agents/programmatic_seo_agent.py

import asyncio
from typing import Dict, List, Any
from core.agent import BaseAgent
from core.models import AgentConfig, Task, AgentMessage, SEOData
import logging
import random
from datetime import datetime

logger = logging.getLogger(__name__)


class ProgrammaticSEOAgent(BaseAgent):
    """Programmatic SEO Agent responsible for creating long-tail content at scale"""
    
    def __init__(self, config: AgentConfig):
        super().__init__(config)
        self.content_templates = []
        self.long_tail_keywords = []
        self.generated_pages = []
        self.scaling_strategies = []
        
    async def execute(self):
        """Execute programmatic SEO functions"""
        logger.info(f"{self.name} executing programmatic SEO...")
        
        # Generate content templates
        await self.create_templates()
        
        # Identify long-tail keywords
        await self.find_long_tail_keywords()
        
        # Generate scalable content
        await self.generate_scalable_content()
        
        # Implement scaling strategies
        await self.implement_scaling()
    
    async def create_templates(self):
        """Create content templates for programmatic generation"""
        logger.info(f"{self.name} creating content templates...")
        
        # Simulate template creation
        templates = [
            {
                "name": "product_comparison_template",
                "structure": ["title", "intro", "feature_comparison", "pros_cons", "conclusion"],
                "variables": ["product1", "product2", "category", "features"],
                "target_keywords": ["best [product] comparison", "[product1] vs [product2]"]
            },
            {
                "name": "local_service_template",
                "structure": ["title", "intro", "services", "process", "contact"],
                "variables": ["service", "location", "business_name"],
                "target_keywords": ["[service] [location]", "[service] near me"]
            },
            {
                "name": "how_to_template",
                "structure": ["title", "intro", "steps", "tips", "faq"],
                "variables": ["task", "tools", "time"],
                "target_keywords": ["how to [task]", "[task] tutorial"]
            }
        ]
        
        self.content_templates.extend(templates)
        
        # Log template creation
        logger.info(f"Created {len(templates)} content templates")
    
    async def find_long_tail_keywords(self):
        """Identify long-tail keywords for programmatic content"""
        logger.info(f"{self.name} finding long-tail keywords...")
        
        # Simulate long-tail keyword discovery
        long_tail_keywords = [
            {"keyword": "best running shoes for flat feet 2024", "volume": 120, "difficulty": "low", "intent": "commercial"},
            {"keyword": "how to fix leaky faucet in apartment", "volume": 85, "difficulty": "low", "intent": "informational"},
            {"keyword": "affordable web design services chicago", "volume": 210, "difficulty": "medium", "intent": "commercial"},
            {"keyword": "organic dog food brands comparison", "volume": 180, "difficulty": "low", "intent": "commercial"},
            {"keyword": "beginner yoga poses for seniors", "volume": 95, "difficulty": "low", "intent": "informational"}
        ]
        
        self.long_tail_keywords.extend(long_tail_keywords)
        
        # Log keyword discovery
        logger.info(f"Found {len(long_tail_keywords)} long-tail keywords")
    
    async def generate_scalable_content(self):
        """Generate content using templates and variables"""
        logger.info(f"{self.name} generating scalable content...")
        
        # Simulate content generation using templates
        generated_content = []
        for i in range(5):  # Generate 5 sample pages
            content = {
                "title": f"Generated Page {i+1}",
                "url": f"/generated-page-{i+1}",
                "template_used": random.choice(self.content_templates)["name"],
                "target_keyword": random.choice(self.long_tail_keywords)["keyword"],
                "status": "published",
                "word_count": random.randint(800, 1500)
            }
            generated_content.append(content)
        
        self.generated_pages.extend(generated_content)
        
        # Log content generation
        logger.info(f"Generated {len(generated_content)} scalable content pages")
    
    async def implement_scaling(self):
        """Implement strategies for scaling content generation"""
        logger.info(f"{self.name} implementing scaling strategies...")
        
        # Simulate scaling strategies
        scaling_strategies = [
            {"strategy": "automated_keyword_research", "implementation": "api_integration"},
            {"strategy": "template_variety_expansion", "implementation": "new_template_creation"},
            {"strategy": "content_personalization", "implementation": "user_data_integration"},
            {"strategy": "multi_format_content", "implementation": "video_audio_transcripts"}
        ]
        
        self.scaling_strategies.extend(scaling_strategies)
        
        # Send scaling updates to SEO Director
        await self.send_message(
            recipient="seo_director",
            content=f"Scaling strategies implemented: {len(scaling_strategies)}",
            message_type="info"
        )
    
    async def _execute_task_logic(self, task: Task) -> Dict[str, Any]:
        """Execute specific task logic for Programmatic SEO agent"""
        if task.type == "create_templates":
            await self.create_templates()
            return {"status": "completed", "result": self.content_templates}
        elif task.type == "find_keywords":
            await self.find_long_tail_keywords()
            return {"status": "completed", "result": self.long_tail_keywords[:5]}  # Return first 5
        elif task.type == "generate_content":
            await self.generate_scalable_content()
            return {"status": "completed", "result": self.generated_pages}
        else:
            return {"status": "error", "message": f"Unknown task type: {task.type}"}