ALwrity Version 0.5.1 (Fastapi + React)
This commit is contained in:
ajaysi
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import streamlit as st
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import pandas as pd
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from typing import Dict, List, Any, Optional
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from datetime import datetime, timedelta
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import logging
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from pathlib import Path
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import sys
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# Add parent directory to path to import existing tools
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parent_dir = str(Path(__file__).parent.parent.parent.parent.parent)
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if parent_dir not in sys.path:
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sys.path.append(parent_dir)
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from lib.database.models import ContentItem, ContentType, Platform, SEOData
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from lib.ai_seo_tools.content_calendar.core.content_repurposer import SmartContentRepurposingEngine
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from lib.ai_seo_tools.content_calendar.core.content_generator import ContentGenerator
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logger = logging.getLogger(__name__)
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class ContentRepurposingUI:
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"""
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Streamlit UI component for the Smart Content Repurposing Engine.
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"""
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def __init__(self):
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self.repurposing_engine = SmartContentRepurposingEngine()
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self.content_generator = ContentGenerator()
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self.logger = logging.getLogger('content_calendar.repurposing_ui')
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def render_repurposing_interface(self):
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"""Render the main repurposing interface."""
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st.header("🔄 Smart Content Repurposing Engine")
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st.markdown("Transform your content into multiple platform-optimized pieces with AI-powered repurposing.")
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# Create tabs for different repurposing functions
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tab1, tab2, tab3, tab4 = st.tabs([
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"📝 Single Content Repurposing",
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"📚 Content Series Creation",
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"🔍 Content Analysis",
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"📊 Repurposing Dashboard"
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])
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with tab1:
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self._render_single_content_repurposing()
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with tab2:
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self._render_content_series_creation()
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with tab3:
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self._render_content_analysis()
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with tab4:
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self._render_repurposing_dashboard()
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def _render_single_content_repurposing(self):
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"""Render the single content repurposing interface."""
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st.subheader("Repurpose Single Content")
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st.markdown("Transform one piece of content into multiple platform-optimized variations.")
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# Content input section
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col1, col2 = st.columns([2, 1])
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with col1:
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st.markdown("### 📄 Source Content")
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# Content input options
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input_method = st.radio(
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"How would you like to provide content?",
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["Manual Input", "Upload File", "Select from Calendar"],
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horizontal=True
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)
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source_content = None
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if input_method == "Manual Input":
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source_content = self._render_manual_content_input()
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elif input_method == "Upload File":
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source_content = self._render_file_upload_input()
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else: # Select from Calendar
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source_content = self._render_calendar_selection()
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with col2:
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st.markdown("### 🎯 Target Platforms")
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# Platform selection
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available_platforms = [
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Platform.TWITTER,
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Platform.LINKEDIN,
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Platform.INSTAGRAM,
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Platform.FACEBOOK,
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Platform.WEBSITE
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]
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selected_platforms = st.multiselect(
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"Select target platforms:",
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options=available_platforms,
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default=[Platform.TWITTER, Platform.LINKEDIN],
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format_func=lambda x: x.name.title()
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)
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# Repurposing strategy
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strategy = st.selectbox(
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"Repurposing Strategy:",
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["adaptive", "atomic", "series"],
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help="Adaptive: AI chooses best approach, Atomic: Break into small pieces, Series: Create connected content"
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)
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# Generate repurposed content
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if st.button("🚀 Generate Repurposed Content", type="primary"):
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if source_content and selected_platforms:
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with st.spinner("Repurposing content..."):
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try:
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repurposed_content = self.content_generator.repurpose_content_for_platforms(
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content_item=source_content,
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target_platforms=selected_platforms,
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strategy=strategy
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)
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if repurposed_content:
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self._display_repurposed_content(repurposed_content)
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else:
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st.error("Failed to generate repurposed content. Please try again.")
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except Exception as e:
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st.error(f"Error during repurposing: {str(e)}")
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else:
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st.warning("Please provide source content and select at least one target platform.")
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def _render_content_series_creation(self):
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"""Render the content series creation interface."""
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st.subheader("Create Cross-Platform Content Series")
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st.markdown("Generate a strategic content series that progressively reveals information across platforms.")
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# Source content input
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source_content = self._render_manual_content_input(key_suffix="_series")
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if source_content:
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col1, col2 = st.columns(2)
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with col1:
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st.markdown("### 🌐 Platform Strategy")
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# Platform selection with strategy
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platforms = st.multiselect(
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"Select platforms for series:",
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options=[Platform.TWITTER, Platform.LINKEDIN, Platform.INSTAGRAM, Platform.FACEBOOK, Platform.WEBSITE],
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default=[Platform.TWITTER, Platform.LINKEDIN, Platform.WEBSITE],
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format_func=lambda x: x.name.title(),
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key="series_platforms"
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)
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series_type = st.selectbox(
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"Series Strategy:",
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["progressive_disclosure", "platform_native"],
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help="Progressive: Gradually reveal info across platforms, Native: Optimize for each platform's strengths"
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)
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with col2:
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st.markdown("### 📅 Timeline Preview")
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if platforms:
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# Show timeline preview
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timeline_df = self._create_series_timeline_preview(source_content, platforms)
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st.dataframe(timeline_df, use_container_width=True)
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# Generate series
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if st.button("📚 Create Content Series", type="primary", key="create_series"):
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if platforms:
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with st.spinner("Creating content series..."):
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try:
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series_content = self.content_generator.create_content_series_across_platforms(
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source_content=source_content,
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platforms=platforms,
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series_type=series_type
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)
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if series_content:
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self._display_content_series(series_content)
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else:
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st.error("Failed to create content series. Please try again.")
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except Exception as e:
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st.error(f"Error creating series: {str(e)}")
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else:
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st.warning("Please select at least one platform for the series.")
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def _render_content_analysis(self):
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"""Render the content analysis interface."""
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st.subheader("Content Repurposing Analysis")
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st.markdown("Analyze your content's repurposing potential and get AI-powered recommendations.")
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# Content input
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content_to_analyze = self._render_manual_content_input(key_suffix="_analysis")
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if content_to_analyze:
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col1, col2 = st.columns([1, 1])
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with col1:
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available_platforms = st.multiselect(
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"Available platforms for analysis:",
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options=[Platform.TWITTER, Platform.LINKEDIN, Platform.INSTAGRAM, Platform.FACEBOOK, Platform.WEBSITE],
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default=[Platform.TWITTER, Platform.LINKEDIN, Platform.INSTAGRAM, Platform.FACEBOOK, Platform.WEBSITE],
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format_func=lambda x: x.name.title(),
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key="analysis_platforms"
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)
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with col2:
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if st.button("🔍 Analyze Content", type="primary"):
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if available_platforms:
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with st.spinner("Analyzing content..."):
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try:
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analysis = self.content_generator.analyze_content_for_repurposing(
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content_item=content_to_analyze,
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available_platforms=available_platforms
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)
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if analysis:
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self._display_content_analysis(analysis)
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else:
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st.error("Failed to analyze content. Please try again.")
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except Exception as e:
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st.error(f"Error during analysis: {str(e)}")
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else:
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st.warning("Please select at least one platform for analysis.")
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def _render_repurposing_dashboard(self):
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"""Render the repurposing dashboard with metrics and insights."""
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st.subheader("Repurposing Dashboard")
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st.markdown("Track your content repurposing performance and insights.")
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# Mock data for demonstration
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col1, col2, col3, col4 = st.columns(4)
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with col1:
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st.metric("Content Pieces Created", "156", "+23")
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with col2:
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st.metric("Time Saved", "312 hours", "+45 hours")
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with col3:
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st.metric("Platform Coverage", "85%", "+12%")
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with col4:
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st.metric("Engagement Boost", "34%", "+8%")
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# Recent repurposing activity
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st.markdown("### 📈 Recent Repurposing Activity")
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# Mock data for recent activity
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recent_activity = pd.DataFrame({
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'Date': ['2024-01-15', '2024-01-14', '2024-01-13', '2024-01-12'],
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'Source Content': ['AI Writing Tips', 'SEO Best Practices', 'Content Strategy Guide', 'Social Media Trends'],
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'Platforms': ['Twitter, LinkedIn', 'LinkedIn, Instagram', 'All Platforms', 'Twitter, Facebook'],
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'Pieces Created': [3, 2, 5, 2],
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'Status': ['Published', 'Scheduled', 'Draft', 'Published']
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})
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st.dataframe(recent_activity, use_container_width=True)
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# Performance insights
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st.markdown("### 💡 Performance Insights")
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insights_col1, insights_col2 = st.columns(2)
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with insights_col1:
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st.info("🎯 **Best Performing Platform**: LinkedIn posts show 45% higher engagement when repurposed from blog content.")
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with insights_col2:
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st.success("📊 **Optimization Tip**: Twitter threads perform 60% better when created from long-form content with statistics.")
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def _render_manual_content_input(self, key_suffix: str = "") -> Optional[ContentItem]:
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"""Render manual content input form."""
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with st.form(f"content_input_form{key_suffix}"):
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title = st.text_input("Content Title:", key=f"title{key_suffix}")
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content_type = st.selectbox(
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"Content Type:",
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options=[ContentType.BLOG_POST, ContentType.SOCIAL_MEDIA, ContentType.VIDEO, ContentType.NEWSLETTER],
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format_func=lambda x: x.name.replace('_', ' ').title(),
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key=f"content_type{key_suffix}"
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)
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description = st.text_area(
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"Content Description/Body:",
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height=200,
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help="Paste your content here. This will be analyzed and repurposed.",
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key=f"description{key_suffix}"
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)
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col1, col2 = st.columns(2)
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with col1:
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author = st.text_input("Author:", value="Content Creator", key=f"author{key_suffix}")
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with col2:
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tags = st.text_input("Tags (comma-separated):", key=f"tags{key_suffix}")
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submitted = st.form_submit_button("📝 Use This Content")
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if submitted and title and description:
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# Create ContentItem
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content_item = ContentItem(
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title=title,
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description=description,
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content_type=content_type,
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platforms=[],
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publish_date=datetime.now(),
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status="draft",
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author=author,
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tags=tags.split(',') if tags else [],
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notes="",
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seo_data=SEOData(title=title, meta_description="", keywords=[], structured_data={})
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)
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return content_item
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return None
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def _render_file_upload_input(self) -> Optional[ContentItem]:
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"""Render file upload input."""
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uploaded_file = st.file_uploader(
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"Upload content file:",
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type=['txt', 'md', 'docx'],
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help="Upload a text file, markdown file, or Word document"
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)
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if uploaded_file:
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try:
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# Read file content
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if uploaded_file.type == "text/plain":
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content = str(uploaded_file.read(), "utf-8")
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else:
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content = str(uploaded_file.read(), "utf-8") # Simplified for demo
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# Extract title from filename
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title = uploaded_file.name.split('.')[0].replace('_', ' ').title()
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# Create ContentItem
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content_item = ContentItem(
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title=title,
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description=content,
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content_type=ContentType.BLOG_POST,
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platforms=[],
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publish_date=datetime.now(),
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status="draft",
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author="Uploaded Content",
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tags=[],
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notes=f"Uploaded from file: {uploaded_file.name}",
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seo_data=SEOData(title=title, meta_description="", keywords=[], structured_data={})
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)
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st.success(f"✅ File uploaded: {uploaded_file.name}")
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return content_item
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except Exception as e:
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st.error(f"Error reading file: {str(e)}")
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return None
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def _render_calendar_selection(self) -> Optional[ContentItem]:
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"""Render calendar content selection."""
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st.info("📅 Calendar integration coming soon! For now, please use manual input or file upload.")
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return None
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def _display_repurposed_content(self, repurposed_content: List[ContentItem]):
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"""Display the repurposed content results."""
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st.success(f"✅ Successfully created {len(repurposed_content)} repurposed content pieces!")
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for i, content in enumerate(repurposed_content):
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with st.expander(f"📱 {content.platforms[0].name.title()} - {content.title}"):
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st.markdown(f"**Platform:** {content.platforms[0].name.title()}")
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st.markdown(f"**Content Type:** {content.content_type.name.replace('_', ' ').title()}")
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st.markdown(f"**Scheduled for:** {content.publish_date.strftime('%Y-%m-%d')}")
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st.markdown("**Content:**")
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st.write(content.description)
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if content.tags:
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st.markdown(f"**Tags:** {', '.join(content.tags)}")
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# Action buttons
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col1, col2, col3 = st.columns(3)
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with col1:
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if st.button(f"📝 Edit", key=f"edit_{i}"):
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st.info("Edit functionality coming soon!")
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with col2:
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if st.button(f"📅 Schedule", key=f"schedule_{i}"):
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st.info("Scheduling functionality coming soon!")
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with col3:
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if st.button(f"📋 Copy", key=f"copy_{i}"):
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st.code(content.description)
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def _display_content_series(self, series_content: Dict[str, List[ContentItem]]):
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"""Display the content series results."""
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total_pieces = sum(len(pieces) for pieces in series_content.values())
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st.success(f"✅ Successfully created content series with {total_pieces} pieces across {len(series_content)} platforms!")
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for platform, content_pieces in series_content.items():
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st.markdown(f"### 📱 {platform.title()} Series ({len(content_pieces)} pieces)")
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for i, content in enumerate(content_pieces):
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with st.expander(f"Part {i+1}: {content.title}"):
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st.markdown(f"**Scheduled for:** {content.publish_date.strftime('%Y-%m-%d')}")
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st.markdown("**Content:**")
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st.write(content.description)
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if content.tags:
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st.markdown(f"**Tags:** {', '.join(content.tags)}")
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def _display_content_analysis(self, analysis: Dict[str, Any]):
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"""Display content analysis results."""
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st.markdown("### 📊 Content Analysis Results")
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# Content metrics
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col1, col2, col3 = st.columns(3)
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content_analysis = analysis.get('content_analysis', {})
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with col1:
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st.metric("Word Count", content_analysis.get('word_count', 0))
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with col2:
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richness = content_analysis.get('content_richness', 'Unknown')
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st.metric("Content Richness", richness)
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with col3:
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potential = content_analysis.get('repurposing_potential', 'Unknown')
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st.metric("Repurposing Potential", potential)
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# Recommendations
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st.markdown("### 💡 Recommendations")
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col1, col2 = st.columns(2)
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with col1:
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st.markdown("**Recommended Platforms:**")
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platforms = analysis.get('platform_suggestions', [])
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for platform in platforms:
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st.write(f"• {platform.name.title()}")
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with col2:
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st.markdown("**Suggested Strategies:**")
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strategies = analysis.get('strategy_suggestions', [])
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for strategy in strategies:
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st.write(f"• {strategy.replace('_', ' ').title()}")
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# Content atoms
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st.markdown("### 🔬 Content Atoms Analysis")
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atoms = content_analysis.get('content_atoms', {})
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for atom_type, atom_list in atoms.items():
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if atom_list:
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with st.expander(f"{atom_type.title()} ({len(atom_list)} found)"):
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for atom in atom_list:
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st.write(f"• {atom}")
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# Estimated output
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estimated = analysis.get('estimated_output', {})
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if estimated:
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st.markdown("### 📈 Estimated Output")
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col1, col2, col3 = st.columns(3)
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with col1:
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st.metric("Total Pieces", estimated.get('total_pieces', 0))
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with col2:
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st.metric("Time Savings", estimated.get('time_savings', '0 hours'))
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with col3:
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st.metric("Content Multiplication", estimated.get('content_multiplication', '1x'))
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def _create_series_timeline_preview(self, content: ContentItem, platforms: List[Platform]) -> pd.DataFrame:
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"""Create a preview timeline for content series."""
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timeline_data = []
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base_date = datetime.now()
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||||
for i, platform in enumerate(platforms):
|
||||
release_date = base_date + timedelta(days=i)
|
||||
timeline_data.append({
|
||||
'Platform': platform.name.title(),
|
||||
'Release Date': release_date.strftime('%Y-%m-%d'),
|
||||
'Content Type': self._get_platform_content_type(platform),
|
||||
'Strategy': self._get_platform_strategy(platform)
|
||||
})
|
||||
|
||||
return pd.DataFrame(timeline_data)
|
||||
|
||||
def _get_platform_content_type(self, platform: Platform) -> str:
|
||||
"""Get content type for platform."""
|
||||
types = {
|
||||
Platform.TWITTER: "Thread/Tweet",
|
||||
Platform.LINKEDIN: "Professional Post",
|
||||
Platform.INSTAGRAM: "Visual Post",
|
||||
Platform.FACEBOOK: "Engaging Post",
|
||||
Platform.WEBSITE: "Blog Article"
|
||||
}
|
||||
return types.get(platform, "Standard Post")
|
||||
|
||||
def _get_platform_strategy(self, platform: Platform) -> str:
|
||||
"""Get strategy for platform."""
|
||||
strategies = {
|
||||
Platform.TWITTER: "Hook & Engage",
|
||||
Platform.LINKEDIN: "Authority Building",
|
||||
Platform.INSTAGRAM: "Visual Storytelling",
|
||||
Platform.FACEBOOK: "Community Discussion",
|
||||
Platform.WEBSITE: "Complete Information"
|
||||
}
|
||||
return strategies.get(platform, "Standard Approach")
|
||||
|
||||
# Main function to render the UI
|
||||
def render_content_repurposing_ui():
|
||||
"""Main function to render the content repurposing UI."""
|
||||
ui = ContentRepurposingUI()
|
||||
ui.render_repurposing_interface()
|
||||
|
||||
# For testing
|
||||
if __name__ == "__main__":
|
||||
render_content_repurposing_ui()
|
||||
Reference in New Issue
Block a user