MakerAI 3.0 Suite — The AI Operating System for Delphi

🌐 Official Website: https://makerai.cimamaker.com

MakerAI 3.0 is not just a component suite — it's a complete AI orchestration framework for Delphi developers.

With full support for RAG, MCP, autonomous agents, and graph-based orchestration, you can design and deploy intelligent, self-learning, and context-aware systems natively in Delphi.

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The Power of MakerAI 3.0: The AI Orchestration Platform

MakerAI 3.0 provides the architecture to manage the entire lifecycle of complex AI applications, acting as the operating system for intelligence within your software.

• 🚀 Orchestrate Autonomous Agents: Create powerful agents that manage state, utilize advanced Semantic Memory, and execute complex workflows defined by the internal graph engine.
• 🧠 RAG Engine 2.0 (Knowledge & Context): Connect AI to your private data with the robust Retrieval-Augmented Generation (RAG) V2.0 engine, supporting massive indexing, multi-model environments, and hybrid embeddings.
• 🛠️ Enjoy 100% Native Performance: MakerAI is pure Delphi. This ensures optimal performance, seamless integration, and compilation without heavy external dependencies across all supported Delphi versions (10.3 to 12 Athens).
• 🌐 Universal LLM Connectivity (AiConnection V3): The unified connector, TAiConnection, features enhanced connectivity and stability for seamless integration with OpenAI, Gemini, Claude, Ollama, Groq, and many more.
• 🏗️ Enterprise-Grade Architecture: Ideal foundation for integrating AI into mission-critical systems like ERP, CRM, LMS, and industrial solutions.

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✨ Key Features (Version 3.0 Modules)

MakerAI 3.0 introduces next-generation features focused on complexity and reliability.

🧠 RAG (Retrieval-Augmented Generation) Engine 2.0

The completely overhauled RAG engine allows the language models to use your private knowledge with unprecedented precision.

• Massive Indexing: Efficiently index millions of documents for enterprise-scale applications.
• Hybrid Embeddings: Utilize a combination of sparse and dense vectors for superior search relevance.
• Multi-Model Support: Seamlessly integrate RAG across different LLM backends (OpenAI, Gemini, Ollama, etc.).

💾 Advanced Semantic Memory

• Unified Memory Model: New semantic memory layer deeply integrated with the RAG engine and the Workflow Graphs, allowing agents to form personalized, long-term context that transcends single conversations.
• Short and Long-Term Recall: Equip agents with the ability to recall specific past interactions and generalize long-term learnings.

🔄 Workflow Engine (Graphs) & Agents

• Visual and Code-Based Orchestration: Define complex logical flows by connecting nodes and edges. Agents follow this defined logic, utilizing memory and tools to achieve goals.

📞 MakerAI Tools System (Function Calling)

• Unified Tool Management: A standardized and improved system for defining and exposing native Delphi functions (Tools) to the language model, enabling the AI to interact with your application's core logic (e.g., querying databases, sending commands).

🗣️ Voice Monitoring & Progressive Transcription

• Activation Commands: Integrated support for "wake-word" detection.
• Live Transcription: Progressive audio transcription, ideal for real-time applications and low-latency interaction.

🎨 Professional Visual Components (ChatUI)

• Chat UI: Professional-grade, easy-to-use visual components for quickly building multimedia-integrated chat interfaces (text, images, audio, video).

🔌 MCP (Model Context Protocol) Support

• Native MCP Client & Server: Connect to or expose your Delphi application functions as standard MCP tools, ensuring seamless interoperability with other platforms.

🌐 Universal LLM Connector (AiConnection V3)

• Enhanced Connectivity: Improved performance and stability for accessing all major providers (OpenAI, Gemini, Claude, Groq, Ollama, Mistral).
• Native Multimodal Support: Process and generate text, images, and audio seamlessly.

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🛠️ MakerAI 3.0 Core Modules & Components

The suite is composed of non-visual and visual components designed for maximum modularity and ease of integration into the Delphi environment.

🌐 Universal Connectivity & LLMs (AiConnection V3)

Component	Description
TAIChatConnections	Unified universal connector for managing messages, contexts, and sessions with any LLM provider.
TAIChatOpenAi	Driver for OpenAI (GPT-3.5, GPT-4, DALL-E).
TAIChatClaude	Driver for Anthropic Claude.
TAIChatGemini	Driver for Google Gemini.
TAIChatGrok	Driver for xAI Grok.
TAIChatMistral	Driver for Mistral AI.
TAIChatOllama	Driver for local and open-source models via Ollama.
TAIChatDeepSeek	Driver for DeepSeek AI.
TAIChatGroq	Driver for Groq (high-speed processing).

🧠 Knowledge & Memory Engines (RAG)

Component	Description
RAGVector	Vector and embedding-based Retrieval Augmented Generation (RAG) system. Ideal for massive indexing of unstructured documents.
RAGGraph	Graph-based RAG system for context retrieval based on graph database structure and relationships.
GraphDB	Component for administering and querying the graph-based knowledge database (for relational knowledge).

🚀 Autonomous Agents & Workflow Orchestration

Component	Description
TAiAgentManager	The central orchestration engine that manages the lifecycle and execution of workflows and agents.
TAiAgent	Defines an autonomous unit capable of managing state, memory, and executing complex tasks within the workflow.
TAiAgentNode	Represents a specific step or task within a workflow.
TAiAgentLink	Defines the logical connections and transitions between workflow nodes (tasks).
Benefits	Eliminates multitasking complexity, simplifies debugging, and ensures workflow extensibility.

📞 Tools & Protocol (Function Calling / MCP)

Component	Description
TAIFunctions	Enables and manages the Function Calling system for the LLM to interact with native Delphi functions.
MCP Client	Client implementation within TAIFunctions to consume functions from other MCP servers.
MCPServer	Dedicated server to expose Delphi application functions as standardized tools via HTTP or StdIO.

🎨 User Interface & Multimedia

Component	Description
VoiceMonitor	Engine for real-time voice processing, including wake-word detection and progressive transcription.
ChatInput	Visual component for text and multimedia input in chat interfaces.
ChatList	Visual component acting as the main container to display conversation history.
Bubbles	Specialized visual components for rendering chat messages (text, images, videos) with a professional format.

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📦 Detailed Installation Guide (Modular V3.0)

Follow these steps carefully to ensure a correct installation of the four core packages in the Delphi IDE.

Step 1: Get the Source Code

Clone the repository using Git (recommended) or download the ZIP file from GitHub.

git clone https://github.com/gustavoeenriquez/MakerAi.git

Unzip the file to a folder of your choice. For example: C:\Delphi\MakerAI.

Step 2: Configure Paths in the Delphi IDE

This is a crucial step. You must tell the Delphi IDE where to find the MakerAI source files.

1. Open your Delphi IDE (10.3 Rio, 10.4 Sydney, 11 Alexandria, or 12 Athens).
2. Go to the menu: Tools > Options....
3. In the Options dialog, navigate to Language > Delphi > Library.
4. Ensure you have the correct platform selected (e.g., Windows 32-bit). You will need to repeat this step for each platform you intend to use.
5. Click the ... button next to the "Library path" field.
6. In the new window, add the path to each of the subfolders inside the MakerAI Source directory:

...\MakerAi\Source\Agents
...\MakerAi\Source\Chat
...\MakerAi\Source\ChatUI       <-- NEW (Visual Components)
...\MakerAi\Source\Core
...\MakerAi\Source\Design
...\MakerAi\Source\MCPClient
...\MakerAi\Source\MCPServer
...\MakerAi\Source\Packages
...\MakerAi\Source\RAG
...\MakerAi\Source\Resources    <-- NEW (Resources)
...\MakerAi\Source\Tools
...\MakerAi\Source\Utils

Tip: Add the full path to each of these folders to prevent compilation issues.

7. Click OK and then Save to store the configuration.

Step 3: Compile and Install the Packages

MakerAI 3.0 is built on a modular architecture using four packages. You must compile and install them in the correct order.

1. In Delphi, go to File > Open Project....
2. Navigate to the folder where you cloned the repository and open the project group file: ...\MakerAi\Source\Packages\MakerAI.groupproj.

Compile and Install Runtime Packages:

3. Right-click on MakerAi.dpk and select Compile. (Core functionality), then right-click again and select Install. (Registers ChatUI components)
4. Right-click on MakerAi.RAG.Drivers.dpk and select Compile. (DB connections for RAG), then right-click again and select Install. (Registers ChatUI components)

Compile and Install Visual/Design Packages:

5. Right-click on the visual package MakerAi.UI.dpk and select Compile, then right-click again and select Install. (Registers ChatUI components)
6. Right-click on the design-time package MakerAiDsg.dpk and select Compile, then right-click again and select Install. (Registers core non-visual components)

An IDE message will confirm that the components have been installed successfully into the Tool Palette.

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💡 Basic Usage Example

procedure TForm1.Button1Click(Sender: TObject);
var
  Response: string;
begin
  // Make sure you have configured DriverName and Model in the Object Inspector
  Response := AiConnection1.AddMessageAndRun('What is the capital of France?', 'user', []);
  Memo1.Lines.Add('AI: ' + Response);
end;

Image Usage Example

procedure TForm1.Button2Click(Sender: TObject);
var
  MediaFile : TAiMediaFile;
  Response : string;
begin
  MediaFile := TAiMediaFile.Create;
  try
    MediaFile.LoadFromFile('C:\my_image.jpg'); // Replace with the path to your image
    Response := AiConnection1.AddMessageAndRun('Describe this image', 'user', [MediaFile]);
    Memo1.Lines.Add('AI: ' + Response);
  finally
    MediaFile.Free;
  end;
end;

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🔄 Changelog

(MAJOR) Version 3.0 (Q4 2025 / Q1 2026)

• Architectural Shift: MakerAI upgraded from component suite to a complete AI Orchestration Platform / AI Operating System.
• RAG Engine 2.0: Complete overhaul introducing Hybrid Embeddings, massive indexing support, and multi-model compatibility.
• Advanced Semantic Memory: New memory model integrated with RAG and Workflow Graphs for complex, context-aware agents.
• AiConnection V3: Enhanced performance, stability, and connectivity for all major LLM providers.
• New Source Structure: Added ChatUI and Resources folders.
• Modular Packaging: Implementation of four packages: MakerAi.bpl, MakerAi.RAG.Drivers.bpl, MakerAi.UI.bpl, and MakerAiDsg.bpl.
• New Feature: Integrated Voice Monitoring with progressive transcription and activation commands.
• New Feature: Professional visual components for building advanced multimedia chat interfaces (ChatUI).
• Compatibility: Official support for Delphi 10.3, 10.4 Sydney, 11 Alexandria, 12 Athens and 13 Florence.
• Tools: Unified MakerAI Tools system for standardized function calling.

Version 2.6.0 (August 20, 2025)

• New Compatibility! Added official support for Delphi 10.3 Rio and Delphi 11 Alexandria.
• Fix (Ollama): Fixed a bug in the Ollama connector that occurred during asynchronous calls.

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🤝 Contributing

Contributions are welcome. If you have ideas, improvements, or find a bug, please open an issue or submit a pull request. Together, we can make MakerAI the definitive AI tool for the Delphi community.

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💬 Community & Support

• Official Website: https://makerai.cimamaker.com
• GitHub Issues: For reporting bugs and suggesting features.
• Telegram Group: Join the conversation for help and to share your projects.
• Email: gustavoeenriquez@gmail.com

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📜 License

This project is licensed under the MIT License. See the LICENSE.txt file for details.