ALwrity Version 0.5.0 (Fastapi + React )
This commit is contained in:
ajaysi
498
lib/content_calendar/ui/components/content_optimization.py
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498
lib/content_calendar/ui/components/content_optimization.py
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import streamlit as st
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from typing import Dict, Any, List
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from datetime import datetime
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import pandas as pd
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from lib.ai_seo_tools.content_calendar.core.content_generator import ContentGenerator
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from lib.ai_seo_tools.content_calendar.core.ai_generator import AIGenerator
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from lib.ai_seo_tools.content_calendar.integrations.seo_optimizer import SEOOptimizer
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from lib.database.models import ContentItem, ContentType, Platform, SEOData
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import logging
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from lib.database.models import get_engine, get_session, init_db
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logger = logging.getLogger('content_calendar.optimization')
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engine = get_engine()
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init_db(engine)
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session = get_session(engine)
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class OptimizationManager:
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def __init__(self):
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if 'optimization_history' not in st.session_state:
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st.session_state.optimization_history = {}
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if 'optimization_previews' not in st.session_state:
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st.session_state.optimization_previews = {}
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if 'optimization_metrics' not in st.session_state:
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st.session_state.optimization_metrics = {}
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def track_optimization(self, content_id: str, optimization_data: Dict[str, Any]) -> bool:
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"""Track optimization changes for content with detailed metrics."""
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try:
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if content_id not in st.session_state.optimization_history:
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st.session_state.optimization_history[content_id] = []
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optimization_data['timestamp'] = datetime.now()
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optimization_data['metrics'] = self._calculate_optimization_metrics(optimization_data)
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st.session_state.optimization_history[content_id].append(optimization_data)
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# Update metrics
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if content_id not in st.session_state.optimization_metrics:
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st.session_state.optimization_metrics[content_id] = []
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st.session_state.optimization_metrics[content_id].append(optimization_data['metrics'])
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return True
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except Exception as e:
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logger.error(f"Error tracking optimization: {str(e)}")
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return False
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def _calculate_optimization_metrics(self, optimization_data: Dict[str, Any]) -> Dict[str, Any]:
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"""Calculate detailed optimization metrics."""
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try:
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metrics = {
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'readability_score': 0,
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'seo_score': 0,
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'engagement_potential': 0,
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'keyword_density': 0,
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'content_quality': 0
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}
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# Calculate readability score
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if 'content' in optimization_data:
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content = optimization_data['content']
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metrics['readability_score'] = self._calculate_readability(content)
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# Calculate SEO score
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if 'seo_data' in optimization_data:
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seo_data = optimization_data['seo_data']
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metrics['seo_score'] = self._calculate_seo_score(seo_data)
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metrics['keyword_density'] = self._calculate_keyword_density(seo_data)
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# Calculate engagement potential
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if 'engagement_metrics' in optimization_data:
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engagement = optimization_data['engagement_metrics']
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metrics['engagement_potential'] = self._calculate_engagement_potential(engagement)
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# Calculate overall content quality
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metrics['content_quality'] = (
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metrics['readability_score'] * 0.3 +
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metrics['seo_score'] * 0.3 +
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metrics['engagement_potential'] * 0.4
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)
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return metrics
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except Exception as e:
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logger.error(f"Error calculating optimization metrics: {str(e)}")
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return {}
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def _calculate_readability(self, content: str) -> float:
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"""Calculate content readability score."""
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try:
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# Implement readability calculation logic
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# This is a placeholder implementation
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return 0.8
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except Exception as e:
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logger.error(f"Error calculating readability: {str(e)}")
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return 0.0
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def _calculate_seo_score(self, seo_data: SEOData) -> float:
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"""Calculate SEO optimization score."""
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try:
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# Implement SEO score calculation logic
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# This is a placeholder implementation
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return 0.85
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except Exception as e:
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logger.error(f"Error calculating SEO score: {str(e)}")
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return 0.0
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def _calculate_keyword_density(self, seo_data: SEOData) -> float:
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"""Calculate keyword density."""
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try:
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# Implement keyword density calculation logic
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# This is a placeholder implementation
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return 2.5
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except Exception as e:
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logger.error(f"Error calculating keyword density: {str(e)}")
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return 0.0
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def _calculate_engagement_potential(self, engagement: Dict[str, Any]) -> float:
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"""Calculate content engagement potential."""
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try:
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# Implement engagement potential calculation logic
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# This is a placeholder implementation
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return 0.75
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except Exception as e:
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logger.error(f"Error calculating engagement potential: {str(e)}")
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return 0.0
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def get_optimization_history(self, content_id: str) -> List[Dict[str, Any]]:
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"""Get detailed optimization history for content."""
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return st.session_state.optimization_history.get(content_id, [])
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def get_optimization_metrics(self, content_id: str) -> List[Dict[str, Any]]:
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"""Get optimization metrics history."""
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return st.session_state.optimization_metrics.get(content_id, [])
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def save_preview(self, content_id: str, preview_data: Dict[str, Any]) -> bool:
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"""Save optimization preview with versioning."""
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try:
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if content_id not in st.session_state.optimization_previews:
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st.session_state.optimization_previews[content_id] = []
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preview_data['version'] = len(st.session_state.optimization_previews[content_id]) + 1
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preview_data['timestamp'] = datetime.now()
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st.session_state.optimization_previews[content_id].append(preview_data)
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return True
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except Exception as e:
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logger.error(f"Error saving preview: {str(e)}")
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return False
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def get_preview(self, content_id: str, version: int = None) -> Dict[str, Any]:
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"""Get optimization preview with optional versioning."""
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try:
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previews = st.session_state.optimization_previews.get(content_id, [])
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if not previews:
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return {}
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if version is None:
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return previews[-1]
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for preview in previews:
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if preview['version'] == version:
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return preview
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return {}
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except Exception as e:
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logger.error(f"Error getting preview: {str(e)}")
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return {}
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def render_content_optimization(
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content_generator: ContentGenerator,
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ai_generator: AIGenerator,
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seo_optimizer: SEOOptimizer
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):
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"""Render the content optimization interface with advanced features."""
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st.title("Content Calendar")
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# Initialize optimization manager
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optimization_manager = OptimizationManager()
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# Check if calendar manager is available
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if 'calendar_manager' not in st.session_state:
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st.error("Calendar manager not initialized. Please refresh the page.")
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return
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# Create main tabs
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main_tabs = st.tabs(["Content Planning", "Content Optimization"])
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with main_tabs[0]:
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# Create two columns for the layout
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col1, col2 = st.columns([1, 1])
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with col1:
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st.header("Quick Calendar Generation")
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st.markdown("""
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Generate a content calendar in three simple steps:
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1. Enter your keywords
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2. Select target platforms
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3. Choose time period
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""")
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# Step 1: Keywords Input
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st.subheader("Step 1: Enter Keywords")
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keywords = st.text_area(
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"Enter keywords or topics (one per line)",
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help="Enter the main topics or keywords you want to create content about"
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)
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# Step 2: Platform Selection
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st.subheader("Step 2: Select Target Platforms")
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platform_categories = {
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"Website": ["WEBSITE"],
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"Social Media": ["INSTAGRAM", "FACEBOOK", "TWITTER", "LINKEDIN"],
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"Video": ["YOUTUBE"],
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"Newsletter": ["NEWSLETTER"]
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}
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selected_platforms = []
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for category, platforms in platform_categories.items():
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st.markdown(f"**{category}**")
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for platform in platforms:
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if st.checkbox(platform.replace("_", " ").title(), key=f"platform_{platform}"):
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selected_platforms.append(platform)
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# Step 3: Time Period
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st.subheader("Step 3: Choose Time Period")
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time_period = st.selectbox(
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"Select time period",
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["1 Week", "2 Weeks", "1 Month", "3 Months", "6 Months"],
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help="Choose how far ahead you want to plan your content"
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)
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# Generate Calendar Button
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if st.button("Generate with AI", type="primary"):
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if not keywords or not selected_platforms:
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st.error("Please enter keywords and select at least one platform.")
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else:
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with st.spinner("Generating content calendar..."):
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try:
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# Generate content ideas based on keywords
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content_ideas = []
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for keyword in keywords.split('\n'):
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if keyword.strip():
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# Generate content ideas for each platform
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for platform in selected_platforms:
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try:
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# Create a content item for the AI generator
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content_item = ContentItem(
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title=keyword.strip(),
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description=f"Content about {keyword.strip()}",
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content_type=ContentType.BLOG_POST if platform == "WEBSITE" else ContentType.SOCIAL_MEDIA,
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platforms=[Platform[platform]],
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publish_date=datetime.now(),
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seo_data=SEOData(
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title=keyword.strip(),
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meta_description=f"Content about {keyword.strip()}",
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keywords=[keyword.strip()],
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structured_data={}
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)
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)
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# Generate content using AI generator
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content_idea = ai_generator.enhance_content(
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content=content_item,
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enhancement_type='content_generation',
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target_audience={
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'content_settings': {
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'tone': 'professional',
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'length': 'medium',
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'engagement_goal': 'awareness',
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'creativity_level': 5
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}
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}
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)
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if content_idea:
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content_ideas.append({
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'title': content_idea.get('title', keyword.strip()),
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'introduction': content_idea.get('content', f"Content about {keyword.strip()}"),
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'platform': platform,
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'meta_description': content_idea.get('meta_description', ''),
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'keywords': [keyword.strip()]
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})
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except Exception as e:
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logger.error(f"Error generating content for {keyword} on {platform}: {str(e)}")
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continue
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if content_ideas:
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# Create calendar entries
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calendar = st.session_state.calendar_manager.get_calendar()
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for idea in content_ideas:
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try:
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# Create content item
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content_item = ContentItem(
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title=idea['title'],
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description=idea['introduction'],
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content_type=ContentType.BLOG_POST if idea['platform'] == "WEBSITE" else ContentType.SOCIAL_MEDIA,
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platforms=[Platform[idea['platform']]],
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publish_date=datetime.now(),
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seo_data=SEOData(
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title=idea['title'],
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meta_description=idea.get('meta_description', ''),
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keywords=idea.get('keywords', []),
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structured_data={}
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)
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)
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calendar.add_content(content_item)
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except Exception as e:
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logger.error(f"Error adding content to calendar: {str(e)}")
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continue
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st.success("Content calendar generated successfully!")
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st.rerun() # Refresh to show new content
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else:
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st.error("Failed to generate any content ideas. Please try different keywords or settings.")
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except Exception as e:
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logger.error(f"Error generating content calendar: {str(e)}")
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st.error("An error occurred while generating the content calendar. Please try again.")
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with col2:
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st.header("Scheduled Content")
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# Get all content from calendar
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calendar = st.session_state.calendar_manager.get_calendar()
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if not calendar:
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st.info("No content scheduled yet. Generate content using the form on the left.")
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else:
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# Group content by platform
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platform_content = {}
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for item in calendar.get_all_content():
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platform = item.platforms[0].name if item.platforms else "Unknown"
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if platform not in platform_content:
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platform_content[platform] = []
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platform_content[platform].append(item)
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# Create tabs for each platform
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platform_tabs = st.tabs(list(platform_content.keys()))
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for i, (platform, content) in enumerate(platform_content.items()):
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with platform_tabs[i]:
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st.write(f"### {platform} Content")
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# Convert content to DataFrame for better display
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content_data = []
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for item in content:
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content_data.append({
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'Date': item.publish_date.strftime('%Y-%m-%d'),
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'Title': item.title,
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'Type': item.content_type.name,
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'Status': item.status
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})
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if content_data:
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df = pd.DataFrame(content_data)
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st.dataframe(df, use_container_width=True)
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# Add action buttons for each content item
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for item in content:
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with st.expander(f"Actions for: {item.title}"):
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col1, col2, col3 = st.columns(3)
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with col1:
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if st.button("Edit", key=f"edit_{item.title}"):
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st.session_state.selected_content = item.title
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with col2:
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if st.button("Optimize", key=f"optimize_{item.title}"):
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st.session_state.selected_content = item.title
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st.session_state.active_tab = "Content Optimization"
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with col3:
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if st.button("Delete", key=f"delete_{item.title}"):
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calendar.remove_content(item)
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st.success(f"Removed {item.title}")
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st.rerun()
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with main_tabs[1]:
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st.header("Content Optimization")
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# Get available content
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calendar = st.session_state.calendar_manager.get_calendar()
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if not calendar:
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st.info("No content available for optimization. Use the Content Planning tab to generate content.")
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return
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available_content = calendar.get_all_content()
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content_options = [item.title for item in available_content]
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# Content selection
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selected_content = st.selectbox(
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"Select content to optimize",
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options=content_options,
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key="optimize_content_select"
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)
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if selected_content:
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try:
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content_item = next(
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item for item in available_content
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if item.title == selected_content
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)
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# Create tabs for different optimization aspects
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opt_tabs = st.tabs(["Content Optimization", "SEO Optimization", "Preview", "History", "Analytics"])
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with opt_tabs[0]:
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st.subheader("Content Optimization")
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# Show onboarding info if no optimization history
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if not optimization_manager.get_optimization_history(content_item.title):
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st.info("""
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### Content Optimization Guide
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Use these tools to enhance your content:
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- **Content Tone**: Adjust the writing style to match your brand voice
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- **Content Length**: Optimize for your target platform's requirements
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- **Engagement Goal**: Focus on specific audience actions
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- **Creativity Level**: Balance between creative and professional content
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Click 'Generate Optimization' to get started!
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""")
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# Advanced Optimization Settings
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col1, col2 = st.columns(2)
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with col1:
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tone = st.select_slider(
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"Content Tone",
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options=["Professional", "Casual", "Educational", "Entertaining", "Persuasive"],
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value="Professional"
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)
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length = st.radio(
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"Content Length",
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["Short", "Medium", "Long"],
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horizontal=True
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)
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with col2:
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engagement_goal = st.selectbox(
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"Engagement Goal",
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["Awareness", "Consideration", "Conversion", "Retention"]
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)
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creativity_level = st.slider(
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"Creativity Level",
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min_value=1,
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max_value=10,
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value=5
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)
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if st.button("Generate Optimization", type="primary"):
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with st.spinner("Optimizing content..."):
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try:
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# Generate optimization
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optimization = content_generator.optimize_content(
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content=content_item,
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tone=tone,
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length=length,
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engagement_goal=engagement_goal,
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creativity_level=creativity_level
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)
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if optimization:
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st.success("Content optimized successfully!")
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# Show optimization results
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st.subheader("Optimization Results")
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st.write(optimization.get('content', ''))
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# Save optimization history
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optimization_manager.track_optimization(
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content_item.title,
|
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{
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'tone': tone,
|
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'length': length,
|
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'engagement_goal': engagement_goal,
|
||||
'creativity_level': creativity_level,
|
||||
'content': optimization.get('content', ''),
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'timestamp': datetime.now()
|
||||
}
|
||||
)
|
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else:
|
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st.error("Failed to optimize content. Please try again.")
|
||||
except Exception as e:
|
||||
logger.error(f"Error optimizing content: {str(e)}")
|
||||
st.error("An error occurred while optimizing content. Please try again.")
|
||||
|
||||
with opt_tabs[1]:
|
||||
st.subheader("SEO Optimization")
|
||||
# SEO optimization content here
|
||||
|
||||
with opt_tabs[2]:
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||||
st.subheader("Content Preview")
|
||||
# Content preview here
|
||||
|
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with opt_tabs[3]:
|
||||
st.subheader("Optimization History")
|
||||
# Optimization history here
|
||||
|
||||
with opt_tabs[4]:
|
||||
st.subheader("Performance Analytics")
|
||||
# Analytics content here
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error processing selected content: {str(e)}")
|
||||
st.error("Error processing selected content. Please try again.")
|
||||
|
||||
# Remove everything after this point
|
||||
Reference in New Issue
Block a user