135 lines
4.6 KiB
Python
135 lines
4.6 KiB
Python
"""
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SEO Optimization Agent implementation.
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"""
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from typing import Dict, Any, List, Optional
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from datetime import datetime
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from loguru import logger
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from .base import SIFBaseAgent, TXTAI_AVAILABLE, Agent
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from services.intelligence.agents.core_agent_framework import BaseALwrityAgent, TaskProposal
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from services.database import has_onboarding_session
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try:
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from services.intelligence.sif_integration import SIFIntegrationService
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SIF_AVAILABLE = True
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except ImportError:
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SIF_AVAILABLE = False
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class SEOOptimizationAgent(BaseALwrityAgent):
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"""
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Agent responsible for technical SEO, keyword strategy, and performance optimization.
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"""
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def __init__(self, user_id: str, shared_llm_name: str, llm: Any = None, **kwargs):
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super().__init__(user_id, "seo_specialist", shared_llm_name, llm, **kwargs)
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self.sif_service = None
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if SIF_AVAILABLE and has_onboarding_session(user_id):
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try:
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self.sif_service = SIFIntegrationService(user_id)
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except Exception as e:
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logger.warning(f"Failed to initialize SIF service for SEOOptimizationAgent: {e}")
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elif SIF_AVAILABLE:
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logger.debug(
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"Skipping SIF service initialization for SEOOptimizationAgent user {}: no onboarding session",
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user_id,
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)
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def _create_txtai_agent(self):
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"""Create a specialized txtai Agent for SEO optimization."""
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if not TXTAI_AVAILABLE or Agent is None:
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return None
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_llm_for_agent = getattr(self.llm, "llm", self.llm)
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return Agent(
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tools=[
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{
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"name": "seo_auditor",
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"description": "Performs comprehensive SEO audits",
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"target": self._seo_auditor_tool
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},
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{
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"name": "keyword_researcher",
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"description": "Researches high-potential keywords",
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"target": self._keyword_researcher_tool
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},
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{
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"name": "on_page_optimizer",
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"description": "Optimizes on-page elements",
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"target": self._on_page_optimizer_tool
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},
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{
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"name": "technical_fixer",
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"description": "Fixes technical SEO issues",
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"target": self._technical_fixer_tool
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}
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],
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llm=_llm_for_agent,
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max_iterations=15,
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# Removed unsupported 'system' argument
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# Instruction will be provided via orchestrator context or initial prompt
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# Instruction should be provided during invocation or via orchestrator context
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)
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# Tool Implementations
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def _seo_auditor_tool(self, context: Dict[str, Any]) -> Dict[str, Any]:
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"""
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SEO audit tool that retrieves existing SEO data via SIF.
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Args:
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context: Dictionary containing 'website_url' to audit.
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"""
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# Stub implementation
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return {"health": "good", "issues": []}
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def _keyword_researcher_tool(self, context: Dict[str, Any]) -> Dict[str, Any]:
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"""
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Keyword research tool.
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Args:
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context: Dictionary containing 'seed_keywords' or 'topic'.
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"""
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# Stub implementation
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return {"keywords": []}
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def _on_page_optimizer_tool(self, context: Dict[str, Any]) -> Dict[str, Any]:
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"""
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On-page optimization tool.
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Args:
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context: Dictionary containing 'url' and 'target_keyword'.
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"""
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# Stub implementation
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return {"optimized": True}
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def _technical_fixer_tool(self, context: Dict[str, Any]) -> Dict[str, Any]:
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"""
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Technical SEO fixer tool.
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Args:
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context: Dictionary containing 'issue_id' to fix.
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"""
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# Stub implementation
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return {"fixed": True}
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async def propose_daily_tasks(self, context: Dict[str, Any]) -> List[TaskProposal]:
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"""
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Propose SEO-focused tasks.
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"""
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proposals = []
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# 1. Quick SEO Win
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proposals.append(TaskProposal(
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title="Fix Broken Links",
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description="3 internal links on 'About Us' page are broken.",
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pillar_id="distribute",
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priority="high",
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estimated_time=10,
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source_agent="SEOOptimizationAgent",
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reasoning="Easy technical win.",
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action_type="navigate",
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action_url="/content-planning-dashboard"
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))
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return proposals
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