments from a CSV file and extracts data about them according to a prompt.
This code checks if the comments are testimonial-worthy or not.
To learn more about how the code works, read this.
Code:
import csv import time from SimplerLLM.language.llm import LLM, LLMProvider from SimplerLLM.tools.file_loader import read_csv_file def is_testimonial_worthy(comment): llm_instance = LLM.create(provider=LLMProvider.OPENAI, model_name="gpt-3.5-turbo") u_prompt = f"""You are an expert in comment analysis. Evaluate if this YouTube comment is worthy of being a testimonial on my website. Only consider positive testimonials. Return True or False. Comment: {comment} """ response = llm_instance.generate_response(prompt=u_prompt) return response start = time.time() file = read_csv_file("youtube_comments.csv") counter = 0 with open('my_data.csv', 'a', newline='', encoding='utf-8') as csvfile: writer = csv.writer(csvfile, delimiter=',', quotechar='"', quoting=csv.QUOTE_ALL) if csvfile.tell() == 0: writer.writerow(['Comment', 'User', 'Profile Picture', 'Video ID', 'Video Privacy', 'Time', 'Testimonial Worthy']) for row in file.content[1:]: testimonial = is_testimonial_worthy(row[0]) row[6] = testimonial writer.writerow([row[0], row[1], row[2], row[3], row[4], row[5], row[6]]) counter = counter + 1 print(counter) end = time.time() print(end-start)
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