Files
ALwrity/backend/api/blog_writer/seo_analysis.py

312 lines
11 KiB
Python

"""
Blog Writer SEO Analysis API Endpoint
Provides API endpoint for analyzing blog content SEO with parallel processing
and CopilotKit integration for real-time progress updates.
"""
from fastapi import APIRouter, HTTPException, BackgroundTasks, Depends
from pydantic import BaseModel
from typing import Dict, Any, Optional
from loguru import logger
from datetime import datetime
from services.blog_writer.seo.blog_content_seo_analyzer import BlogContentSEOAnalyzer
from services.blog_writer.core.blog_writer_service import BlogWriterService
from middleware.auth_middleware import get_current_user
router = APIRouter(prefix="/api/blog-writer/seo", tags=["Blog SEO Analysis"])
class SEOAnalysisRequest(BaseModel):
"""Request model for SEO analysis"""
blog_content: str
blog_title: Optional[str] = None
research_data: Dict[str, Any]
user_id: Optional[str] = None
session_id: Optional[str] = None
class SEOAnalysisResponse(BaseModel):
"""Response model for SEO analysis"""
success: bool
analysis_id: str
overall_score: float
category_scores: Dict[str, float]
analysis_summary: Dict[str, Any]
actionable_recommendations: list
detailed_analysis: Optional[Dict[str, Any]] = None
visualization_data: Optional[Dict[str, Any]] = None
generated_at: str
error: Optional[str] = None
class SEOAnalysisProgress(BaseModel):
"""Progress update model for real-time updates"""
analysis_id: str
stage: str
progress: int
message: str
timestamp: str
# Initialize analyzer
seo_analyzer = BlogContentSEOAnalyzer()
blog_writer_service = BlogWriterService()
@router.post("/analyze", response_model=SEOAnalysisResponse)
async def analyze_blog_seo(
request: SEOAnalysisRequest,
current_user: Dict[str, Any] = Depends(get_current_user)
):
"""
Analyze blog content for SEO optimization
This endpoint performs comprehensive SEO analysis including:
- Content structure analysis
- Keyword optimization analysis
- Readability assessment
- Content quality evaluation
- AI-powered insights generation
Args:
request: SEOAnalysisRequest containing blog content and research data
current_user: Authenticated user from middleware
Returns:
SEOAnalysisResponse with comprehensive analysis results
"""
try:
logger.info(f"Starting SEO analysis for blog content")
# Extract Clerk user ID (required)
if not current_user:
raise HTTPException(status_code=401, detail="Authentication required")
user_id = str(current_user.get('id', ''))
if not user_id:
raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
# Validate request
if not request.blog_content or not request.blog_content.strip():
raise HTTPException(status_code=400, detail="Blog content is required")
if not request.research_data:
raise HTTPException(status_code=400, detail="Research data is required")
# Generate analysis ID
import uuid
analysis_id = str(uuid.uuid4())
# Perform SEO analysis
analysis_results = await seo_analyzer.analyze_blog_content(
blog_content=request.blog_content,
research_data=request.research_data,
blog_title=request.blog_title,
user_id=user_id
)
# Check for errors
if 'error' in analysis_results:
logger.error(f"SEO analysis failed: {analysis_results['error']}")
return SEOAnalysisResponse(
success=False,
analysis_id=analysis_id,
overall_score=0,
category_scores={},
analysis_summary={},
actionable_recommendations=[],
detailed_analysis=None,
visualization_data=None,
generated_at=analysis_results.get('generated_at', ''),
error=analysis_results['error']
)
# Return successful response
return SEOAnalysisResponse(
success=True,
analysis_id=analysis_id,
overall_score=analysis_results.get('overall_score', 0),
category_scores=analysis_results.get('category_scores', {}),
analysis_summary=analysis_results.get('analysis_summary', {}),
actionable_recommendations=analysis_results.get('actionable_recommendations', []),
detailed_analysis=analysis_results.get('detailed_analysis'),
visualization_data=analysis_results.get('visualization_data'),
generated_at=analysis_results.get('generated_at', '')
)
except HTTPException:
raise
except Exception as e:
logger.error(f"SEO analysis endpoint error: {e}")
raise HTTPException(status_code=500, detail=f"SEO analysis failed: {str(e)}")
@router.post("/analyze-with-progress")
async def analyze_blog_seo_with_progress(
request: SEOAnalysisRequest,
current_user: Dict[str, Any] = Depends(get_current_user)
):
"""
Analyze blog content for SEO with real-time progress updates
This endpoint provides real-time progress updates for CopilotKit integration.
It returns a stream of progress updates and final results.
Args:
request: SEOAnalysisRequest containing blog content and research data
current_user: Authenticated user from middleware
Returns:
Generator yielding progress updates and final results
"""
try:
logger.info(f"Starting SEO analysis with progress for blog content")
# Extract Clerk user ID (required)
if not current_user:
raise HTTPException(status_code=401, detail="Authentication required")
user_id = str(current_user.get('id', ''))
if not user_id:
raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
# Validate request
if not request.blog_content or not request.blog_content.strip():
raise HTTPException(status_code=400, detail="Blog content is required")
if not request.research_data:
raise HTTPException(status_code=400, detail="Research data is required")
# Generate analysis ID
import uuid
analysis_id = str(uuid.uuid4())
# Yield progress updates
async def progress_generator():
try:
# Stage 1: Initialization
yield SEOAnalysisProgress(
analysis_id=analysis_id,
stage="initialization",
progress=10,
message="Initializing SEO analysis...",
timestamp=datetime.utcnow().isoformat()
)
# Stage 2: Keyword extraction
yield SEOAnalysisProgress(
analysis_id=analysis_id,
stage="keyword_extraction",
progress=20,
message="Extracting keywords from research data...",
timestamp=datetime.utcnow().isoformat()
)
# Stage 3: Non-AI analysis
yield SEOAnalysisProgress(
analysis_id=analysis_id,
stage="non_ai_analysis",
progress=40,
message="Running content structure and readability analysis...",
timestamp=datetime.utcnow().isoformat()
)
# Stage 4: AI analysis
yield SEOAnalysisProgress(
analysis_id=analysis_id,
stage="ai_analysis",
progress=70,
message="Generating AI-powered insights...",
timestamp=datetime.utcnow().isoformat()
)
# Stage 5: Results compilation
yield SEOAnalysisProgress(
analysis_id=analysis_id,
stage="compilation",
progress=90,
message="Compiling analysis results...",
timestamp=datetime.utcnow().isoformat()
)
# Perform actual analysis
analysis_results = await seo_analyzer.analyze_blog_content(
blog_content=request.blog_content,
research_data=request.research_data,
blog_title=request.blog_title,
user_id=user_id
)
# Final result
yield SEOAnalysisProgress(
analysis_id=analysis_id,
stage="completed",
progress=100,
message="SEO analysis completed successfully!",
timestamp=datetime.utcnow().isoformat()
)
# Yield final results (can't return in async generator)
yield analysis_results
except Exception as e:
logger.error(f"Progress generator error: {e}")
yield SEOAnalysisProgress(
analysis_id=analysis_id,
stage="error",
progress=0,
message=f"Analysis failed: {str(e)}",
timestamp=datetime.utcnow().isoformat()
)
raise
return progress_generator()
except HTTPException:
raise
except Exception as e:
logger.error(f"SEO analysis with progress endpoint error: {e}")
raise HTTPException(status_code=500, detail=f"SEO analysis failed: {str(e)}")
@router.get("/analysis/{analysis_id}")
async def get_analysis_result(analysis_id: str):
"""
Get SEO analysis result by ID
Args:
analysis_id: Unique identifier for the analysis
Returns:
SEO analysis results
"""
try:
# In a real implementation, you would store results in a database
# For now, we'll return a placeholder
logger.info(f"Retrieving SEO analysis result for ID: {analysis_id}")
return {
"analysis_id": analysis_id,
"status": "completed",
"message": "Analysis results retrieved successfully"
}
except Exception as e:
logger.error(f"Get analysis result error: {e}")
raise HTTPException(status_code=500, detail=f"Failed to retrieve analysis result: {str(e)}")
@router.get("/health")
async def health_check():
"""Health check endpoint for SEO analysis service"""
return {
"status": "healthy",
"service": "blog-seo-analysis",
"timestamp": datetime.utcnow().isoformat()
}