112 lines
4.6 KiB
Python
112 lines
4.6 KiB
Python
import os
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import sys
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import json
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from pathlib import Path
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from loguru import logger
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logger.remove()
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logger.add(sys.stdout,
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colorize=True,
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format="<level>{level}</level>|<green>{file}:{line}:{function}</green>| {message}"
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)
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from ..gpt_providers.text_generation.main_text_generation import llm_text_gen
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def write_blog_google_serp(search_keyword, search_results):
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"""Combine the given online research and GPT blog content"""
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prompt = f"""
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As expert Creative Content writer,
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I want you to write highly detailed blog post, that explores {search_keyword} and also include 5 FAQs.
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I want the post to offer unique insights, relatable examples, and a fresh perspective on the topic.
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Here are some Google search results to spark your creativity on {search_keyword}:
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\n\n
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\"\"\"{search_results}\"\"\"
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"""
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logger.info("Generating blog and FAQs from Google web search results.")
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try:
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response = llm_text_gen(prompt)
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return response
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except Exception as err:
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logger.error(f"Exit: Failed to get response from LLM: {err}")
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exit(1)
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def improve_blog_intro(blog_content, blog_intro):
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"""Combine the given online research and gpt blog content"""
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prompt = f"""
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You are a skilled content editor, tasked with creating an engaging peek into the blog post provided.
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This peek should entice readers to delve into the full content.
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Here's what you need to do:
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1. **Replace the old blog introduction with the new one provided.**
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2. **Craft a short and captivating summary of the key points and interesting takeaways from the blog.**
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- Highlight what makes the blog unique and worth reading.
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- This peek should be placed directly before the new introduction.
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3. **Include the complete blog content, with the new introduction and the added peek.**
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Do not provide explanations for your actions, simply present the edited blog content.
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Blog Content: \"\"\"{blog_content}\"\"\"
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Blog Introduction: \"\"\"{blog_intro}\"\"\"
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"""
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logger.info("Generating blog introduction from tavily answer.")
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try:
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response = llm_text_gen(prompt)
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return response
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except Exception as err:
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logger.error(f"Exit: Failed to get response from LLM: {err}")
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exit(1)
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def blog_with_keywords(blog, keywords):
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"""Combine the given online research and gpt blog content"""
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prompt = f"""
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You are Sarah, the Creative Content writer, writing up fresh ideas and crafts them with care.
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She makes complex topics easy to understand and writes in a friendly tone that connects with everyone.
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She excels at simplifying complex topics and communicates with charisma, making technical jargon come alive for her audience.
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As an expert digital content writer, specializing in content optimization and SEO.
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I will provide you with my 'blog content' and 'list of keywords' on the same topic.
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Your task is to write an original blog, utilizing given keywords and blog content.
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Your blog should be highly detailed and well formatted.
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Blog content: '{blog}'
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list of keywords: '{keywords}'
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"""
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try:
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response = llm_text_gen(prompt)
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return response
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except Exception as err:
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logger.error(f"blog_with_keywords: Failed to get response from LLM: {err}")
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raise err
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def blog_with_research(report, blog):
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"""Combine the given online research and gpt blog content"""
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prompt = f"""
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As expert Creative Content writer, Your task is to update a blog post using the latest research.
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Here's what you need to do:
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1. **Read the outdated blog content and the new research report carefully.**
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2. **Identify key insights and updates from the research report that should be incorporated into the blog post.**
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3. **Rewrite sections of the blog post to reflect the new information, ensuring a smooth and natural flow.**
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4. **Maintain the blog's original friendly and conversational tone throughout.**
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Remember, your goal is to seamlessly blend the new information into the existing blog post, making it accurate and engaging for readers.
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\n\n
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Research Report: \"\"\"{report}\"\"\"
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Blog Content: \"\"\"{blog}\"\"\"
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"""
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try:
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response = llm_text_gen(prompt)
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return response
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except Exception as err:
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logger.error(f"blog_with_research: Failed to get response from LLM: {err}")
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raise err
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