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WIP - UI, Audio, firecrawl, long-form - V0.5

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ajaysi
2024-06-20 22:48:52 +05:30
parent 899abad1ba
commit 074ddf6210
12 changed files with 206 additions and 131 deletions
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94
lib/ai_writers/keywords_to_blog_streamlit.py
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@@ -1,21 +1,27 @@
import sys
import os
import asyncio
from textwrap import dedent
from pathlib import Path
from datetime import datetime
import streamlit as st
from gtts import gTTS
import base64
from dotenv import load_dotenv
# Load environment variables
load_dotenv(Path('../../.env'))
# Logger setup
from loguru import logger
logger.remove()
logger.add(sys.stdout,
colorize=True,
format="<level>{level}</level>|<green>{file}:{line}:{function}</green>| {message}"
)
colorize=True,
format="<level>{level}</level>|<green>{file}:{line}:{function}</green>| {message}")
from ..ai_web_researcher.gpt_online_researcher import do_google_serp_search,\
do_tavily_ai_search, do_metaphor_ai_research, do_google_pytrends_analysis
# Import other necessary modules
from ..ai_web_researcher.gpt_online_researcher import (
do_google_serp_search, do_tavily_ai_search,
do_metaphor_ai_research, do_google_pytrends_analysis)
from .blog_from_google_serp import write_blog_google_serp, blog_with_research
from ..ai_web_researcher.you_web_reseacher import get_rag_results, search_ydc_index
from ..blog_metadata.get_blog_metadata import blog_metadata
@@ -23,6 +29,21 @@ 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
# Function to convert text to speech and save as an audio file
def text_to_speech(text, lang='en'):
tts = gTTS(text=text, lang=lang)
tts.save("output.mp3")
return "output.mp3"
# Function to get audio file as a downloadable link
def get_audio_file(audio_file):
with open(audio_file, "rb") as file:
data = file.read()
b64_data = base64.b64encode(data).decode()
return f'<a href="data:audio/mp3;base64,{b64_data}" download="output.mp3">Download audio file</a>'
def write_blog_from_keywords(search_keywords, url=None):
"""
This function will take a blog Topic to first generate sections for it
@@ -45,8 +66,8 @@ def write_blog_from_keywords(search_keywords, url=None):
status.update(label=f"🛀 Starting Tavily AI research: {search_keywords}")
tavily_search_result, t_titles, t_answer = do_tavily_ai_search(search_keywords)
status.update(label=f"🙆 Finished Google Search & Tavily AI Search on: {search_keywords}",
state="complete", expanded=False)
status.update(label=f"🙆 Finished Google Search & Tavily AI Search on: {search_keywords}",
state="complete", expanded=False)
except Exception as err:
st.error(f"Failed in web research: {err}")
@@ -66,21 +87,21 @@ def write_blog_from_keywords(search_keywords, url=None):
# logger.info/check the final blog content.
logger.info("######### Draft1: Finished Blog from Google web search: ###########")
with st.status("Started Writing blog from Tavily Web search..", expanded=True) as status:
# Do Tavily AI research to augument the above blog.
# Do Tavily AI research to augment the above blog.
try:
#example_blog_titles.append(t_titles)
# example_blog_titles.append(t_titles)
if blog_markdown_str and tavily_search_result:
logger.info(f"\n\n######### Blog content after Tavily AI research: ######### \n\n")
blog_markdown_str = write_blog_google_serp(search_keywords, tavily_search_result)
status.update(label="Finished Writing Blog From Tavily Results:{blog_markdown_str}", expanded=True)
status.update(label=f"Finished Writing Blog From Tavily Results:{blog_markdown_str}", expanded=True)
except Exception as err:
logger.error(f"Failed to do Tavily AI research: {err}")
status.update(label="🙎 Generating - Title, Meta Description, Tags, Categories for the content.", expanded=True)
try:
blog_title, blog_meta_desc, blog_tags, blog_categories = blog_metadata(blog_markdown_str)
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}")
@@ -94,38 +115,21 @@ def write_blog_from_keywords(search_keywords, url=None):
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)
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 for : {search_keywords} -------------- \n")
# Render the result on streamlit UI
st.image(generated_image_filepath)
st.markdown(f"{blog_markdown_str}")
status.update(label=f"Finished, Review & Use your Original Content Below: {saved_blog_to_file}", state="complete")
# Display options below the content
col1, col2, col3, col4, col5 = st.columns(5)
if col1.button('Copy'):
pyperclip.copy(blog_markdown_str)
st.success("Text copied to clipboard!")
if col2.button('Rephrase'):
rephrased_text = rephrase_text(blog_markdown_str)
st.markdown(rephrased_text)
if col3.button('Change Tone'):
tone = st.selectbox("Select Tone", ["Formal", "Casual", "Professional"])
if st.button("Apply Tone"):
toned_text = change_tone(blog_markdown_str, tone)
st.markdown(toned_text)
if col4.button('Make Shorter'):
shorter_text = make_shorter(blog_markdown_str)
st.markdown(shorter_text)
if col5.button('Translate'):
language = st.selectbox("Select Language", ["Spanish", "French", "German"])
if st.button("Translate"):
translated_text = translate_text(blog_markdown_str, language)
st.markdown(translated_text)
# Render the result on streamlit UI
if generated_image_filepath:
st.image(generated_image_filepath)
st.markdown(f"{blog_markdown_str}")
status.update(label=f"Finished, Review & Use your Original Content Below: {saved_blog_to_file}",
state="complete")
# Passing the text and language to the engine, here we have marked slow=False. Which tells
# the module that the converted audio should have a high speed
tts = gTTS(text=blog_markdown_str, lang='en', slow=False)
# Saving the converted audio in a mp3 file
tts.save("delete_me.mp3")
st.audio("delete_me.mp3")