Files
ALwrity/lib/ai_writers/long_form_ai_writer.py
2025-04-11 17:47:55 +05:30

287 lines
12 KiB
Python

#####################################################
#
# Alwrity, AI Long form writer - Writing_with_Prompt_Chaining
# and generative AI.
#
#####################################################
import os
import re
import time #iwish
import sys
import yaml
from pathlib import Path
from dotenv import load_dotenv
from configparser import ConfigParser
import streamlit as st
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 get_blog_metadata_longform
from ..blog_postprocessing.save_blog_to_file import save_blog_to_file
from ..gpt_providers.text_generation.main_text_generation import llm_text_gen
def generate_with_retry(prompt, system_prompt=None):
"""
Generates content from the model with retry handling for errors.
Parameters:
prompt (str): The prompt to generate content from.
system_prompt (str, optional): Custom system prompt to use instead of the default one.
Returns:
str: The generated content.
"""
try:
# FIXME: Need a progress bar here.
return llm_text_gen(prompt, system_prompt)
except Exception as e:
logger.error(f"Error generating content: {e}")
st.error(f"Error generating content: {e}")
return False
def long_form_generator(content_keywords):
"""
Write long form content using prompt chaining and iterative generation.
Parameters:
content_keywords (str): The main keywords or topic for the long-form content.
Returns:
str: The generated long-form content.
"""
with st.status("Start Writing Long Form Article, Hold my Beer..", expanded=True) as status:
# Read the main_config to define tone, character, personality of the content to be generated.
try:
status.update(label=f"Starting to write content on {content_keywords}.")
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, content_length = read_return_config_section('blog_characteristics')
except Exception as err:
logger.error(f"Failed to Read config params from main_config: {err}")
st.error(f"Failed to Read config params from main_config: {err}")
return False
try:
filepath = os.path.join(os.environ["PROMPTS_DIR"], "long_form_ai_writer.prompts")
status.update(label=f"Reading Prompts from {filepath}.")
# 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:
st.error(f"Exit: Failed to read prompts from {filepath}: {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}',
content_type=content_type,
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
)
# 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(content_title.format(web_research_result=web_research_result))
logger.info(f"The title of the content is: {content_title}")
status.update(label=f"The title of the content is: {content_title}")
except Exception as err:
logger.error(f"Content title Generation Error: {err}")
return False
try:
content_outline = generate_with_retry(content_outline.format(
content_title=content_title,
web_research_result=web_research_result))
logger.info(f"The content Outline is: {content_outline}\n\n")
status.update(label=f"Completed with Content Outline.")
except Exception as err:
logger.error(f"Failed to generate content outline: {err}")
return False
try:
status.update(label=f"Do web research with Tavily to provide context for content creation.")
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, max_results=5)
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}")
st.error(f"Failed to do Tavily AI search: {err}")
return False
try:
starting_draft = generate_with_retry(starting_prompt.format(
content_title=content_title,
content_outline=content_outline,
web_research_result=web_research_result,
writing_guidelines=writing_guidelines))
except Exception as err:
st.error(f"Failed to Generate Starting draft: {err}")
logger.error(f"Failed to Generate Starting draft: {err}")
return False
try:
logger.info(f"Starting to write on the outline introduction.")
draft = starting_draft
continuation = generate_with_retry(continuation_prompt.format(
content_title=content_title,
content_outline=content_outline,
content_text=draft,
web_research_result=web_research_result,
writing_guidelines=writing_guidelines))
except Exception as err:
logger.error(f"Failed to write the initial draft: {err}")
return False
# 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}")
return False
logger.info(f"Writing in progress... Current draft length: {len(draft)} characters")
status.update(label=f"Writing in progress... Current draft length: {len(draft)} characters")
search_terms = f"""
I will provide you with content outline below, your task is to read the outline & return 8 google search keywords.
Your response will be used to do web research for writing on the given outline.
Do not explain your response, provide 8 google search sentences encompassing the given content outline.
Important: Provide the search term results as comma separated values.\n\n
Content Outline:\n
'{content_outline}'
"""
search_words = generate_with_retry(search_terms)
status.update(label=f"Search terms from written draft: {search_words}")
while 'IAMDONE' not in continuation:
#web_research_result, m_titles = do_metaphor_ai_research(content_keywords)
str_list = re.split(r',\s*', search_words)
# Strip quotes from each element
str_list = [s.strip('\'"') for s in str_list]
# for search_term in str_list:
# web_research_result, m_titles, t_titles = do_tavily_ai_search(search_term, max_results=5)
# status.update(label=f"Search terms from written draft: {search_term}")
# 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
try:
continuation = generate_with_retry(continuation_prompt.format(
content_title=content_title,
content_outline=content_outline,
content_text=draft,
web_research_result=web_research_result,
writing_guidelines=writing_guidelines))
draft += '\n\n' + continuation
logger.info(f"Writing in progress... Current draft length: {len(draft)} characters")
status.update(label=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.
except Exception as err:
st.error(f"Failed to continually write long-form content: {err}")
logger.error(f"Failed to continually write the Essay: {err}")
return False
# Remove 'IAMDONE' and print the final story
final = draft.replace('IAMDONE', '').strip()
status.update(label="Success: Finished writing Long form content.")
# # In long content sending the whole content for each content metadata is expensive.
# # https://ai.google.dev/gemini-api/docs/caching?lang=python
# #blog_title, blog_meta_desc, blog_tags, blog_categories = get_blog_metadata_longform(final)
# blog_categories = get_blog_metadata_longform(final)
# print("\n\n-----{blog_categories}------\n\n")
#
# status.update(label="Success: Finished with Title, Meta Description, Tags, categories")
# 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)
logger.info(f"\n{final}\n\n")
logger.info(f"\n\n ################ Finished writing Blog for : {content_keywords} #################### \n")
with st.expander("**Click to View the final content draft:**"):
st.markdown(f"\n{final}\n\n")
return final
def generate_long_form_content(content_keywords):
"""
Main function to generate long-form content based on the provided keywords.
Parameters:
content_keywords (str): The main keywords or topic for the long-form content.
Returns:
str: The generated long-form content.
"""
return long_form_generator(content_keywords)
# Example usage
if __name__ == "__main__":
# Example usage of the function
content_keywords = "artificial intelligence in healthcare"
generated_content = generate_long_form_content(content_keywords)
print(f"Generated content: {generated_content[:100]}...")