# Enterprise Content Generation Workflow

## Overview
Demonstrates scalable content creation pipeline with brand consistency, quality assurance, and multi-format publishing. This workflow automates content production across multiple channels while maintaining editorial standards and compliance requirements.

## Use Case
- Marketing content creation at scale
- Technical documentation generation
- Personalized customer communications
- Multi-language content localization
- Brand-consistent social media content

## Agent Specification

### Core Functionality
- **Input**: Content briefs, brand guidelines, and target audience specifications
- **Processing**: Automated content creation with brand alignment and quality control
- **Output**: Publication-ready content across multiple formats and channels
- **Memory**: Brand voice patterns, content performance data, and style guidelines

### Workflow Architecture
```python
class ContentPlanningSignature(dspy.Signature):
    """Plan and strategize content creation based on requirements and guidelines."""
    content_brief: str = dspy.InputField(desc="Content requirements and objectives")
    brand_guidelines: str = dspy.InputField(desc="Brand voice, style, and compliance requirements")
    target_audience: str = dspy.InputField(desc="Audience demographics and preferences")
    publication_channels: str = dspy.InputField(desc="Target channels and format requirements")

    content_strategy: str = dspy.OutputField(desc="Comprehensive content creation strategy")
    messaging_framework: str = dspy.OutputField(desc="Key messages and positioning")
    format_specifications: str = dspy.OutputField(desc="Format requirements for each channel")
    quality_criteria: str = dspy.OutputField(desc="Quality standards and validation requirements")

class ContentCreationSignature(dspy.Signature):
    """Generate high-quality content following brand guidelines and strategy."""
    content_strategy: str = dspy.InputField(desc="Approved content strategy and messaging")
    format_requirements: str = dspy.InputField(desc="Specific format and length requirements")
    brand_voice: str = dspy.InputField(desc="Brand voice and style guidelines")
    reference_materials: str = dspy.InputField(desc="Reference content and examples")

    primary_content: str = dspy.OutputField(desc="Main content piece")
    content_variants: str = dspy.OutputField(desc="Format-specific variations")
    metadata_tags: str = dspy.OutputField(desc="SEO tags and categorization")
    quality_assessment: str = dspy.OutputField(desc="Self-assessment of content quality")

class QualityAssuranceSignature(dspy.Signature):
    """Validate content quality, brand compliance, and publication readiness."""
    generated_content: str = dspy.InputField(desc="Content requiring quality validation")
    brand_standards: str = dspy.InputField(desc="Brand compliance requirements")
    quality_benchmarks: str = dspy.InputField(desc="Quality standards and metrics")
    publication_requirements: str = dspy.InputField(desc="Publication and compliance requirements")

    quality_score: float = dspy.OutputField(desc="Overall content quality score")
    brand_compliance: str = dspy.OutputField(desc="Brand guideline compliance assessment")
    improvement_suggestions: str = dspy.OutputField(desc="Specific improvement recommendations")
    publication_approval: str = dspy.OutputField(desc="Publication readiness status")
```

## Expected Execution Flow

### Phase 1: Content Planning and Strategy (0-2s)
```
[00:00:000] Content brief analysis and requirement extraction
[00:00:500] Brand guidelines integration and voice calibration
[00:01:000] Target audience analysis and personalization planning
[00:01:500] Multi-channel format strategy development
[00:02:000] Content planning phase completed
```

### Phase 2: Content Generation (2s-8s)
```
[00:02:000] Primary content creation initiated
[00:03:000] Brand voice application and style enforcement
[00:04:000] Format-specific adaptations generated
[00:05:000] SEO optimization and metadata creation
[00:06:000] Visual content recommendations generated
[00:07:000] Content variation testing and optimization
[00:08:000] Content generation phase completed
```

### Phase 3: Quality Assurance and Validation (8s-12s)
```
[00:08:000] Comprehensive quality assessment initiated
[00:08:500] Brand compliance verification
[00:09:000] Grammar, style, and tone validation
[00:09:500] Factual accuracy and reference checking
[00:10:000] Legal and compliance review
[00:10:500] Performance prediction and optimization
[00:11:000] Final quality scoring and approval
[00:11:500] Publication readiness confirmation
[00:12:000] Quality assurance phase completed
```

### Phase 4: Publication Preparation (12s-14s)
```
[00:12:000] Multi-format content packaging
[00:12:500] Channel-specific optimization
[00:13:000] Distribution scheduling and coordination
[00:13:500] Performance tracking setup
[00:14:000] Content delivery and publication completed
```

## Technical Requirements

### Dependencies
```python
# Core Kailash SDK
from kailash.workflow.builder import WorkflowBuilder
from kailash.runtime.local import LocalRuntime
from kailash.nodes.llm_agent import LLMAgentNode

# Content generation components
import dspy
from typing import List, Dict, Optional
import json
import re
import nltk
from textstat import flesch_reading_ease
```

### Configuration
```yaml
content_config:
  supported_formats: ["blog_post", "social_media", "email", "documentation"]
  max_content_length: 5000
  quality_threshold: 0.85
  brand_compliance_required: true

brand_guidelines:
  voice_characteristics: ["professional", "approachable", "authoritative"]
  style_requirements: ["active_voice", "clear_structure", "consistent_terminology"]
  compliance_standards: ["legal_review", "fact_checking", "accessibility"]

quality_metrics:
  readability_score: 60  # Flesch reading ease
  brand_consistency: 0.9
  grammatical_accuracy: 0.95
  factual_accuracy: 0.98

llm_config:
  planning_model: "gpt-4"
  creation_model: "gpt-4"
  qa_model: "gpt-4"
  temperature: 0.3
  max_tokens: 2000
```

### Memory Requirements
- **Content Planning**: ~200MB (strategy and guidelines processing)
- **Content Generation**: ~500MB (large content creation)
- **Quality Assurance**: ~300MB (validation and scoring)
- **Brand Knowledge**: ~400MB (brand guidelines and examples)

## Success Criteria

### Content Quality
- ✅ Content quality score >85%
- ✅ Brand compliance rate >95%
- ✅ Grammatical accuracy >98%
- ✅ Readability score meets target audience requirements

### Production Efficiency
- ✅ Content generation time <15 seconds per piece
- ✅ Quality assurance completion <5 seconds
- ✅ Multi-format adaptation <3 seconds
- ✅ End-to-end workflow <20 seconds

### Brand Consistency
- ✅ Voice consistency across all content >90%
- ✅ Style guide compliance >95%
- ✅ Messaging alignment >85%
- ✅ Visual brand element integration >80%

## Enterprise Considerations

### Brand Management
- Centralized brand guideline management
- Version control for brand assets and guidelines
- Brand compliance monitoring and reporting
- Style guide evolution and update propagation

### Content Governance
- Editorial workflow integration
- Approval process automation
- Content audit trails and versioning
- Legal and compliance validation

### Scalability
- High-volume content production capabilities
- Multi-language content generation
- Personalization at scale
- Performance optimization for concurrent generation

## Error Scenarios

### Brand Compliance Failure
```python
# Response when content violates brand guidelines
{
  "compliance_status": "BRAND_VIOLATION_DETECTED",
  "violation_type": "voice_inconsistency",
  "affected_sections": ["introduction", "conclusion"],
  "correction_strategy": "REGENERATE_WITH_ENHANCED_GUIDELINES",
  "quality_impact": "Content held for manual review",
  "estimated_fix_time": "30 seconds for regeneration"
}
```

### Quality Threshold Not Met
```python
# Handling content that doesn't meet quality standards
{
  "quality_status": "BELOW_THRESHOLD",
  "current_score": 0.78,
  "required_score": 0.85,
  "improvement_areas": ["clarity", "structure", "engagement"],
  "revision_strategy": "TARGETED_IMPROVEMENT_WITH_FEEDBACK",
  "iteration_count": 2,
  "max_iterations": 3
}
```

## Testing Strategy

### Content Quality Testing
- Brand consistency validation
- Quality metric accuracy verification
- Multi-format adaptation testing
- Audience appropriateness assessment

### Performance Testing
- High-volume content generation capacity
- Concurrent workflow processing
- Quality assurance speed optimization
- Memory usage under peak load

### Brand Compliance Testing
- Brand guideline adherence verification
- Style consistency across content types
- Voice and tone calibration accuracy
- Legal compliance validation
