ALwrity Version 0.5.0 (Fastapi + React )
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ajaysi
340
lib/ai_seo_tools/seo_analyzer_api.py
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340
lib/ai_seo_tools/seo_analyzer_api.py
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"""
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FastAPI endpoint for the Comprehensive SEO Analyzer
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Provides data for the React SEO Dashboard
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"""
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from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel, HttpUrl
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from typing import List, Optional, Dict, Any
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from datetime import datetime
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import json
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from .comprehensive_seo_analyzer import ComprehensiveSEOAnalyzer, SEOAnalysisResult
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app = FastAPI(
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title="Comprehensive SEO Analyzer API",
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description="API for analyzing website SEO performance with actionable insights",
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version="1.0.0"
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)
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# Initialize the analyzer
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seo_analyzer = ComprehensiveSEOAnalyzer()
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class SEOAnalysisRequest(BaseModel):
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url: HttpUrl
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target_keywords: Optional[List[str]] = None
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class SEOAnalysisResponse(BaseModel):
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url: str
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timestamp: datetime
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overall_score: int
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health_status: str
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critical_issues: List[str]
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warnings: List[str]
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recommendations: List[str]
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data: Dict[str, Any]
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success: bool
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message: str
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@app.post("/analyze-seo", response_model=SEOAnalysisResponse)
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async def analyze_seo(request: SEOAnalysisRequest):
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"""
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Analyze a URL for comprehensive SEO performance
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Args:
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request: SEOAnalysisRequest containing URL and optional target keywords
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Returns:
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SEOAnalysisResponse with detailed analysis results
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"""
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try:
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# Convert URL to string
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url_str = str(request.url)
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# Perform analysis
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result = seo_analyzer.analyze_url(url_str, request.target_keywords)
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# Convert to response format
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response_data = {
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'url': result.url,
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'timestamp': result.timestamp,
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'overall_score': result.overall_score,
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'health_status': result.health_status,
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'critical_issues': result.critical_issues,
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'warnings': result.warnings,
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'recommendations': result.recommendations,
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'data': result.data,
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'success': True,
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'message': f"SEO analysis completed successfully for {result.url}"
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}
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return SEOAnalysisResponse(**response_data)
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except Exception as e:
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raise HTTPException(
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status_code=500,
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detail=f"Error analyzing SEO: {str(e)}"
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)
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@app.get("/health")
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async def health_check():
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"""Health check endpoint"""
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return {
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"status": "healthy",
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"timestamp": datetime.now(),
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"service": "Comprehensive SEO Analyzer API"
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}
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@app.get("/analysis-summary/{url:path}")
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async def get_analysis_summary(url: str):
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"""
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Get a quick summary of SEO analysis for a URL
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Args:
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url: The URL to analyze
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Returns:
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Summary of SEO analysis
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"""
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try:
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# Ensure URL has protocol
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if not url.startswith(('http://', 'https://')):
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url = f"https://{url}"
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# Perform analysis
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result = seo_analyzer.analyze_url(url)
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# Create summary
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summary = {
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"url": result.url,
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"overall_score": result.overall_score,
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"health_status": result.health_status,
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"critical_issues_count": len(result.critical_issues),
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"warnings_count": len(result.warnings),
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"recommendations_count": len(result.recommendations),
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"top_issues": result.critical_issues[:3],
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"top_recommendations": result.recommendations[:3],
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"analysis_timestamp": result.timestamp.isoformat()
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}
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return summary
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except Exception as e:
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raise HTTPException(
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status_code=500,
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detail=f"Error getting analysis summary: {str(e)}"
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)
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@app.get("/seo-metrics/{url:path}")
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async def get_seo_metrics(url: str):
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"""
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Get detailed SEO metrics for dashboard display
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Args:
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url: The URL to analyze
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Returns:
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Detailed SEO metrics for React dashboard
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"""
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try:
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# Ensure URL has protocol
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if not url.startswith(('http://', 'https://')):
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url = f"https://{url}"
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# Perform analysis
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result = seo_analyzer.analyze_url(url)
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# Extract metrics for dashboard
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metrics = {
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"overall_score": result.overall_score,
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"health_status": result.health_status,
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"url_structure_score": result.data.get('url_structure', {}).get('score', 0),
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"meta_data_score": result.data.get('meta_data', {}).get('score', 0),
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"content_score": result.data.get('content_analysis', {}).get('score', 0),
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"technical_score": result.data.get('technical_seo', {}).get('score', 0),
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"performance_score": result.data.get('performance', {}).get('score', 0),
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"accessibility_score": result.data.get('accessibility', {}).get('score', 0),
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"user_experience_score": result.data.get('user_experience', {}).get('score', 0),
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"security_score": result.data.get('security_headers', {}).get('score', 0)
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}
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# Add detailed data for each category
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dashboard_data = {
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"metrics": metrics,
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"critical_issues": result.critical_issues,
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"warnings": result.warnings,
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"recommendations": result.recommendations,
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"detailed_analysis": {
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"url_structure": result.data.get('url_structure', {}),
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"meta_data": result.data.get('meta_data', {}),
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"content_analysis": result.data.get('content_analysis', {}),
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"technical_seo": result.data.get('technical_seo', {}),
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"performance": result.data.get('performance', {}),
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"accessibility": result.data.get('accessibility', {}),
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"user_experience": result.data.get('user_experience', {}),
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"security_headers": result.data.get('security_headers', {}),
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"keyword_analysis": result.data.get('keyword_analysis', {})
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},
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"timestamp": result.timestamp.isoformat(),
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"url": result.url
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}
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return dashboard_data
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except Exception as e:
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raise HTTPException(
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status_code=500,
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detail=f"Error getting SEO metrics: {str(e)}"
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)
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@app.post("/batch-analyze")
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async def batch_analyze(urls: List[str]):
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"""
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Analyze multiple URLs in batch
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Args:
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urls: List of URLs to analyze
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Returns:
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Batch analysis results
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"""
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try:
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results = []
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for url in urls:
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try:
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# Ensure URL has protocol
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if not url.startswith(('http://', 'https://')):
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url = f"https://{url}"
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# Perform analysis
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result = seo_analyzer.analyze_url(url)
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# Add to results
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results.append({
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"url": result.url,
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"overall_score": result.overall_score,
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"health_status": result.health_status,
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"critical_issues_count": len(result.critical_issues),
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"warnings_count": len(result.warnings),
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"success": True
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})
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except Exception as e:
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# Add error result
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results.append({
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"url": url,
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"overall_score": 0,
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"health_status": "error",
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"critical_issues_count": 0,
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"warnings_count": 0,
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"success": False,
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"error": str(e)
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})
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return {
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"total_urls": len(urls),
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"successful_analyses": len([r for r in results if r['success']]),
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"failed_analyses": len([r for r in results if not r['success']]),
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"results": results
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}
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except Exception as e:
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raise HTTPException(
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status_code=500,
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detail=f"Error in batch analysis: {str(e)}"
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)
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# Enhanced prompts for better results
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ENHANCED_PROMPTS = {
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"critical_issue": "🚨 CRITICAL: This issue is severely impacting your SEO performance and must be fixed immediately.",
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"warning": "⚠️ WARNING: This could be improved to boost your search rankings.",
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"recommendation": "💡 RECOMMENDATION: Implement this to improve your SEO score.",
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"excellent": "🎉 EXCELLENT: Your SEO is performing very well in this area!",
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"good": "✅ GOOD: Your SEO is performing well, with room for minor improvements.",
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"needs_improvement": "🔧 NEEDS IMPROVEMENT: Several areas need attention to boost your SEO.",
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"poor": "❌ POOR: Significant improvements needed across multiple areas."
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}
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def enhance_analysis_result(result: SEOAnalysisResult) -> SEOAnalysisResult:
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"""
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Enhance analysis results with better prompts and user-friendly language
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"""
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# Enhance critical issues
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enhanced_critical_issues = []
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for issue in result.critical_issues:
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enhanced_issue = f"{ENHANCED_PROMPTS['critical_issue']} {issue}"
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enhanced_critical_issues.append(enhanced_issue)
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# Enhance warnings
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enhanced_warnings = []
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for warning in result.warnings:
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enhanced_warning = f"{ENHANCED_PROMPTS['warning']} {warning}"
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enhanced_warnings.append(enhanced_warning)
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# Enhance recommendations
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enhanced_recommendations = []
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for rec in result.recommendations:
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enhanced_rec = f"{ENHANCED_PROMPTS['recommendation']} {rec}"
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enhanced_recommendations.append(enhanced_rec)
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# Create enhanced result
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enhanced_result = SEOAnalysisResult(
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url=result.url,
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timestamp=result.timestamp,
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overall_score=result.overall_score,
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health_status=result.health_status,
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critical_issues=enhanced_critical_issues,
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warnings=enhanced_warnings,
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recommendations=enhanced_recommendations,
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data=result.data
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)
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return enhanced_result
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@app.post("/analyze-seo-enhanced", response_model=SEOAnalysisResponse)
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async def analyze_seo_enhanced(request: SEOAnalysisRequest):
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"""
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Analyze a URL with enhanced, user-friendly prompts
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Args:
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request: SEOAnalysisRequest containing URL and optional target keywords
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Returns:
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SEOAnalysisResponse with enhanced, user-friendly analysis results
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"""
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try:
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# Convert URL to string
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url_str = str(request.url)
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# Perform analysis
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result = seo_analyzer.analyze_url(url_str, request.target_keywords)
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# Enhance results
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enhanced_result = enhance_analysis_result(result)
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# Convert to response format
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response_data = {
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'url': enhanced_result.url,
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'timestamp': enhanced_result.timestamp,
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'overall_score': enhanced_result.overall_score,
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'health_status': enhanced_result.health_status,
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'critical_issues': enhanced_result.critical_issues,
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'warnings': enhanced_result.warnings,
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'recommendations': enhanced_result.recommendations,
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'data': enhanced_result.data,
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'success': True,
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'message': f"Enhanced SEO analysis completed successfully for {enhanced_result.url}"
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}
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return SEOAnalysisResponse(**response_data)
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except Exception as e:
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raise HTTPException(
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status_code=500,
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detail=f"Error analyzing SEO: {str(e)}"
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)
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=8000)
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