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

110 lines
4.8 KiB
Python

import sys
import os
from textwrap import dedent
import json
import asyncio
from pathlib import Path
from datetime import datetime
import streamlit as st
from dotenv import load_dotenv
load_dotenv(Path('../../.env'))
from loguru import logger
logger.remove()
logger.add(sys.stdout,
colorize=True,
format="<level>{level}</level>|<green>{file}:{line}:{function}</green>| {message}"
)
from ..ai_web_researcher.firecrawl_web_crawler import scrape_url
from ..blog_metadata.get_blog_metadata import blog_metadata
from ..blog_postprocessing.save_blog_to_file import save_blog_to_file
from ..gpt_providers.text_to_image_generation.main_generate_image_from_prompt import generate_image
from ..gpt_providers.text_generation.main_text_generation import llm_text_gen
from ..gpt_providers.image_to_text_gen.gemini_image_describe import describe_image, analyze_image_with_prompt
def blog_from_image(prompt, uploaded_img):
"""
This function will take a blog Topic to first generate sections for it
and then generate content for each section.
"""
# Use to store the blog in a string, to save in a *.md file.
blog_markdown_str = None
logger.info(f"Researching and Writing Blog on {uploaded_img} and {prompt}")
# FIXME: Implement support for Openai.
if not os.getenv("GEMINI_API_KEY"):
st.error("Only Gemini supported, Open Issue ticket on github for Openai, others.")
st.stop()
with st.status("Started Writing from Image..", expanded=True) as status:
st.empty()
status.update(label=f"Researching and Writing Blog on given Image")
try:
blog_markdown_str = write_blog_from_image(prompt, uploaded_img)
except Exception as err:
st.error(f"Failed to write blog from Image - Error: {err}")
logger.error(f"Failed to write blog from image: {err}")
st.stop()
status.update(label="Successfully wrote blog from image.", expanded=False, state="complete")
try:
status.update(label="🙎 Generating - Title, Meta Description, Tags, Categories for the content.")
blog_title, blog_meta_desc, blog_tags, blog_categories = asyncio.run(blog_metadata(blog_markdown_str))
except Exception as err:
st.error(f"Failed to get blog metadata: {err}")
try:
status.update(label="🙎 Generating Image for the new blog.")
generated_image_filepath = generate_image(f"{blog_title} + ' ' + {blog_meta_desc}")
except Exception as err:
st.warning(f"Failed in Image generation: {err}")
saved_blog_to_file = save_blog_to_file(blog_markdown_str, blog_title, blog_meta_desc,
blog_tags, blog_categories, generated_image_filepath)
status.update(label=f"Saved the content in this file: {saved_blog_to_file}")
logger.info(f"\n\n --------- Finished writing Blog -------------- \n")
st.image(generated_image_filepath, caption=blog_title)
st.markdown(f"{blog_markdown_str}")
status.update(label=f"Finished, Review & Use your Original Content Below: {saved_blog_to_file}", state="complete")
# Clean up the temporary file after processing (optional)
os.remove(uploaded_img)
def write_blog_from_image(prompt, uploaded_img):
"""Combine the given online research and GPT blog content"""
try:
config_path = Path(os.environ["ALWRITY_CONFIG"])
with open(config_path, 'r', encoding='utf-8') as file:
config = json.load(file)
except Exception as err:
logger.error(f"Error: Failed to read values from config: {err}")
exit(1)
blog_characteristics = config['Blog Content Characteristics']
if not prompt:
prompt = f"""
As expert Creative Content writer, analyse the given image carefully.
I want you to write a detailed {blog_characteristics['Blog Type']} blog post including 5 FAQs.
Below are the guidelines to follow:
1). You must respond in {blog_characteristics['Blog Language']} language.
2). Tone and Brand Alignment: Adjust your tone, voice, personality for {blog_characteristics['Blog Tone']} audience.
3). Make sure your response content length is of {blog_characteristics['Blog Length']} words.
"""
logger.info("Generating blog and FAQs from image analysis.")
try:
# Use the gemini_image_describe function to analyze the image with the custom prompt
response = analyze_image_with_prompt(uploaded_img, prompt)
if not response:
logger.error("Failed to get response from image analysis")
return "Failed to generate content from image."
return response
except Exception as err:
logger.error(f"Exit: Failed to get response from image analysis: {err}")
exit(1)