SEO Article Generator

Automate SEO-optimized content creation with AI-powered keyword research, competitive analysis, and structured article generation. Streamline content production from keyword discovery to publish-ready articles.

Features

Keyword Research Integration: DataForSEO API for volume, CPC, and competition metrics
Competitive Analysis: Automated content scraping and gap analysis
Topic Generation: AI-powered topic suggestions based on keyword data
Content Creation: Full article generation with SEO optimization
Real-time Processing: Live streaming of content generation progress

Architecture Overview

The content generation process follows a four-stage pipeline:

Business Analysis → Keyword Research → Topic Generation → Article Creation

Processing Pipeline

Stage 1: Business Context Analysis

Analyze the target website to understand business focus, audience, and content style.

Stage 2: Keyword Research

Research and validate keywords using DataForSEO API for search volume and competition data.

Stage 3: Topic Development

Generate SEO-optimized topic suggestions based on keyword opportunities and competitive gaps.

Stage 4: Article Generation

Create comprehensive articles with proper SEO structure, internal linking, and calls-to-action.

Implementation

Business Summary Generation

def generate_business_summary(website_url):
    # 1. Validate URL accessibility
    url_checker = URLCheckerService()
    if not url_checker.is_reachable(website_url):
        raise URLNotAccessibleError(website_url)
    
    # 2. Extract website content
    scraped_content = scrape_url_content(website_url)
    
    # 3. Initialize LLM for analysis
    llm = initialize_llm(model="gpt-4")
    
    # 4. Generate business summary
    prompts = create_business_analysis_prompts()
    chain = create_analysis_chain(llm, prompts)
    
    summary = chain.run(scraped_content)
    return summary

Keyword Research Workflow

def research_keywords(domain, seed_keywords):
    # 1. Initialize DataForSEO client
    dataforseo_client = DataForSEOClient()
    
    # 2. Get keyword suggestions
    keyword_suggestions = dataforseo_client.get_keyword_ideas(
        keywords=seed_keywords,
        location="United States",
        language="en"
    )
    
    # 3. Analyze keyword metrics
    keyword_data = []
    for keyword in keyword_suggestions:
        metrics = dataforseo_client.get_keyword_metrics(keyword)
        keyword_data.append({
            'keyword': keyword,
            'search_volume': metrics['search_volume'],
            'competition': metrics['competition_level'],
            'cpc': metrics['cost_per_click'],
            'difficulty': metrics['keyword_difficulty']
        })
    
    return sorted(keyword_data, key=lambda x: x['search_volume'], reverse=True)

Article Generation Process

def generate_seo_article(topic, keywords, business_context):
    # 1. Research competitor content
    competitor_articles = fetch_competitor_content(keywords)
    
    # 2. Initialize content generation chain
    llm = initialize_llm(model="gpt-4")
    memory = initialize_memory()
    
    # 3. Create article generation prompts
    prompts = create_article_prompts(
        topic=topic,
        target_keywords=keywords,
        business_context=business_context,
        competitor_insights=competitor_articles
    )
    
    # 4. Generate article sections
    article_chain = create_content_chain(llm, prompts, memory)
    
    # Stream article generation
    for section in article_chain.stream():
        yield section
    
    return article_chain.get_final_output()

API Reference

Business Summary Endpoint

POST /pro-agent/business-summary

Request Body

{
  "websiteUrl": "https://example.com",
  "analysisDepth": "comprehensive",
  "focusAreas": ["products", "target_audience", "brand_voice"]
}

Response Format

{
  "summary": {
    "businessType": "E-commerce Platform",
    "targetAudience": "Small to medium businesses",
    "keyProducts": ["Inventory Management", "Point of Sale"],
    "brandVoice": "Professional, approachable, solution-focused",
    "contentThemes": ["efficiency", "growth", "automation"]
  },
  "metadata": {
    "processingTime": "8s",
    "pagesAnalyzed": 5,
    "contentLength": 12500
  }
}

Keyword Research Endpoint

GET /pro-agent/keyword-research

Query Parameters

domain: Target domain for research
seedKeywords: Comma-separated list of seed keywords
location: Geographic location for search data
limit: Maximum number of keywords to return

Response Format

{
  "keywords": [
    {
      "keyword": "inventory management software",
      "searchVolume": 8100,
      "competition": "medium",
      "cpc": 12.45,
      "difficulty": 65,
      "trend": "stable",
      "relatedKeywords": [
        "warehouse management system",
        "stock control software"
      ]
    }
  ],
  "totalKeywords": 150,
  "processingTime": "12s"
}

Topic Generation Endpoint

POST /pro-agent/topic-generation

Request Body

{
  "primaryKeyword": "inventory management software",
  "secondaryKeywords": ["warehouse management", "stock control"],
  "businessContext": "B2B SaaS platform targeting SMEs",
  "contentType": "informational",
  "targetLength": "long-form"
}

Response Format

{
  "topics": [
    {
      "title": "Complete Guide to Inventory Management Software for Small Businesses",
      "angle": "Comprehensive educational guide",
      "targetKeywords": ["inventory management software", "small business"],
      "estimatedDifficulty": "medium",
      "contentOutline": [
        "What is Inventory Management Software?",
        "Key Features to Look For",
        "Implementation Best Practices",
        "ROI and Cost Analysis"
      ]
    }
  ],
  "competitorGaps": [
    "Lack of SME-specific implementation guides",
    "Limited cost comparison content"
  ]
}

Article Generation Endpoint

POST /pro-agent/article-generation

Request Body

{
  "topic": {
    "title": "Complete Guide to Inventory Management Software",
    "targetKeywords": ["inventory management", "warehouse software"],
    "contentType": "guide"
  },
  "requirements": {
    "wordCount": 2500,
    "includeImages": true,
    "internalLinks": 3,
    "callsToAction": 2
  },
  "businessContext": {
    "companyName": "StockWise",
    "products": ["Inventory Pro", "Warehouse Manager"],
    "targetAudience": "SME operations managers"
  }
}

Response Format (Streaming)

data: {"type": "section", "title": "Introduction", "content": "Effective inventory management..."}
data: {"type": "section", "title": "Key Features", "content": "Modern inventory systems..."}
data: {"type": "meta", "wordCount": 2487, "readabilityScore": 68}
data: {"type": "complete", "articleId": "art_12345"}

Core Components

Component	Purpose
URLCheckerService	Website accessibility validation
DataForSEO Client	Keyword metrics and search data
Content Scraper	Competitor content extraction
LLM Chain	Content generation and optimization
Topic Validator	Topic uniqueness and SEO potential
Article Formatter	SEO structure and formatting

Configuration

Keyword Research Settings

{
  "dataforseo": {
    "apiKey": "your-dataforseo-key",
    "location": "2840",
    "language": "en",
    "maxKeywords": 1000,
    "includeRelated": true
  },
  "filtering": {
    "minSearchVolume": 100,
    "maxDifficulty": 80,
    "excludeQuestions": false
  }
}

Content Generation Parameters

{
  "generation": {
    "model": "gpt-4",
    "maxTokens": 4000,
    "temperature": 0.7,
    "structure": {
      "introduction": 150,
      "mainSections": 4,
      "wordsPerSection": 400,
      "conclusion": 100
    }
  },
  "seo": {
    "keywordDensity": 1.5,
    "headingStructure": "h1-h2-h3",
    "metaDescriptionLength": 155,
    "internalLinks": 3
  }
}

Usage Examples

Complete Article Generation Workflow

# 1. Generate business summary
curl -X POST /pro-agent/business-summary \
  -H "Content-Type: application/json" \
  -d '{"websiteUrl": "https://stockwise.com"}'

# 2. Research keywords
curl -X GET "/pro-agent/keyword-research?domain=stockwise.com&seedKeywords=inventory,warehouse"

# 3. Generate topic
curl -X POST /pro-agent/topic-generation \
  -H "Content-Type: application/json" \
  -d '{
    "primaryKeyword": "inventory management software",
    "businessContext": "B2B SaaS for SMEs"
  }'

# 4. Create article
curl -X POST /pro-agent/article-generation \
  -H "Content-Type: application/json" \
  -d '{
    "topic": {
      "title": "Complete Inventory Management Guide",
      "targetKeywords": ["inventory software", "warehouse management"]
    }
  }'

Python Integration

import requests

class SEOArticleGenerator:
    def __init__(self, api_key):
        self.api_key = api_key
        self.base_url = "https://api.example.com"
    
    def generate_article(self, website_url, target_keyword):
        # 1. Business analysis
        business_data = self.analyze_business(website_url)
        
        # 2. Keyword research
        keywords = self.research_keywords(website_url, target_keyword)
        
        # 3. Topic generation
        topic = self.generate_topic(keywords[0], business_data)
        
        # 4. Article creation
        article = self.create_article(topic, keywords, business_data)
        
        return article
    
    def analyze_business(self, url):
        response = requests.post(f"{self.base_url}/pro-agent/business-summary", 
                               json={"websiteUrl": url})
        return response.json()
    
    def research_keywords(self, domain, seed_keyword):
        response = requests.get(f"{self.base_url}/pro-agent/keyword-research",
                              params={"domain": domain, "seedKeywords": seed_keyword})
        return response.json()["keywords"]

# Usage
generator = SEOArticleGenerator("your-api-key")
article = generator.generate_article("https://example.com", "inventory software")

Performance & Limits

Processing Metrics

Business Analysis: 5-15 seconds per website
Keyword Research: 10-30 seconds for 100 keywords
Topic Generation: 3-8 seconds per topic
Article Creation: 45-90 seconds for 2000-word articles

Rate Limits

API Requests: 100 requests per hour per API key
DataForSEO Calls: Limited by DataForSEO subscription
Content Generation: 20 articles per day per account

Content Specifications

Article Length: 500-5000 words
Keyword Density: 1-3% for target keywords
Reading Level: Flesch score 60-80 (accessible)
SEO Structure: H1, H2, H3 hierarchy with keyword optimization

Error Handling

Common Error Responses

Status Code	Error Type	Description	Solution
`400`	`INVALID_WEBSITE_URL`	Website URL inaccessible or invalid	Verify URL format and website accessibility
`429`	`KEYWORD_QUOTA_EXCEEDED`	DataForSEO API limit reached	Upgrade DataForSEO plan or wait for reset
`422`	`INSUFFICIENT_CONTENT`	Website lacks adequate content for analysis	Provide alternative content sources
`500`	`GENERATION_FAILED`	Article generation pipeline error	Retry with simplified requirements

Error Response Format

{
  "error": {
    "code": "KEYWORD_QUOTA_EXCEEDED",
    "message": "DataForSEO API quota exceeded",
    "details": {
      "quotaUsed": 950,
      "quotaLimit": 1000,
      "resetDate": "2024-02-01T00:00:00Z"
    }
  }
}

Integration Guide

Authentication

All requests require API key authentication:

curl -H "Authorization: Bearer your-api-key"

Webhook Configuration

Configure webhooks for content completion:

{
  "webhookUrl": "https://your-app.com/content-ready",
  "events": ["article.completed", "keyword.research.completed"]
}

Content Quality Controls

Generated articles include:

SEO Optimization: Proper keyword placement and density
Readability: Target Flesch score of 60-80
Structure: Logical H1-H6 heading hierarchy
Internal Linking: Strategic links to related content
Meta Elements: Optimized title tags and descriptions
Content Guidelines: Brand voice and style consistency

Overview

Setup

Your Account

Features

Pro Agents

Policies

​Features

​Architecture Overview

​Processing Pipeline

​Stage 1: Business Context Analysis

​Stage 2: Keyword Research

​Stage 3: Topic Development

​Stage 4: Article Generation

​Implementation

​Business Summary Generation

​Keyword Research Workflow

​Article Generation Process

​API Reference

​Business Summary Endpoint

​Keyword Research Endpoint

​Topic Generation Endpoint

​Article Generation Endpoint

​Core Components

​Configuration

​Keyword Research Settings

​Content Generation Parameters

​Usage Examples

​Complete Article Generation Workflow

​Python Integration

​Performance & Limits

​Processing Metrics

​Rate Limits

​Content Specifications

​Error Handling

​Common Error Responses

​Error Response Format

​Integration Guide

​Authentication

​Webhook Configuration

​Content Quality Controls

Features

Architecture Overview

Processing Pipeline

Stage 1: Business Context Analysis

Stage 2: Keyword Research

Stage 3: Topic Development

Stage 4: Article Generation

Implementation

Business Summary Generation

Keyword Research Workflow

Article Generation Process

API Reference

Business Summary Endpoint

Keyword Research Endpoint

Topic Generation Endpoint

Article Generation Endpoint

Core Components

Configuration

Keyword Research Settings

Content Generation Parameters

Usage Examples

Complete Article Generation Workflow

Python Integration

Performance & Limits

Processing Metrics

Rate Limits

Content Specifications

Error Handling

Common Error Responses

Error Response Format

Integration Guide

Authentication

Webhook Configuration

Content Quality Controls