Streamlit UI, Porting CLI - WIP
This commit is contained in:
ajaysi
@@ -13,6 +13,7 @@ import yaml
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from pathlib import Path
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from dotenv import load_dotenv
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from configparser import ConfigParser
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import streamlit as st
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from google.api_core import retry
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import google.generativeai as genai
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@@ -57,190 +58,195 @@ def long_form_generator(content_keywords):
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Write long form content using prompt chaining and iterative generation.
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Parameters:
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"""
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# Read the main_config to define tone, character, personality of the content to be generated.
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try:
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logger.info(f"Starting to write content on {content_keywords}.")
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# Define persona and writing guidelines
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content_tone, target_audience, content_type, content_language, output_format = read_return_config_section('blog_characteristics')
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except Exception as err:
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logger.error(f"Failed to Read config params from main_config: {err}")
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return
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try:
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filepath = os.path.join(os.environ["PROMPTS_DIR"], "long_form_ai_writer.prompts")
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# Check if file exists
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if not os.path.exists(filepath):
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raise FileNotFoundError(f"File {filepath} does not exist")
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with open(filepath, 'r') as file:
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prompts = yaml.safe_load(file)
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except Exception as err:
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logger.error(f"Exit: Failed to read prompts from {filepath}: {err}")
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exit(1)
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writing_guidelines = prompts.get('writing_guidelines').format(
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content_language=content_language,
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content_tone=content_tone,
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content_type=content_type,
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output_format=output_format,
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content_keywords=content_keywords,
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target_audience=target_audience
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)
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content_title = prompts.get('content_title').format(
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content_language=content_language,
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content_keywords=content_keywords,
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target_audience=target_audience
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)
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with st.status("Start Writing Long Form Article, Hold my Beer..", expanded=True) as status:
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# Read the main_config to define tone, character, personality of the content to be generated.
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try:
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logger.info(f"Starting to write content on {content_keywords}.")
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# Define persona and writing guidelines
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content_tone, target_audience, content_type, content_language, output_format = read_return_config_section('blog_characteristics')
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except Exception as err:
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logger.error(f"Failed to Read config params from main_config: {err}")
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return
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content_outline = prompts.get('content_outline').format(
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content_language=content_language,
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content_title='{content_title}',
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content_type=content_type,
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target_audience=target_audience
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)
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starting_prompt = prompts.get('starting_prompt').format(
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content_language=content_language,
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content_title='{content_title}',
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content_outline='{content_outline}',
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writing_guidelines=writing_guidelines
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)
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continuation_prompt = prompts.get('continuation_prompt').format(
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content_language=content_language,
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content_title='{content_title}',
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content_outline='{content_outline}',
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content_text='{content_text}',
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web_research_result='{web_research_result}',
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writing_guidelines=writing_guidelines
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)
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# Configure generative AI
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load_dotenv(Path('../.env'))
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generation_config = {
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"temperature": 0.8,
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"top_p": 0.95,
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"max_output_tokens": 8192,
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}
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genai.configure(api_key=os.getenv('GEMINI_API_KEY'))
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# Initialize the generative model
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model = genai.GenerativeModel('gemini-pro', generation_config=generation_config)
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model_pro = genai.GenerativeModel('gemini-1.5-flash-latest', generation_config=generation_config)
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# Do SERP web research for given keywords to generate title and outline.
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web_research_result, g_titles = do_google_serp_search(content_keywords)
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# Generate prompts
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try:
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content_title = generate_with_retry(model_pro, content_title.format(web_research_result=web_research_result)).text
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logger.info(f"The title of the content is: {content_title}")
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except Exception as err:
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logger.error(f"Content title Generation Error: {err}")
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return
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try:
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content_outline = generate_with_retry(model_pro, content_outline.format(
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content_title=content_title,
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web_research_result=web_research_result)).text
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logger.info(f"The content Outline is: {content_outline}\n\n")
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except Exception as err:
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logger.error(f"Failed to generate content outline: {err}")
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try:
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logger.info("Do web research with Tavily to provide context for content creation.")
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# Do Metaphor/Exa AI search.
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table_data = []
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web_research_result, m_titles, t_titles = do_tavily_ai_search(content_keywords, max_results=5)
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for item in web_research_result.get("results"):
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title = item.get("title", "")
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snippet = item.get("content", "")
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table_data.append([title, snippet])
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web_research_result = table_data
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except Exception as err:
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logger.error(f"Failed to do Tavily AI search: {err}")
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return
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try:
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starting_draft = generate_with_retry(model_pro, starting_prompt.format(
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content_title=content_title,
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content_outline=content_outline,
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web_research_result=web_research_result,
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writing_guidelines=writing_guidelines)).text
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except Exception as err:
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logger.error(f"Failed to Generate Starting draft: {err}")
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return
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try:
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logger.info(f"Starting to write on the outline introduction.")
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draft = starting_draft
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continuation = generate_with_retry(model, continuation_prompt.format(
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content_title=content_title,
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content_outline=content_outline,
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content_text=draft,
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web_research_result=web_research_result,
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writing_guidelines=writing_guidelines)).text
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except Exception as err:
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logger.error(f"Failed to write the initial draft: {err}")
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# Add the continuation to the initial draft, keep building the story until we see 'IAMDONE'
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try:
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draft += '\n\n' + continuation
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except Exception as err:
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logger.error(f"Failed as: {err} and {continuation}")
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logger.info(f"Writing in progress... Current draft length: {len(draft)} characters")
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search_terms = f"""
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I will provide you with blog outline, your task is to read the outline & return 3 google search keywords.
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Your response will be used to do web research for writing on the given outline.
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Do not explain your response, provide 3 google search sentences encompassing the given content outline.
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Content Outline:\n\n
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{content_outline}
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"""
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search_words = generate_with_retry(model_pro, search_terms).text
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while 'IAMDONE' not in continuation:
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try:
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#web_research_result, m_titles = do_metaphor_ai_research(content_keywords)
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str_list = re.split(r',\s*', search_words)
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# Strip quotes from each element
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str_list = [s.strip('\'"') for s in str_list]
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for search_term in str_list:
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web_research_result, m_titles, t_titles = do_tavily_ai_search(search_term, max_results=5)
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filepath = os.path.join(os.environ["PROMPTS_DIR"], "long_form_ai_writer.prompts")
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# Check if file exists
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if not os.path.exists(filepath):
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raise FileNotFoundError(f"File {filepath} does not exist")
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with open(filepath, 'r') as file:
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prompts = yaml.safe_load(file)
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except Exception as err:
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logger.error(f"Exit: Failed to read prompts from {filepath}: {err}")
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exit(1)
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writing_guidelines = prompts.get('writing_guidelines').format(
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content_language=content_language,
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content_tone=content_tone,
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content_type=content_type,
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output_format=output_format,
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content_keywords=content_keywords,
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target_audience=target_audience
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)
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content_title = prompts.get('content_title').format(
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content_language=content_language,
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content_keywords=content_keywords,
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target_audience=target_audience
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)
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content_outline = prompts.get('content_outline').format(
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content_language=content_language,
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content_title='{content_title}',
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content_type=content_type,
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target_audience=target_audience
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)
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starting_prompt = prompts.get('starting_prompt').format(
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content_language=content_language,
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content_title='{content_title}',
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content_outline='{content_outline}',
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writing_guidelines=writing_guidelines
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)
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continuation_prompt = prompts.get('continuation_prompt').format(
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content_language=content_language,
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content_title='{content_title}',
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content_outline='{content_outline}',
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content_text='{content_text}',
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web_research_result='{web_research_result}',
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writing_guidelines=writing_guidelines
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)
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# Configure generative AI
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load_dotenv(Path('../.env'))
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generation_config = {
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"temperature": 0.6,
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"top_p": 1,
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"max_output_tokens": 4096,
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}
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genai.configure(api_key=os.getenv('GEMINI_API_KEY'))
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# Initialize the generative model
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model = genai.GenerativeModel('gemini-pro', generation_config=generation_config)
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model_pro = genai.GenerativeModel('gemini-1.5-flash-latest', generation_config=generation_config)
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# Do SERP web research for given keywords to generate title and outline.
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web_research_result, g_titles = do_google_serp_search(content_keywords)
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# Generate prompts
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try:
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content_title = generate_with_retry(model_pro, content_title.format(web_research_result=web_research_result)).text
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logger.info(f"The title of the content is: {content_title}")
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status.update(label=f"The title of the content is: {content_title}")
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except Exception as err:
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logger.error(f"Content title Generation Error: {err}")
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return
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try:
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content_outline = generate_with_retry(model_pro, content_outline.format(
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content_title=content_title,
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web_research_result=web_research_result)).text
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logger.info(f"The content Outline is: {content_outline}\n\n")
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status.update(label="Generated the content outline.")
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except Exception as err:
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logger.error(f"Failed to generate content outline: {err}")
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try:
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logger.info("Do web research with Tavily to provide context for content creation.")
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# Do Metaphor/Exa AI search.
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table_data = []
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web_research_result, m_titles, t_titles = do_tavily_ai_search(content_keywords, max_results=5)
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for item in web_research_result.get("results"):
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title = item.get("title", "")
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snippet = item.get("content", "")
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table_data.append([title, snippet])
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web_research_result = table_data
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except Exception as err:
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logger.error(f"Failed to do Tavily AI search: {err}")
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return
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try:
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starting_draft = generate_with_retry(model_pro, starting_prompt.format(
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content_title=content_title,
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content_outline=content_outline,
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web_research_result=web_research_result,
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writing_guidelines=writing_guidelines)).text
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except Exception as err:
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logger.error(f"Failed to Generate Starting draft: {err}")
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return
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try:
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logger.info(f"Starting to write on the outline introduction.")
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draft = starting_draft
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continuation = generate_with_retry(model, continuation_prompt.format(
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content_title=content_title,
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content_title=content_title,
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content_outline=content_outline,
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content_text=draft,
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web_research_result=web_research_result,
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writing_guidelines=writing_guidelines)).text
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draft += '\n\n' + continuation
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logger.info(f"Writing in progress... Current draft length: {len(draft)} characters")
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# At this point, the context is little stale. We should more web research on
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# related queries as per the content outline, to augment the LLM context.
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except Exception as err:
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logger.error(f"Failed to continually write the Essay: {err}")
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return
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logger.error(f"Failed to write the initial draft: {err}")
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# Remove 'IAMDONE' and print the final story
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final = draft.replace('IAMDONE', '').strip()
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blog_title, blog_meta_desc, blog_tags, blog_categories = blog_metadata(final,
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content_keywords, m_titles)
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generated_image_filepath = None
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# TBD: Save the blog content as a .md file. Markdown or HTML ?
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save_blog_to_file(final, blog_title, blog_meta_desc, blog_tags, blog_categories, generated_image_filepath)
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blog_frontmatter = f"""
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---
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title: {blog_title}
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categories: [{blog_categories}]
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tags: [{blog_tags}]
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Meta description: {blog_meta_desc.replace(":", "-")}
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---"""
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logger.info(f"\n{blog_frontmatter}{final}\n\n")
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logger.info(f"\n\n ################ Finished writing Blog for : {content_keywords} #################### \n")
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# Add the continuation to the initial draft, keep building the story until we see 'IAMDONE'
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try:
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draft += '\n\n' + continuation
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except Exception as err:
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logger.error(f"Failed as: {err} and {continuation}")
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logger.info(f"Writing in progress... Current draft length: {len(draft)} characters")
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search_terms = f"""
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I will provide you with blog outline, your task is to read the outline & return 3 google search keywords.
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Your response will be used to do web research for writing on the given outline.
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Do not explain your response, provide 3 google search sentences encompassing the given content outline.
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Provide the search term results as comma separated values.\n\n
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Content Outline:\n
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'{content_outline}'
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"""
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search_words = generate_with_retry(model_pro, search_terms).text
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status.update(label=f"Search terms from written draft: {search_words}")
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while 'IAMDONE' not in continuation:
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try:
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#web_research_result, m_titles = do_metaphor_ai_research(content_keywords)
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str_list = re.split(r',\s*', search_words)
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# Strip quotes from each element
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str_list = [s.strip('\'"') for s in str_list]
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for search_term in str_list:
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web_research_result, m_titles, t_titles = do_tavily_ai_search(search_term, max_results=5)
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continuation = generate_with_retry(model, continuation_prompt.format(
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content_title=content_title,
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content_outline=content_outline,
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content_text=draft,
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web_research_result=web_research_result,
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writing_guidelines=writing_guidelines)).text
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draft += '\n\n' + continuation
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logger.info(f"Writing in progress... Current draft length: {len(draft)} characters")
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status.update(label=f"Writing in progress... Current draft length: {len(draft)} characters")
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# At this point, the context is little stale. We should more web research on
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# related queries as per the content outline, to augment the LLM context.
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except Exception as err:
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logger.error(f"Failed to continually write the Essay: {err}")
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return
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# Remove 'IAMDONE' and print the final story
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final = draft.replace('IAMDONE', '').strip()
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blog_title, blog_meta_desc, blog_tags, blog_categories = blog_metadata(final,
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content_keywords, m_titles)
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generated_image_filepath = None
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# TBD: Save the blog content as a .md file. Markdown or HTML ?
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save_blog_to_file(final, blog_title, blog_meta_desc, blog_tags, blog_categories, generated_image_filepath)
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blog_frontmatter = f"""
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---
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title: {blog_title}
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categories: [{blog_categories}]
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tags: [{blog_tags}]
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Meta description: {blog_meta_desc.replace(":", "-")}
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---"""
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logger.info(f"\n{blog_frontmatter}{final}\n\n")
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st.write(f"\n{blog_frontmatter}{final}\n\n")
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logger.info(f"\n\n ################ Finished writing Blog for : {content_keywords} #################### \n")
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