Base code
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Kunthawat Greethong
402
backend/test/debug_step8_isolated.py
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402
backend/test/debug_step8_isolated.py
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#!/usr/bin/env python3
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"""
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Step 8 Debug Script - Isolated Testing
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=====================================
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This script tests Step 8 (Daily Content Planning) in isolation with controlled inputs
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to identify which specific parameter is causing the 'float' object has no attribute 'get' error.
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The script will:
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1. Set up Step 8 with fixed, known dictionary inputs
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2. Test the daily content generation in isolation
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3. Identify which specific parameter is coming through as a float
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4. Help pinpoint whether the issue is in weekly_theme, posting_day, platform_strategies, or other data
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"""
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import asyncio
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import sys
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import os
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import logging
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from typing import Dict, List, Any
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# Add the project root to the path
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sys.path.append(os.path.dirname(os.path.abspath(__file__)))
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# Configure logging
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
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)
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logger = logging.getLogger(__name__)
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# Import Step 8 components
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from services.calendar_generation_datasource_framework.prompt_chaining.steps.phase3.step8_daily_content_planning.step8_main import DailyContentPlanningStep
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from services.calendar_generation_datasource_framework.prompt_chaining.steps.phase3.step8_daily_content_planning.daily_schedule_generator import DailyScheduleGenerator
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def create_controlled_test_data():
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"""Create controlled test data with known types for Step 8 testing."""
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# 1. Weekly themes from Step 7 (should be list of dictionaries)
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weekly_themes = [
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{
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"title": "Week 1 Theme: AI Implementation Guide",
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"description": "Comprehensive guide on AI implementation for businesses",
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"primary_pillar": "AI and Machine Learning",
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"secondary_pillars": ["Digital Transformation", "Innovation"],
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"strategic_alignment": "high",
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"audience_alignment": "high",
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"week_number": 1,
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"content_count": 5,
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"priority": "high",
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"estimated_impact": "High",
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"ai_confidence": 0.9
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},
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{
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"title": "Week 2 Theme: Digital Transformation Strategies",
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"description": "Strategic approaches to digital transformation",
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"primary_pillar": "Digital Transformation",
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"secondary_pillars": ["Business Strategy", "Innovation"],
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"strategic_alignment": "high",
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"audience_alignment": "medium",
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"week_number": 2,
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"content_count": 4,
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"priority": "medium",
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"estimated_impact": "Medium",
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"ai_confidence": 0.8
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}
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]
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# 2. Platform strategies from Step 6 (should be dictionary)
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platform_strategies = {
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"linkedin": {
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"content_types": ["articles", "posts", "videos"],
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"posting_times": ["09:00", "12:00", "15:00"],
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"content_adaptation": "professional tone, industry insights",
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"engagement_strategy": "thought leadership content"
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},
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"twitter": {
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"content_types": ["tweets", "threads", "images"],
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"posting_times": ["08:00", "11:00", "14:00", "17:00"],
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"content_adaptation": "concise, engaging, hashtag optimization",
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"engagement_strategy": "conversation starters"
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}
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}
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# 3. Content pillars from Step 5 (should be list)
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content_pillars = [
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"AI and Machine Learning",
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"Digital Transformation",
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"Innovation and Technology Trends",
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"Business Strategy and Growth"
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]
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# 4. Calendar framework from Step 4 (should be dictionary)
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calendar_framework = {
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"duration_weeks": 4,
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"content_frequency": "daily",
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"posting_schedule": {
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"monday": ["09:00", "12:00", "15:00"],
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"tuesday": ["09:00", "12:00", "15:00"],
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"wednesday": ["09:00", "12:00", "15:00"],
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"thursday": ["09:00", "12:00", "15:00"],
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"friday": ["09:00", "12:00", "15:00"]
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},
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"theme_structure": "weekly_themes",
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"content_mix": {
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"blog_posts": 0.4,
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"social_media": 0.3,
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"videos": 0.2,
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"infographics": 0.1
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}
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}
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# 5. Business goals from Step 1 (should be list)
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business_goals = [
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"Increase brand awareness by 40%",
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"Generate 500 qualified leads per month",
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"Establish thought leadership"
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]
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# 6. Target audience from Step 1 (should be dictionary)
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target_audience = {
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"primary": "Tech professionals",
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"secondary": "Business leaders",
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"demographics": {
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"age_range": "25-45",
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"location": "Global",
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"interests": ["technology", "innovation", "business growth"]
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}
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}
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# 7. Keywords from Step 2 (should be list)
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keywords = [
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"AI implementation",
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"digital transformation",
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"machine learning",
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"business automation",
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"technology trends"
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]
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return {
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"weekly_themes": weekly_themes,
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"platform_strategies": platform_strategies,
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"content_pillars": content_pillars,
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"calendar_framework": calendar_framework,
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"business_goals": business_goals,
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"target_audience": target_audience,
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"keywords": keywords
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}
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def validate_data_types(data: Dict[str, Any], test_name: str):
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"""Validate that all data has the expected types."""
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logger.info(f"🔍 Validating data types for {test_name}")
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expected_types = {
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"weekly_themes": list,
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"platform_strategies": dict,
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"content_pillars": list,
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"calendar_framework": dict,
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"business_goals": list,
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"target_audience": dict,
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"keywords": list
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}
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for key, expected_type in expected_types.items():
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if key in data:
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actual_type = type(data[key])
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if actual_type != expected_type:
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logger.error(f"❌ Type mismatch for {key}: expected {expected_type.__name__}, got {actual_type.__name__}")
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logger.error(f" Value: {data[key]}")
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return False
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else:
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logger.info(f"✅ {key}: {actual_type.__name__} (correct)")
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else:
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logger.warning(f"⚠️ Missing key: {key}")
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return True
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async def test_daily_schedule_generator_isolated():
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"""Test the DailyScheduleGenerator in isolation with controlled inputs."""
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logger.info("🧪 Testing DailyScheduleGenerator in isolation")
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# Create controlled test data
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test_data = create_controlled_test_data()
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# Validate data types
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if not validate_data_types(test_data, "DailyScheduleGenerator"):
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logger.error("❌ Data type validation failed")
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return False
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try:
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# Create DailyScheduleGenerator instance
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generator = DailyScheduleGenerator()
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# Test the generate_daily_schedules method
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logger.info("📅 Testing generate_daily_schedules method")
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# Get posting preferences and calendar duration
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posting_preferences = {
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"preferred_times": ["09:00", "12:00", "15:00"],
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"posting_frequency": "daily"
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}
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calendar_duration = test_data["calendar_framework"]["duration_weeks"] * 7
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# Call the method with controlled inputs
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daily_schedules = await generator.generate_daily_schedules(
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test_data["weekly_themes"],
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test_data["platform_strategies"],
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test_data["content_pillars"],
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test_data["calendar_framework"],
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posting_preferences,
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calendar_duration
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)
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logger.info(f"✅ DailyScheduleGenerator test successful")
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logger.info(f" Generated {len(daily_schedules)} daily schedules")
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# Validate the output
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if isinstance(daily_schedules, list):
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logger.info("✅ Output is a list (correct)")
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for i, schedule in enumerate(daily_schedules[:3]): # Show first 3
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logger.info(f" Schedule {i+1}: {type(schedule)} - {schedule.get('day_number', 'N/A')}")
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else:
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logger.error(f"❌ Output is not a list: {type(daily_schedules)}")
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return False
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return True
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except Exception as e:
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logger.error(f"❌ DailyScheduleGenerator test failed: {str(e)}")
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logger.error(f" Exception type: {type(e).__name__}")
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import traceback
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logger.error(f" Traceback: {traceback.format_exc()}")
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return False
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async def test_step8_execute_method():
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"""Test Step 8's execute method with controlled inputs."""
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logger.info("🧪 Testing Step 8 execute method")
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# Create controlled test data
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test_data = create_controlled_test_data()
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# Validate data types
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if not validate_data_types(test_data, "Step 8 Execute"):
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logger.error("❌ Data type validation failed")
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return False
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try:
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# Create Step 8 instance
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step8 = DailyContentPlanningStep()
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# Create context with controlled data
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context = {
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"step_results": {
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"step_07": {
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"result": {
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"weekly_themes": test_data["weekly_themes"]
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}
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},
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"step_06": {
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"result": {
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"platform_strategies": test_data["platform_strategies"]
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}
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},
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"step_05": {
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"result": {
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"content_pillars": test_data["content_pillars"]
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}
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},
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"step_04": {
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"result": {
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"calendar_framework": test_data["calendar_framework"]
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}
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},
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"step_01": {
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"result": {
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"business_goals": test_data["business_goals"],
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"target_audience": test_data["target_audience"]
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}
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},
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"step_02": {
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"result": {
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"keywords": test_data["keywords"]
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}
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}
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},
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"user_data": {
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"business_goals": test_data["business_goals"],
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"target_audience": test_data["target_audience"],
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"keywords": test_data["keywords"]
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}
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}
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# Test the execute method
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logger.info("📅 Testing Step 8 execute method")
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result = await step8.execute(context)
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logger.info(f"✅ Step 8 execute test successful")
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logger.info(f" Result type: {type(result)}")
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logger.info(f" Result keys: {list(result.keys()) if isinstance(result, dict) else 'N/A'}")
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return True
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except Exception as e:
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logger.error(f"❌ Step 8 execute test failed: {str(e)}")
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logger.error(f" Exception type: {type(e).__name__}")
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import traceback
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logger.error(f" Traceback: {traceback.format_exc()}")
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return False
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async def test_specific_methods_with_debugging():
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"""Test specific methods with detailed debugging to identify the float issue."""
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logger.info("🔍 Testing specific methods with detailed debugging")
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# Create controlled test data
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test_data = create_controlled_test_data()
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try:
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# Create DailyScheduleGenerator instance
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generator = DailyScheduleGenerator()
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# Test _get_weekly_theme method specifically
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logger.info("🔍 Testing _get_weekly_theme method")
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for week_num in [1, 2]:
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theme = generator._get_weekly_theme(test_data["weekly_themes"], week_num)
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logger.info(f" Week {week_num} theme type: {type(theme)}")
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logger.info(f" Week {week_num} theme: {theme}")
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if not isinstance(theme, dict):
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logger.error(f"❌ Week {week_num} theme is not a dictionary!")
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return False
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# Test _generate_daily_content method with controlled inputs
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logger.info("🔍 Testing _generate_daily_content method")
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# Create a controlled posting_day
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posting_day = {
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"day_number": 1,
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"week_number": 1,
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"content_count": 3,
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"platforms": ["linkedin", "twitter"]
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}
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# Test with controlled weekly theme
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weekly_theme = test_data["weekly_themes"][0] # First theme
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# Test the method
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content = await generator._generate_daily_content(
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posting_day,
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weekly_theme,
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test_data["platform_strategies"],
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test_data["content_pillars"],
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test_data["calendar_framework"]
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)
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logger.info(f"✅ _generate_daily_content test successful")
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logger.info(f" Content type: {type(content)}")
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logger.info(f" Content: {content}")
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return True
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except Exception as e:
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logger.error(f"❌ Specific method test failed: {str(e)}")
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logger.error(f" Exception type: {type(e).__name__}")
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import traceback
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logger.error(f" Traceback: {traceback.format_exc()}")
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return False
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async def main():
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"""Main debug function."""
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logger.info("🚀 Starting Step 8 Debug Script")
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logger.info("=" * 50)
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# Test 1: DailyScheduleGenerator in isolation
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logger.info("\n🧪 Test 1: DailyScheduleGenerator in isolation")
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success1 = await test_daily_schedule_generator_isolated()
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# Test 2: Step 8 execute method
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logger.info("\n🧪 Test 2: Step 8 execute method")
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success2 = await test_step8_execute_method()
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# Test 3: Specific methods with debugging
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logger.info("\n🧪 Test 3: Specific methods with debugging")
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success3 = await test_specific_methods_with_debugging()
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# Summary
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logger.info("\n" + "=" * 50)
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logger.info("📊 Debug Results Summary")
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logger.info("=" * 50)
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logger.info(f"✅ Test 1 (DailyScheduleGenerator): {'PASSED' if success1 else 'FAILED'}")
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logger.info(f"✅ Test 2 (Step 8 Execute): {'PASSED' if success2 else 'FAILED'}")
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logger.info(f"✅ Test 3 (Specific Methods): {'PASSED' if success3 else 'FAILED'}")
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if success1 and success2 and success3:
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logger.info("🎉 All tests passed! Step 8 is working correctly with controlled inputs.")
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logger.info("💡 The issue might be in the data flow from previous steps.")
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else:
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logger.error("❌ Some tests failed. Check the logs above for specific issues.")
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logger.info("=" * 50)
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if __name__ == "__main__":
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asyncio.run(main())
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