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🎉 OpenKeywords v1.0.0 - Initial Release

07 Dec 00:47
@federicodeponte federicodeponte
v1.0.0
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🎉 OpenKeywords v1.0.0 - Initial Release

AI-powered SEO keyword research tool using Google Gemini 2.0, deep research, and SERP analysis.

✨ What's New

Core Features

  • 🤖 AI-Powered Generation with Google Gemini 2.0 Flash
  • 🔍 Deep Research from Reddit, Quora, forums (Google Search grounding)
  • 📊 SERP Analysis with DataForSEO (snippets, PAA, AEO)
  • 🎯 Competitor Analysis via SE Ranking API
  • 🧠 Smart Clustering with semantic grouping
  • 🌍 Multilingual support (30+ languages)

What Makes It Different

  • No keyword databases - generates fresh keywords using AI + real discussions
  • Context-aware - understands intent, not just matching strings
  • Source attribution - tracks where each keyword came from
  • SERP-first - analyzes actual search results, not estimates
  • Research-backed - finds keywords from real user questions

📦 Installation

pip install openkeywords

Or from source:

git clone https://github.com/federicodeponte/openkeyword.git
cd openkeyword
pip install -e .

🚀 Quick Start

CLI Usage

# Basic generation
openkeywords generate \
  --topic "sustainable fashion" \
  --company "EcoStyle Apparel" \
  --count 50

# With deep research
openkeywords generate \
  --topic "AI automation" \
  --research \
  --serp-analysis \
  --output results.csv

Python API

from openkeywords import KeywordGenerator, CompanyInfo, GenerationConfig

# Setup
company = CompanyInfo(
    name="Your Company",
    website="https://example.com",
    description="Your business description"
)

config = GenerationConfig(
    target_language="en",
    target_country="US",
    keyword_count=50,
    enable_research=True,
    enable_serp_analysis=True
)

# Generate
generator = KeywordGenerator(gemini_api_key="YOUR_KEY")
result = await generator.generate_keywords("your topic", company, config)

# Export
result.to_csv("keywords.csv")
result.to_json("keywords.json")

📊 What You Get

Per Keyword

  • Keyword phrase
  • Search intent (informational, commercial, transactional, navigational)
  • AI relevance score (0-100)
  • Cluster assignment
  • Question detection
  • Search volume (optional, requires DataForSEO)
  • Keyword difficulty (optional, requires SE Ranking)
  • SERP features (featured snippet, PAA, related searches)
  • AEO opportunity score
  • Source attribution

Aggregate Data

  • Semantic clusters with themes
  • Intent distribution
  • Question ratio
  • Top sources
  • Domain analysis

🔧 Configuration

Requires API keys for full functionality:

# Required
export GEMINI_API_KEY="your_key"

# Optional (enables additional features)
export DATAFORSEO_LOGIN="your_login"
export DATAFORSEO_PASSWORD="your_password"
export SERANKING_API_KEY="your_key"

📚 Documentation

🎯 Use Cases

  1. Content Planning - Generate content calendars with semantic clustering
  2. SEO Research - Find gaps in competitor keyword coverage
  3. Market Research - Discover niche communities and discussions
  4. International SEO - Multi-language keyword research
  5. AEO Optimization - Identify Answer Engine opportunities

📈 Stats

  • Repository Size: 800KB (clean, no bloat)
  • Documentation: 8 comprehensive guides
  • Examples: 4 usage examples
  • Test Coverage: Comprehensive test suite
  • License: MIT (open source friendly)

🚀 What's Next

v2.0 - Content Briefs (Planned)

  • Content suggestions per keyword
  • Research quotes and citations
  • Writer instructions
  • Content gap analysis

v3.0 - Full Data Capture (Planned)

  • Complete citation library (APA/MLA/Chicago)
  • Full source URLs with metadata
  • Volume trends and seasonality
  • Historical data tracking

🙏 Credits

Developed by SCAILE Technologies

Powered by:

  • Google Gemini 2.0 for AI generation
  • DataForSEO for SERP analysis
  • SE Ranking for competitor analysis

📄 License

MIT License - See LICENSE

🐛 Issues & Feedback

Found a bug? Have a feature request?

Full Changelog: https://github.com/federicodeponte/openkeyword/commits/v1.0.0

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