Yesterday at 12:34 PM1 day The MBS FileMaker Plugin provides a comprehensive set of components to integrate Artificial Intelligence (AI) and Machine Learning (ML) into FileMaker solutions. This includes local LLM execution, platform-native ML frameworks, external API integration, and scripting bridges to other AI ecosystems.Below is a technical overview of the available components and how developers can use them in real-world scenarios.Foundation ModelsProvides access to Apple's Foundation Models framework for running on-device large language models (LLMs).Initialize and manage model sessionsSend prompts and receive streamed or complete responsesConfigure parameters such as temperature, token limits, and system promptsSupports multilingual input/outputTypical use cases include chat interfaces, text summarization, structured data extraction, and natural language command parsing—all without requiring internet access.See FoundationModels functions and Use Foundation Models in FileMaker.Llama.cppIntegrates llama.cpp to run open-source LLMs locally within FileMaker.Load GGUF/GGML models from local storageControl inference parameters (context size, temperature, top-k, top-p)Maintain conversation context for chat-based workflowsNo dependency on external servicesIdeal for offline deployments, secure environments, or custom fine-tuned models. Developers can build fully self-contained AI systems inside FileMaker.See Llama functions and Use Llama.cpp in FileMaker.CoreMLExecute machine learning models using Apple's CoreML framework.Load compiled .mlmodel filesRun inference on structured or image dataSupports classification, regression, and neural networksCommon use cases include predictive analytics, recommendation systems, and image classification workflows embedded directly in FileMaker.See CoreML functions and related functions that run CoreML models within the frameworks like CoreImage.Detect function.Windows MLProvides access to Windows Machine Learning APIs on Windows 10 and newer.Load ONNX modelsPerform inference using local hardware accelerationIntegrate ML into Windows-based FileMaker deploymentsUseful for cross-platform solutions where macOS uses CoreML and Windows uses ONNX-based models.See WindowsML functions.VisionWraps Apple’s Vision framework for image analysis tasks.Text detection and recognitionFace detection and landmark trackingObject recognition and classificationBarcode and QR code detectionOften combined with CoreML for custom vision models or with OCR workflows for document processing pipelines.See Vision functions and Vision Framework for FileMaker.Image PlaygroundInterfaces with Apple Intelligence image generation features.Generate images from text promptsAdjust styles and generation parametersStore generated images directly in FileMaker container fieldsUseful for generating previews, assets, or user-driven content inside applications.See ImagePlayground functions and Use Image Playground in FileMaker.PythonRun Python-based AI workflows directly from FileMaker.Execute Python code via MBS Python functionsCall external scripts using Shell functionsIntegrate libraries such as TensorFlow, PyTorch, scikit-learn, or transformersThis approach enables access to the broader AI ecosystem, including custom pipelines, embeddings, vector databases, and advanced data processing.See Python functions and Using Python in FileMaker.OCRBuilt-in OCR functionality based on Tesseract.Extract text from images and PDFsSupport multiple languagesPreprocess images for improved recognition accuracyFrequently used for invoice processing, document indexing, and data entry automation.See OCR, WindowsOCR functions and OCR on Windows in FileMaker.CURLProvides HTTP client functionality to connect with external AI services.Send REST API requests (POST/GET)Handle authentication (API keys, headers)Parse JSON responses using FileMaker JSON functionsEnables integration with services such as OpenAI, Anthropic, or Google AI models. The plugin includes example files demonstrating ChatGPT API integration and response handling.See CURL functions and Using ChatGPT in FileMaker.Integration PatternsYou may combine various functions to build solutions based on the toolbox provided with MBS Plugin:Hybrid AI: Combine local LLMs (FoundationModels/Llama) with cloud APIsPipeline Processing: OCR → LLM → Structured Data OutputAI-assisted UI: Natural language inputs driving FileMaker scriptsOffline-first apps: Fully local AI using Llama + CoreMLConclusionThe MBS FileMaker Plugin enables developers to integrate AI at multiple levels—from low-level ML inference to high-level conversational interfaces.By combining local processing, external APIs, and scripting bridges, it provides a flexible architecture for building modern, intelligent FileMaker solutions.
Create an account or sign in to comment