# MindsDB Core Implementation

This directory (`/mindsdb`) contains the core implementation of MindsDB - an AI federated query engine that follows the "Connect, Unify, Respond" philosophy to help users work with data across disparate sources using natural language and SQL.

## Architecture Overview
![image](https://github.com/user-attachments/assets/2e050a75-fed6-4ba5-9e5a-0c59ac302509)

As shown in the diagram, MindsDB's architecture is organized around its core mission of connecting to data, unifying it through various interfaces, and responding to queries via APIs. The implementation is structured around the following key components:


```

├── API Layer (RESPOND)
│   └── Exposes MindsDB functionality and handles responses
├── Core Components (UNIFY)
│   ├── Interfaces 
│   │   ├── Views - Simplify and organize data scope over federated data
│   │   ├── JOBs - Schedule and synchronize data operations
│   │   ├── Knowledge Bases - Organize unstructured data
│   │   └── ML Models - Transform data using AI/ML
│   └── Utilities - Shared code across interfaces
├── Integration Layer (CONNECT)
│   │── Datasources - Connects to various data sources and services

```

## Core Philosophy: Connect, Unify, Respond

MindsDB's architecture is built around three fundamental capabilities:

### CONNECT (Integrations)

The Integration layer is responsible for connecting MindsDB to all types of data sources:

- **Database Integrations**: Connect to SQL, NoSQL, and time-series databases
- **Vector Store Integrations**: Connect to vector databases for embeddings
- **Application Integrations**: Connect to SaaS platforms and third-party services 
- **File Integrations**: Connect to various file formats and storage systems

These integrations allow MindsDB to access data wherever it resides, forming the foundation for all other capabilities.

### UNIFY (Interfaces)

The Interfaces layer provides tools to unify and organize data from multiple sources:

- **Views**: Simplify data access by creating unified views across different data sources
- **JOBs**: Schedule data synchronization and transformation tasks for real-time data processing
- **Knowledge Bases**: Index and organize unstructured data for efficient retrieval
- **ML Models**: Apply AI/ML transformations to data for predictions and insights

These interfaces allow working with heterogeneous data as if it were unified in a single system.

### RESPOND (APIs)

The API layer enables humans, applications, and AI agents to interact with the unified data:

- **SQL API**: Process SQL queries against unified data sources
- **HTTP API**: Enable programmatic access via RESTful endpoints
- **SDK API**: Provide language-specific libraries for application integration
- **MCP Server**: Support Model Context Protocol for AI agent interactions

These APIs provide multiple ways to query and interact with the unified data ecosystem.

## Component Details

### Integrations (CONNECT)

The `/integrations` directory contains handlers that connect MindsDB to external systems:

- **Data Handlers**: Enable connections to databases and data warehouses
- **Vector Store Handlers**: Connect to vector databases for embedding storage
- **App Handlers**: Integrate with third-party applications and services
- **ML Handlers**: Connect to AI/ML frameworks and model providers

Each handler type follows a common pattern but specializes in its specific domain of integration.

### Interfaces (UNIFY)

The interfaces implemented in MindsDB serve to unify and organize data:

- **Views**: 
  - Define simplified or aggregated views of data
  - Create virtual tables spanning multiple data sources
  - Provide standardized data access patterns

- **JOBs**:
  - Schedule recurring operations on data
  - Maintain synchronized copies of data
  - Automate data transformations in near real-time

- **Knowledge Bases**:
  - Index and organize unstructured data
  - Create searchable repositories of documents
  - Enable semantic retrieval of information

- **ML Models**:
  - Apply machine learning to transform data
  - Generate predictions and insights
  - Process data using various AI techniques

### Utilities

The Utilities module contains shared code used across all interfaces:

- **Type Inference**: Code for detecting data types automatically
- **Data Preparation**: Functions for cleaning and preparing data
- **Vector Operations**: Tools for handling embeddings and vectors
- **Common Helpers**: Shared functions used throughout the codebase

### APIs (RESPOND)

The API layer provides ways to query and interact with the unified data:

- **SQL Interface**: Processes SQL statements for all operations
- **HTTP API**: Enables RESTful access to MindsDB functionality
- **Python SDK**: Provides programmatic access from Python applications
- **MCP Integration**: Implements Model Context Protocol for AI agents

## Implementation Stack

MindsDB's core implementation leverages:

- **Python**: Primary programming language
- **SQL Parser**: For processing SQL queries
- **Vector Libraries**: For embedding handling
- **HTTP/REST**: For API communications
- **Various DB Connectors**: For database integrations
- **Python SDKs**: For third-party service integration

## Directory Structure

The `/mindsdb` directory contains:

- **`/api`**: Implementation of the response layer
- **`/interfaces`**: Implementation of unification tools
- **`/utilities`**: Shared helper code
- **`/integrations`**: Connection handlers for various sources
  - `/handlers`: Base implementation of handlers
  - `/data`: Data source connections
  - `/app`: Application integrations
  - `/ml`: ML/AI framework integrations

## Development Guidelines

When working with the MindsDB codebase:

1. **New Integrations (CONNECT)**: Extend appropriate handler classes for new data sources, applications, or ML frameworks
2. **New Interfaces (UNIFY)**: Implement new tools for data unification in the interfaces layer
3. **API Enhancements (RESPOND)**: Improve the ways users and systems can interact with MindsDB

## Contributing

Contributions to MindsDB are welcome and can focus on any of the three core capabilities:

- **CONNECT**: Add new integration handlers
- **UNIFY**: Enhance data unification interfaces
- **RESPOND**: Improve API capabilities and interactions

For detailed guidance, see the [contribution guide](https://github.com/mindsdb/mindsdb/blob/main/CONTRIBUTING.md).

For comprehensive documentation, visit [MindsDB Documentation](https://docs.mindsdb.com/).
