README_EN.md

Coreness — Multi-tenant Platform for Automation and AI Solutions

🌐 Language: Русский | English

Note on language: The project supports English (docs, code, tooling). You may still run into occasional inaccuracies or mixed-language bits.

🌐 Website: coreness.tech · Documentation: docs.coreness.tech

Coreness is an event-driven platform for building automated workflows through configuration files. You describe the logic in YAML, and the platform handles execution, data storage, and integrations.

Key Use Cases:

• Bot Development (Telegram and other messengers)
• Business Process Automation and notifications
• AI Assistants and chatbots with LLM integration
• Scheduled Tasks and event-driven processing

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✨ Key Features

🎯 Declarative Configuration

All bot logic is defined in YAML files. Create complex scenarios, triggers, conditions, and transitions without writing code.

start:
  trigger:
    - event_type: "message"
      event_text: "/start"
  
  step:
    - action: "send_message"
      params:
        text: "Hello, {first_name}! 👋"
        inline:
          - [{"📋 Menu": "menu"}, {"ℹ️ Help": "help"}]

🏢 Built-in Multi-tenancy

Single platform instance — multiple independent bots with complete data isolation:

• Row-Level Security in PostgreSQL
• Separate configurations, scenarios, and Storage for each tenant
• GitHub synchronization for configurations (Infrastructure as Code)
• Master Bot — ready-to-use bot for tenant management (like @BotFather)

🤖 AI and RAG

Built-in integration with LLM models and vector search:

• Semantic search via pgvector (PostgreSQL)
• Support for OpenAI, Anthropic, Google, DeepSeek via aggregators (OpenRouter, Azure OpenAI)
• RAG context in scenarios — bots respond based on knowledge base
• Function calling and AI agents with tools

⏰ Scheduled Scenarios

Automation based on cron expressions:

• Daily reports
• Scheduled broadcasts
• Periodic checks and notifications

🔧 Flexibility and Extensibility

• Plugin Architecture — easily add new functionality
• Storage — flexible key-value storage for tenant settings
• Transitions — scenario flow control
• Placeholders — dynamic data in any parameters

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🚀 What's Inside

🎯 Configuration

• YAML Scenarios — all logic described declaratively without code
• Triggers — launch by events, conditions, or schedule (cron)
• 30+ Actions — send messages, AI, HTTP, validation, payments, etc.
• Placeholders — dynamic data with modifiers

🏢 Architecture

• Multi-tenancy — data isolation through Row-Level Security
• Events — event-driven architecture, loose coupling
• Storage — key-value storage for settings and states
• Plugins — extensibility through utilities and services

🤖 AI and Integrations

• AI Completion — OpenAI, Anthropic, Google, DeepSeek via aggregators (OpenRouter, Azure OpenAI)
• Embeddings — text vector representation generation via AI API
• ⭐ RAG (vector search) — saving, searching and managing embeddings via pgvector
• ⭐ Webhooks — Telegram and GitHub synchronization

🚀 Deployment

• Docker — ready configurations (test + prod)
• ...and much more

^{⭐ Additional plugins and their extensions. For more information, contact the developer}

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📖 Documentation

Online: docs.coreness.tech — full documentation in the browser.

In repo: complete documentation is also in the docs/ folder → Documentation Navigation

🚀 Getting Started

• 📖 Practical Examples — from simple bot to AI agent with RAG
• 🚀 Deployment — complete installation and update guide
• 🔧 Master Bot — tenant management system (like @BotFather)

📋 Guides

• 📋 Scenario Guide — creating bot logic
• ⚙️ Tenant Configuration — bot setup
• 💾 Attribute Storage — working with Storage

📚 Reference

• 🎯 Action Guide — reference of all available actions
• 📡 System Events — available fields in placeholders
• 🤖 AI Models — LLM integration
• 🔄 Changelog — change history and updates

🔧 Advanced Documentation

• 🏗️ Platform Architecture — detailed architecture and patterns
• 🔌 Plugin Development — creating custom services and utilities
• ⚙️ System Configuration — global platform parameters
• 📝 Logging — working with logs and debugging
• 🧪 Testing — platform testing approaches

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🏗️ Architecture

coreness/
├── app/                 # Application core
│   ├── application.py   # Entry point and orchestrator
│   └── di_container.py  # DI container
│
├── plugins/             # Plugin system
│   ├── utilities/       # Utilities
│   └── services/        # Services
│
├── config/              # Configurations
│   ├── settings.yaml    # Global settings
│   └── tenant/          # Tenant configurations
│
├── tools/               # Platform utilities
├── scripts/             # Scripts
├── tests/               # Tests
└── docker/              # Docker configuration

Principles:

• Event-Driven Architecture — loose coupling through events
• Vertical Slice Architecture — each service is self-contained
• Dependency Injection — dependency management through DI container
• Multi-tenant — data isolation through Row-Level Security

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📞 Contacts

Project website: coreness.tech
Current contacts and info

Project Telegram Channel: t.me/coreness
News, updates, and discussions

Contact the Author: @vensus137
Questions, suggestions, collaboration

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📄 License

Distributed under the MIT license.

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Coreness — Create. Automate. Scale.