/namesmith_agents

Domain name generation Bot

Primary LanguagePythonMIT LicenseMIT

Namesmith - Domain Research and Generation System

An intelligent multi-agent system that automates the generation, evaluation, and resale of high-quality, brandable domain names. Built using LangGraph, it orchestrates various specialized agents to perform market research, generate domain suggestions, evaluate names, and check availability.

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System Architecture

The system is built using LangGraph, a library for creating multi-agent workflows. The main orchestration logic is defined in agents/domain_research_graph.py, which coordinates the following specialized agents:

  1. Market Trends Bot (market_research_bot.py):

    • Generates a list of notable companies in various tech sectors
    • Maps company details (name, category, description, keyword, domain)
    • Analyzes current market trends using GPT-4
    • Extracts key industry patterns and naming conventions

  2. Domain Generator Bot (domain_generator.py):

    • Creates unique, brandable domain suggestions for AI SaaS B2B startups
    • Leverages market trends data for trend-aligned naming
    • Follows specific naming conventions for multiple TLDs (.com, .ai)

  3. Domain Scoring Bot (domain_name_scoring_bot.py):

    • Evaluates domains on multiple criteria (1-10 scale):
      • Memorability
      • Pronounceability
      • Length
      • Brandability
    • Provides detailed scoring rationale
    • Assigns relevant categories and keywords

  4. Availability Checker (check_domain_name_availability.py):

    • Validates domain availability via WHOISJSON API
    • Filters out registered domains
    • Updates availability status in database

  5. Database Integration:

    • Saves domain information through REST API endpoints
    • Stores domain details, availability status, and evaluation scores
    • Uses Pydantic models for data validation

Namesmith Agent Workflow

Data Models

The system uses the following data models (domain_schema.py):

  • DomainName: Basic domain information
  • DNAvailabilityStatus: Domain availability status
  • DNEvaluation: Detailed domain evaluation scores
  • DNSEOAnalysis: SEO analysis data (prepared for future implementation)
  • DomainWithDetails: Combines all domain-related information

Running Instructions

  1. Ensure you have Python 3.7+ installed

  2. Clone the repository: bash git clone <repository-url> cd <repository-directory>

  3. Install dependencies: bash pip install -r requirements.txt

  4. Set up environment variables in .env: OPENAI_API_KEY=your_openai_api_key_here WHOISJSON_API_KEY=your_whoisjson_api_key_here

  5. Run the main script: bash python main.py

API Integration

The system integrates with:

  • OpenAI API for AI-powered domain generation and evaluation
  • WHOISJSON API for domain availability checking
  • Custom REST API endpoints for database operations:
    • /api/domains: Create new domain entries
    • /api/availability-status: Store availability status
    • /api/evaluation: Store domain evaluations
    • /api/seo-analysis: Store SEO analysis (prepared for future use)

Dependencies

Main dependencies include:

  • langchain & langgraph: For workflow orchestration
  • openai: For GPT-4 integration
  • pydantic: For data validation
  • requests: For API interactions
  • python-dotenv: For environment variable management

For a complete list, see requirements.txt

Note

This system uses the OpenAI GPT-4 model and WHOISJSON API, which may incur costs. Make sure you understand the pricing and usage limits of both APIs before running the script.

Future Enhancements

The system is prepared for future enhancements including:

  • SEO analysis implementation
  • Extended domain availability checking features
  • Additional domain evaluation metrics
  • Enhanced market research capabilities