224 lines
8.8 KiB
Python
224 lines
8.8 KiB
Python
#####################################################
|
|
#
|
|
# Alwrity, AI Long form writer - Writing_with_Prompt_Chaining
|
|
# and generative AI.
|
|
#
|
|
#####################################################
|
|
|
|
import os
|
|
import time #iwish
|
|
import sys
|
|
import yaml
|
|
from pathlib import Path
|
|
from dotenv import load_dotenv
|
|
from configparser import ConfigParser
|
|
|
|
from google.api_core import retry
|
|
import google.generativeai as genai
|
|
from pprint import pprint
|
|
from textwrap import dedent
|
|
|
|
from loguru import logger
|
|
logger.remove()
|
|
logger.add(sys.stdout,
|
|
colorize=True,
|
|
format="<level>{level}</level>|<green>{file}:{line}:{function}</green>| {message}"
|
|
)
|
|
|
|
from ..utils.read_main_config_params import read_return_config_section
|
|
from ..ai_web_researcher.gpt_online_researcher import do_metaphor_ai_research
|
|
from ..ai_web_researcher.gpt_online_researcher import do_google_serp_search, do_tavily_ai_search
|
|
from ..blog_metadata.get_blog_metadata import blog_metadata
|
|
from ..blog_postprocessing.save_blog_to_file import save_blog_to_file
|
|
|
|
|
|
def generate_with_retry(model, prompt):
|
|
"""
|
|
Generates content from the model with retry handling for errors.
|
|
|
|
Parameters:
|
|
model (GenerativeModel): The generative model to use for content generation.
|
|
prompt (str): The prompt to generate content from.
|
|
|
|
Returns:
|
|
str: The generated content.
|
|
"""
|
|
try:
|
|
# FIXME: Need a progress bar here.
|
|
return model.generate_content(prompt, request_options={'retry':retry.Retry()})
|
|
except Exception as e:
|
|
logger.error(f"Error generating content: {e}")
|
|
return ""
|
|
|
|
|
|
def long_form_generator(content_keywords):
|
|
"""
|
|
Write long form content using prompt chaining and iterative generation.
|
|
Parameters:
|
|
"""
|
|
# Read the main_config to define tone, character, personality of the content to be generated.
|
|
try:
|
|
logger.info(f"Starting to write content on {content_keywords}.")
|
|
# Define persona and writing guidelines
|
|
content_tone, target_audience, content_type, content_language, output_format = read_return_config_section('blog_characteristics')
|
|
except Exception as err:
|
|
logger.error(f"Failed to Read config params from main_config: {err}")
|
|
return
|
|
|
|
try:
|
|
filepath = os.path.join(os.environ["PROMPTS_DIR"], "long_form_ai_writer.prompts")
|
|
# Check if file exists
|
|
if not os.path.exists(filepath):
|
|
raise FileNotFoundError(f"File {filepath} does not exist")
|
|
with open(filepath, 'r') as file:
|
|
prompts = yaml.safe_load(file)
|
|
except Exception as err:
|
|
logger.error(f"Exit: Failed to read prompts from {filepath}: {err}")
|
|
exit(1)
|
|
|
|
writing_guidelines = prompts.get('writing_guidelines').format(
|
|
content_language=content_language,
|
|
content_tone=content_tone,
|
|
content_type=content_type,
|
|
output_format=output_format,
|
|
content_keywords=content_keywords,
|
|
target_audience=target_audience
|
|
)
|
|
|
|
content_title = prompts.get('content_title').format(
|
|
content_language=content_language,
|
|
content_keywords=content_keywords,
|
|
target_audience=target_audience
|
|
)
|
|
|
|
content_outline = prompts.get('content_outline').format(
|
|
content_language=content_language,
|
|
content_title='{content_title}',
|
|
target_audience=target_audience
|
|
)
|
|
|
|
starting_prompt = prompts.get('starting_prompt').format(
|
|
content_language=content_language,
|
|
content_title='{content_title}',
|
|
content_outline='{content_outline}',
|
|
writing_guidelines=writing_guidelines
|
|
)
|
|
|
|
continuation_prompt = prompts.get('continuation_prompt').format(
|
|
content_language=content_language,
|
|
content_title='{content_title}',
|
|
content_outline='{content_outline}',
|
|
content_text='{content_text}',
|
|
web_research_result='{web_research_result}',
|
|
writing_guidelines=writing_guidelines
|
|
)
|
|
|
|
# Configure generative AI
|
|
load_dotenv(Path('../.env'))
|
|
genai.configure(api_key=os.getenv('GEMINI_API_KEY'))
|
|
# Initialize the generative model
|
|
model = genai.GenerativeModel('gemini-pro')
|
|
model_pro = genai.GenerativeModel('gemini-1.5-flash-latest')
|
|
|
|
# Do SERP web research for given keywords to generate title and outline.
|
|
web_research_result, g_titles = do_google_serp_search(content_keywords)
|
|
|
|
# Generate prompts
|
|
try:
|
|
content_title = generate_with_retry(model_pro, content_title.format(web_research_result=web_research_result)).text
|
|
logger.info(f"The title of the content is: {content_title}")
|
|
except Exception as err:
|
|
logger.error(f"Content title Generation Error: {err}")
|
|
return
|
|
|
|
try:
|
|
content_outline = generate_with_retry(model_pro,
|
|
content_outline.format(content_title=content_title, web_research_result=web_research_result)).text
|
|
logger.info(f"The content Outline is: {content_outline}\n\n")
|
|
except Exception as err:
|
|
logger.error(f"Failed to generate content outline: {err}")
|
|
|
|
try:
|
|
starting_draft = generate_with_retry(model_pro, starting_prompt.format(
|
|
content_title=content_title,
|
|
content_outline=content_outline,
|
|
web_research_result=web_research_result,
|
|
writing_guidelines=writing_guidelines)).text
|
|
except Exception as err:
|
|
logger.error(f"Failed to Generate Starting draft: {err}")
|
|
return
|
|
|
|
try:
|
|
logger.info(f"Starting to write on the outline introduction.")
|
|
draft = starting_draft
|
|
continuation = generate_with_retry(model, continuation_prompt.format(
|
|
content_title=content_title,
|
|
content_outline=content_outline,
|
|
content_text=draft,
|
|
web_research_result=web_research_result,
|
|
writing_guidelines=writing_guidelines)).text
|
|
except Exception as err:
|
|
logger.error(f"Failed to write the initial draft: {err}")
|
|
|
|
# Add the continuation to the initial draft, keep building the story until we see 'IAMDONE'
|
|
try:
|
|
draft += '\n\n' + continuation
|
|
except Exception as err:
|
|
logger.error(f"Failed as: {err} and {continuation}")
|
|
try:
|
|
logger.info("Do web research with Tavily to provide context for content creation.")
|
|
# Do Metaphor/Exa AI search.
|
|
table_data = []
|
|
web_research_result, m_titles, t_titles = do_tavily_ai_search(content_keywords)
|
|
for item in web_research_result.get("results"):
|
|
title = item.get("title", "")
|
|
snippet = item.get("content", "")
|
|
table_data.append([title, snippet])
|
|
web_research_result = table_data
|
|
except Exception as err:
|
|
logger.error(f"Failed to do Tavily AI search: {err}")
|
|
return
|
|
|
|
logger.info(f"Writing in progress... Current draft length: {len(draft)} characters")
|
|
while 'IAMDONE' not in continuation:
|
|
try:
|
|
web_research_result, m_titles = do_metaphor_ai_research(content_keywords)
|
|
continuation = generate_with_retry(model, continuation_prompt.format(
|
|
content_title=content_title,
|
|
content_outline=content_outline,
|
|
content_text=draft,
|
|
web_research_result=web_research_result,
|
|
writing_guidelines=writing_guidelines)).text
|
|
|
|
draft += '\n\n' + continuation
|
|
logger.info(f"Writing in progress... Current draft length: {len(draft)} characters")
|
|
|
|
# At this point, the context is little stale. We should more web research on
|
|
# related queries as per the content outline, to augment the LLM context.
|
|
# web_research_result, m_titles = do_metaphor_ai_research(content_keywords)
|
|
#logger.info(f"Doing Tavily Search Again, Should mix with Exa.ai")
|
|
#web_research_result, m_titles, t_titles = do_tavily_ai_search(content_title)
|
|
except Exception as err:
|
|
logger.error(f"Failed to continually write the Essay: {err}")
|
|
return
|
|
|
|
# Remove 'IAMDONE' and print the final story
|
|
final = draft.replace('IAMDONE', '').strip()
|
|
|
|
blog_title, blog_meta_desc, blog_tags, blog_categories = blog_metadata(final,
|
|
content_keywords, m_titles)
|
|
|
|
generated_image_filepath = None
|
|
# TBD: Save the blog content as a .md file. Markdown or HTML ?
|
|
save_blog_to_file(final, blog_title, blog_meta_desc, blog_tags, blog_categories, generated_image_filepath)
|
|
|
|
blog_frontmatter = f"""
|
|
---
|
|
title: {blog_title}
|
|
categories: [{blog_categories}]
|
|
tags: [{blog_tags}]
|
|
Meta description: {blog_meta_desc.replace(":", "-")}
|
|
---"""
|
|
logger.info(f"\n{blog_frontmatter}{final}\n\n")
|
|
logger.info(f"\n\n ################ Finished writing Blog for : {content_keywords} #################### \n")
|