Alwrity version 0.5.4
This commit is contained in:
ajaysi
@@ -1,232 +0,0 @@
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import re
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import os
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import PyPDF2
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import openai
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import streamlit as st
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import tempfile
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from loguru import logger
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from lib.ai_writers.ai_news_article_writer import ai_news_generation
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from lib.ai_writers.ai_finance_report_generator.ai_financial_dashboard import get_dashboard
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from lib.ai_writers.ai_facebook_writer.facebook_ai_writer import facebook_main_menu
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from lib.ai_writers.linkedin_writer.linkedin_ai_writer import linkedin_main_menu
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from lib.ai_writers.twitter_writers.twitter_dashboard import run_dashboard
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from lib.ai_writers.insta_ai_writer import insta_writer
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from lib.ai_writers.youtube_writers.youtube_ai_writer import youtube_main_menu
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from lib.ai_writers.ai_essay_writer import ai_essay_generator
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from lib.gpt_providers.text_to_image_generation.main_generate_image_from_prompt import generate_image
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#from lib.content_planning_calender.content_planning_agents_alwrity_crew import ai_agents_content_planner
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from lib.gpt_providers.text_generation.main_text_generation import llm_text_gen
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def ai_agents_team():
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# Define options for AI Content Teams
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st.title("🐲 Your AI Agents Teams")
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st.markdown("""Alwrity offers AI agents team for content creators to easily modify them for their needs.
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Abstracting tech & plumbing, easily define role, goal, task. Use different AI agents framework.""")
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options = [
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"AI Planning Team",
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"AI Content Creation Team"
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]
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# Radio button for choosing an AI Content Team
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selected_team = st.radio("**Choose AI Agents Team:**", options)
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if selected_team == "AI Planning Team":
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st.title("AI Agents for Content Ideation")
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plan_keywords = st.text_input(
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"Enter Keywords to get 2 months content calendar:",
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placeholder="Enter keywords to generate AI content calendar:",
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help="Enter at least two words for better results."
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)
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if st.button("Get calendar"):
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if plan_keywords and len(plan_keywords.split()) >= 2:
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with st.spinner("Get Content Plan..."):
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try:
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#plan_content = ai_agents_content_planner(plan_keywords)
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st.success(f"Coming soon: Content plan for: {plan_keywords}")
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#st.markdown(plan_content)
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except Exception as err:
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st.error(f"Failed to generate content plan: {err}")
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else:
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st.error("🚫 Single keywords are just too vague. Try again.")
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elif selected_team == "AI Content Creation Team":
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content_agents()
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def content_agents():
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st.markdown("AI Agents Team for Content Writing")
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content_keywords = st.text_input(
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"Enter Main Domain Keywords of your business:",
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placeholder="Better keywords, Better content. Get keywords from Google search",
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help="These keywords define your main business sector, blogging niche, Industry, domain etc"
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)
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if st.button("Start Writing"):
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if content_keywords and len(content_keywords.split()) >= 2:
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with st.spinner("Generating Content..."):
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try:
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#calendar_content = ai_agents_writers(content_keywords)
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st.success(f"🚫 Not implemented yet: {content_keywords}")
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#st.markdown(calendar_content)
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except Exception as err:
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st.error(f"🚫 Failed to generate content with AI Agents: {err}")
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else:
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st.error("🚫 Single keywords are just too vague. Try again.")
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def essay_writer():
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st.title("AI Essay Writer 📝")
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st.write("Select your essay type, education level, and desired length, then let AI generate an essay for you. ✨")
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# Define essay types and education levels
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essay_types = [
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"📖 Argumentative - Forming an opinion via research. Building an evidence-based argument.",
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"📚 Expository - Knowledge of a topic. Communicating information clearly.",
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"✒️ Narrative - Creative language use. Presenting a compelling narrative.",
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"🎨 Descriptive - Creative language use. Describing sensory details."
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]
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education_levels = [
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"🏫 Primary School",
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"🏫 High School",
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"🎓 College",
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"🎓 Graduate School"
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]
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# Define the options for number of pages
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num_pages_options = [
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"📄 Short Form (1-2 pages)",
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"📄📄 Medium Form (3-5 pages)",
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"📄📄📄 Long Form (6+ pages)"
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]
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# Create columns for input fields
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col1, col2 = st.columns(2)
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with col1:
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# Ask the user for the title of the essay
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essay_title = st.text_input("📝 Essay Title", placeholder="Enter the title of your essay", help="Provide a clear and concise title for your essay.")
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# Ask the user for type of essay
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selected_essay_type = st.selectbox("📚 Type of Essay", options=essay_types, help="Choose the type of essay you want to write.")
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with col2:
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# Ask the user for level of education
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selected_education_level = st.selectbox("🎓 Level of Education", options=education_levels, help="Choose your level of education.")
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# Ask the user for number of pages
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selected_num_pages = st.selectbox("📄 Number of Pages", options=num_pages_options, help="Select the length of your essay.")
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if st.button("🚀 Generate Essay"):
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if essay_title:
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st.success("Generating your essay... ✨")
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ai_essay_generator(essay_title, selected_essay_type, selected_education_level, selected_num_pages)
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else:
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st.error("Please enter a valid title for your essay. 🚫")
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def ai_news_writer():
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""" AI News Writer """
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st.markdown("<h1>📰 AI News Writer 🗞️ </h1>", unsafe_allow_html=True)
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# Input for news keywords
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news_keywords = st.text_input(
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"**🔑 Enter Keywords from News Headlines:**",
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placeholder="Describe the News article in 3-5 words. Enter main keywords describing the News Event:",
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help="Enter at least two words for better results."
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)
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if news_keywords and len(news_keywords.split()) < 2:
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st.error("🚫 News keywords should be at least two words long. Least, you can do..")
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# Selectbox for country and language
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countries = [
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("es", "Spain"),
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("vn", "Vietnam"),
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("pk", "Pakistan"),
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("in", "India"),
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("de", "Germany"),
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("cn", "China")
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]
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languages = [
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("en", "English"),
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("es", "Spanish"),
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("vi", "Vietnamese"),
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("ar", "Arabic"),
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("hi", "Hindi"),
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("de", "German"),
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("zh-cn", "Chinese")
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]
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col1, col2 = st.columns(2)
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with col1:
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news_country = st.selectbox("**🌍 Select Origin Country of News Event:**",
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countries, format_func=lambda x: x[1], help="Which country did the NEWS originate from ?")
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with col2:
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news_language = st.selectbox("**🗣️ Select News Article Language to Search For:**",
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languages, format_func=lambda x: x[1], help="Language to output News Article in ?")
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if st.button("📰 Generate News Report"):
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if news_keywords and len(news_keywords.split()) >= 2:
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with st.spinner("Generating News Report... ⏳"):
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try:
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news_report = ai_news_generation(news_keywords, news_country, news_language)
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st.success(f"Successfully generated news report on: {news_keywords} 🎉")
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st.markdown(news_report)
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except Exception as err:
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st.error(f"Failed to generate news report: {err} ❌")
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else:
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st.error("Please enter valid keywords for the news report. 🚫")
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def ai_finance_ta_writer():
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st.markdown("<div class='sub-header'>AI Financial Technical Analysis Writer</div>", unsafe_allow_html=True)
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ticker_symbol = st.text_input(
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"Enter Ticker Symbol for TA:",
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placeholder="Enter a valid Ticker Symbol (Examples: IBM, BABA, HDFCBANK.NS, TATAMOTORS.NS etc)",
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help="Be sure of the ticker symbol. Double-check it! Examples: IBM, BABA, HDFCBANK.NS, TATAMOTORS.NS"
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)
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if st.button("Generate TA Report"):
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if ticker_symbol:
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with st.spinner("Generating TA Report..."):
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try:
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# Get dashboard instance and generate technical analysis
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dashboard = get_dashboard()
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ta_report = dashboard.generate_technical_analysis(ticker_symbol)
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st.success(f"Successfully generated TA report for: {ticker_symbol}")
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st.markdown(ta_report)
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except Exception as err:
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st.error(f"🚫 Check ticker symbol: Failed to write Financial Technical Analysis. Error: {err}")
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else:
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st.error("🚫 Provide a valid Ticker Symbol. Don't waste my time.")
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def ai_social_writer():
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# Define social media platforms as radio buttons
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social_media_options = [
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("facebook", "Facebook"),
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("linkedin", "LinkedIn"),
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("twitter", "Twitter"),
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("instagram", "Instagram"),
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("youtube", "YouTube")
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]
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# Selectbox for choosing a platform
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selected_platform = st.radio("Choose a Social Media Platform:", social_media_options, format_func=lambda x: x[1])
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if "facebook" in selected_platform:
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facebook_main_menu()
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elif "linkedin" in selected_platform:
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linkedin_main_menu()
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elif "twitter" in selected_platform:
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run_dashboard()
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elif "instagram" in selected_platform:
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insta_writer()
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elif "youtube" in selected_platform:
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youtube_main_menu()
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@@ -1,310 +0,0 @@
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"""Test configuration settings page for ALwrity."""
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import streamlit as st
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from loguru import logger
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import asyncio
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from lib.web_crawlers.async_web_crawler import AsyncWebCrawlerService
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from pages.style_utils import (
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get_test_config_styles,
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get_glass_container,
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get_info_section,
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get_example_box,
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get_analysis_section,
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get_style_guide_html
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)
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import sys
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from lib.personalization.style_analyzer import StyleAnalyzer
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# Set page config - must be the first Streamlit command
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st.set_page_config(
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layout="wide",
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initial_sidebar_state="collapsed",
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menu_items={
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'Get Help': None,
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'Report a bug': None,
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'About': None
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}
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)
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import yaml
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from pathlib import Path
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import os
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from loguru import logger
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from lib.utils.read_main_config_params import get_personalization_settings
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from lib.web_crawlers.crawl4ai_web_crawler import analyze_style
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# Configure logger
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logger.remove() # Remove default handler
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logger.add(
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"logs/test_config_settings.log",
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rotation="500 MB",
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retention="10 days",
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level="DEBUG",
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format="{time:YYYY-MM-DD HH:mm:ss} | {level} | {message}",
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backtrace=True,
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diagnose=True
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)
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logger.add(
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sys.stdout,
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level="INFO",
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format="<green>{time:YYYY-MM-DD HH:mm:ss}</green> | <level>{level: <8}</level> | <cyan>{message}</cyan>"
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)
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# Apply CSS styles
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st.markdown(get_test_config_styles(), unsafe_allow_html=True)
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def load_website_url():
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"""Load website URL from config file."""
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try:
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logger.debug("Loading website URL from config file")
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config_path = Path(os.environ["ALWRITY_CONFIG"])
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config = yaml.safe_load(config_path.read_text())
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url = config.get('website', {}).get('url', '')
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logger.info(f"Loaded website URL: {url}")
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return url
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except Exception as e:
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logger.error(f"Error loading website URL: {str(e)}", exc_info=True)
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return ''
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def display_style_analysis(analysis_results: dict):
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"""Display the style analysis results in a structured format."""
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try:
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# Writing Style Section
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st.markdown("### 🎨 Writing Style Analysis")
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writing_style = analysis_results.get("writing_style", {})
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writing_style_content = f"""
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<ul>
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<li><strong>Tone:</strong> {writing_style.get("tone", "N/A")}</li>
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<li><strong>Voice:</strong> {writing_style.get("voice", "N/A")}</li>
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<li><strong>Complexity:</strong> {writing_style.get("complexity", "N/A")}</li>
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<li><strong>Engagement Level:</strong> {writing_style.get("engagement_level", "N/A")}</li>
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</ul>
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"""
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st.markdown(get_analysis_section("Writing Style", writing_style_content), unsafe_allow_html=True)
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# Content Characteristics Section
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content_chars = analysis_results.get("content_characteristics", {})
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content_chars_content = f"""
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<ul>
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<li><strong>Sentence Structure:</strong> {content_chars.get("sentence_structure", "N/A")}</li>
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<li><strong>Vocabulary Level:</strong> {content_chars.get("vocabulary_level", "N/A")}</li>
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<li><strong>Paragraph Organization:</strong> {content_chars.get("paragraph_organization", "N/A")}</li>
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<li><strong>Content Flow:</strong> {content_chars.get("content_flow", "N/A")}</li>
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</ul>
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"""
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st.markdown(get_analysis_section("Content Characteristics", content_chars_content), unsafe_allow_html=True)
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# Target Audience Section
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target_audience = analysis_results.get("target_audience", {})
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target_audience_content = f"""
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<ul>
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<li><strong>Demographics:</strong> {', '.join(target_audience.get("demographics", ["N/A"]))}</li>
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<li><strong>Expertise Level:</strong> {target_audience.get("expertise_level", "N/A")}</li>
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<li><strong>Industry Focus:</strong> {target_audience.get("industry_focus", "N/A")}</li>
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<li><strong>Geographic Focus:</strong> {target_audience.get("geographic_focus", "N/A")}</li>
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</ul>
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"""
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st.markdown(get_analysis_section("Target Audience", target_audience_content), unsafe_allow_html=True)
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# Content Type Section
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content_type = analysis_results.get("content_type", {})
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content_type_content = f"""
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<ul>
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<li><strong>Primary Type:</strong> {content_type.get("primary_type", "N/A")}</li>
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<li><strong>Secondary Types:</strong> {', '.join(content_type.get("secondary_types", ["N/A"]))}</li>
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<li><strong>Purpose:</strong> {content_type.get("purpose", "N/A")}</li>
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<li><strong>Call to Action:</strong> {content_type.get("call_to_action", "N/A")}</li>
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</ul>
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"""
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st.markdown(get_analysis_section("Content Type", content_type_content), unsafe_allow_html=True)
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# Recommended Settings Section
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recommended = analysis_results.get("recommended_settings", {})
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recommended_content = f"""
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<ul>
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<li><strong>Writing Tone:</strong> {recommended.get("writing_tone", "N/A")}</li>
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<li><strong>Target Audience:</strong> {recommended.get("target_audience", "N/A")}</li>
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<li><strong>Content Type:</strong> {recommended.get("content_type", "N/A")}</li>
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<li><strong>Creativity Level:</strong> {recommended.get("creativity_level", "N/A")}</li>
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<li><strong>Geographic Location:</strong> {recommended.get("geographic_location", "N/A")}</li>
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</ul>
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"""
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st.markdown(get_analysis_section("Recommended Settings", recommended_content), unsafe_allow_html=True)
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except Exception as e:
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logger.error(f"Error displaying style analysis: {str(e)}")
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st.error(f"Error displaying analysis results: {str(e)}")
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def render_test_config_settings():
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"""Render the test configuration settings page."""
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try:
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logger.info("Starting to render test configuration settings")
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# Add back button at the top
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col1, col2 = st.columns([1, 3])
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with col1:
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if st.button("← Back to Personalization Setup"):
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logger.info("User clicked back to personalization setup")
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# Set session state for navigation
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st.session_state.current_step = 4
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st.session_state.next_step = "personalization_setup"
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# Navigate back to the main page where personalization setup is rendered
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st.switch_page("alwrity.py")
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# Title and description
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st.title("🎨 Find Your Style with ALwrity")
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st.markdown(get_glass_container(
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"<p>Enter a website URL or provide content samples to analyze your writing style and get personalized recommendations.</p>"
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), unsafe_allow_html=True)
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# Create two columns for the layout
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col1, col2 = st.columns([2, 1])
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with col1:
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# Website URL input
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st.markdown("### Website URL")
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url = st.text_input(
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"Enter your website URL",
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placeholder="https://example.com",
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help="Provide your website URL to analyze your content style. Leave empty if you want to provide written samples instead."
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)
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logger.debug(f"Website URL input value: {url}")
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# Alternative: Written samples
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if not url:
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st.markdown("### Written Samples")
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st.markdown(get_info_section("""
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<p>No website URL? No problem! You can provide written samples of your content instead.</p>
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<p>Share your best articles, blog posts, or any content that represents your writing style.</p>
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"""), unsafe_allow_html=True)
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samples = st.text_area(
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"Paste your content samples here",
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help="Paste 2-3 samples of your best content. This helps ALwrity understand your writing style."
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)
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logger.debug(f"Sample text length: {len(samples) if samples else 0}")
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st.markdown('</div>', unsafe_allow_html=True)
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# ALwrity Style button
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st.markdown("<div style='height: 20px'></div>", unsafe_allow_html=True)
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if st.button("🎨 ALwrity Style", use_container_width=True):
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if url:
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with st.status("Starting style analysis...", expanded=True) as status:
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try:
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logger.info(f"Starting style analysis for URL: {url}")
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# Step 1: Initialize crawler
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status.update(label="Step 1/4: Initializing web crawler...", state="running")
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crawler_service = AsyncWebCrawlerService()
|
||||
|
||||
# Step 2: Crawl website
|
||||
status.update(label="Step 2/4: Crawling website content...", state="running")
|
||||
loop = asyncio.new_event_loop()
|
||||
asyncio.set_event_loop(loop)
|
||||
result = loop.run_until_complete(crawler_service.crawl_website(url))
|
||||
loop.close()
|
||||
|
||||
if result.get('success', False):
|
||||
content = result.get('content', {})
|
||||
|
||||
# Step 3: Initialize style analyzer
|
||||
status.update(label="Step 3/4: Analyzing content style...", state="running")
|
||||
style_analyzer = StyleAnalyzer()
|
||||
|
||||
# Step 4: Perform style analysis
|
||||
status.update(label="Step 4/4: Generating style recommendations...", state="running")
|
||||
style_analysis = style_analyzer.analyze_content_style(content)
|
||||
|
||||
if style_analysis.get('error'):
|
||||
status.update(label="Analysis failed", state="error")
|
||||
st.error(f"Style analysis failed: {style_analysis['error']}")
|
||||
else:
|
||||
status.update(label="Analysis complete!", state="complete")
|
||||
# Display style analysis results
|
||||
display_style_analysis(style_analysis)
|
||||
|
||||
# Display original content in tabs
|
||||
tab1, tab2, tab3 = st.tabs(["Content", "Metadata", "Links"])
|
||||
|
||||
with tab1:
|
||||
st.markdown("### Main Content")
|
||||
st.markdown(content.get('main_content', 'No content found'))
|
||||
|
||||
with tab2:
|
||||
st.markdown("### Metadata")
|
||||
st.markdown(f"""
|
||||
**Title:** {content.get('title', 'No title found')}
|
||||
|
||||
**Description:** {content.get('description', 'No description found')}
|
||||
|
||||
**Meta Tags:**
|
||||
{content.get('meta_tags', {})}
|
||||
""")
|
||||
|
||||
with tab3:
|
||||
st.markdown("### Links")
|
||||
for link in content.get('links', []):
|
||||
st.markdown(f"- [{link.get('text', '')}]({link.get('href', '')})")
|
||||
|
||||
else:
|
||||
status.update(label="Crawling failed", state="error")
|
||||
st.error(f"Failed to analyze website: {result.get('error', 'Unknown error')}")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error during style analysis: {str(e)}")
|
||||
st.error(f"Analysis failed: {str(e)}")
|
||||
elif samples:
|
||||
with st.spinner("Analyzing content samples..."):
|
||||
try:
|
||||
# TODO: Implement sample text analysis
|
||||
st.info("Sample text analysis coming soon!")
|
||||
except Exception as e:
|
||||
logger.error(f"Error analyzing samples: {str(e)}")
|
||||
st.error(f"Analysis failed: {str(e)}")
|
||||
else:
|
||||
st.warning("Please provide either a website URL or content samples")
|
||||
|
||||
with col2:
|
||||
st.markdown("""
|
||||
### How ALwrity Discovers Your Style
|
||||
|
||||
**AI-Powered Style Analysis**
|
||||
|
||||
ALwrity AI analyzes your existing content to understand your unique writing style and preferences. This helps us generate content that matches your voice perfectly.
|
||||
|
||||
**Step 1: Content Analysis**
|
||||
|
||||
We'll analyze your website content or written samples to understand:
|
||||
|
||||
- Writing tone and voice
|
||||
- Vocabulary and language style
|
||||
- Content structure and formatting
|
||||
- Target audience and engagement style
|
||||
|
||||
**Step 2: Style Recommendations**
|
||||
|
||||
Based on the analysis, we'll provide:
|
||||
|
||||
- Personalized writing guidelines
|
||||
- Content structure templates
|
||||
- Tone and voice recommendations
|
||||
- Audience engagement strategies
|
||||
|
||||
**Step 3: Content Generation**
|
||||
|
||||
Finally, we'll use these insights to:
|
||||
|
||||
- Generate content that matches your style
|
||||
- Maintain consistency across all content
|
||||
- Optimize for your target audience
|
||||
- Ensure brand voice alignment
|
||||
""")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in render_test_config_settings: {str(e)}")
|
||||
st.error(f"An error occurred: {str(e)}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
logger.info("Starting test config settings page")
|
||||
render_test_config_settings()
|
||||
logger.info("Test config settings page rendered successfully")
|
||||
@@ -1,23 +0,0 @@
|
||||
import streamlit as st
|
||||
from streamlit_mic_recorder import speech_to_text
|
||||
|
||||
def record_voice(language="en"):
|
||||
# https://github.com/B4PT0R/streamlit-mic-recorder?tab=readme-ov-file#example
|
||||
state = st.session_state
|
||||
if "text_received" not in state:
|
||||
state.text_received = []
|
||||
|
||||
text = speech_to_text(
|
||||
start_prompt="🎙️Press & Speak🔊",
|
||||
stop_prompt="🔇Stop Recording🚨",
|
||||
language=language,
|
||||
use_container_width=True,
|
||||
just_once=False,
|
||||
)
|
||||
if text:
|
||||
state.text_received.append(text)
|
||||
result = ""
|
||||
for text in state.text_received:
|
||||
result += text
|
||||
state.text_received = []
|
||||
return result if result else None
|
||||
@@ -1,45 +0,0 @@
|
||||
"""Data models for website analysis results."""
|
||||
|
||||
from dataclasses import dataclass
|
||||
from typing import List, Dict, Optional
|
||||
from datetime import datetime
|
||||
|
||||
@dataclass
|
||||
class SEORecommendation:
|
||||
"""A single SEO recommendation."""
|
||||
priority: str # 'high', 'medium', 'low'
|
||||
category: str # 'content', 'technical', 'meta', etc.
|
||||
issue: str
|
||||
recommendation: str
|
||||
impact: str
|
||||
|
||||
@dataclass
|
||||
class MetaTagAnalysis:
|
||||
"""Analysis of meta tags."""
|
||||
title: Dict[str, str] # {'status': 'good', 'value': 'actual title', 'recommendation': 'suggestion'}
|
||||
description: Dict[str, str]
|
||||
keywords: Dict[str, str]
|
||||
has_robots: bool
|
||||
has_sitemap: bool
|
||||
|
||||
@dataclass
|
||||
class ContentAnalysis:
|
||||
"""Analysis of page content."""
|
||||
word_count: int
|
||||
headings_structure: Dict[str, int] # {'h1': 1, 'h2': 3, etc}
|
||||
keyword_density: Dict[str, float]
|
||||
readability_score: float
|
||||
content_quality_score: float
|
||||
|
||||
@dataclass
|
||||
class SEOAnalysisResult:
|
||||
"""Complete SEO analysis result."""
|
||||
url: str
|
||||
analyzed_at: datetime
|
||||
overall_score: float # 0-100
|
||||
meta_tags: MetaTagAnalysis
|
||||
content: ContentAnalysis
|
||||
recommendations: List[SEORecommendation]
|
||||
errors: List[str]
|
||||
warnings: List[str]
|
||||
success: bool
|
||||
Reference in New Issue
Block a user