Accelerating FileMaker Development with AI Code Builders

Accelerating FileMaker Development with AI Code Builders

In this post, we’ll explore how AI code builders—specifically ChatGPT Code Copilot—can help you create custom JavaScript widgets for FileMaker. We’ll walk through an example of building a signature pad, discuss best practices for prompting AI, and touch on some ethical and legal considerations involved in using AI-generated code.

Why Use an AI Code Builder?

AI code builders (e.g., ChatGPT Code Copilot, GitHub Copilot, etc.) leverage machine learning models trained on large amounts of programming data. They can assist developers by

  • Generating boilerplate or starter code automatically

  • Suggesting functions and syntax in real time

  • Speeding up iteration on front-end features like HTML, CSS, and JavaScript

AI Code builders allow you to build a widget or page without knowing ANY programming languages.

When used correctly, these tools can save hours of coding and debugging—especially for tasks that don’t necessarily require advanced, custom logic.

Key Considerations – Ethics, Legality, and Privacy

  1. Ethical Impact
    AI-driven tools can automate mid-level coding tasks, potentially affecting developer job roles. While it streamlines certain work, the long-term impact on developer careers is worth watching.

  2. Legal Concerns
    AI generators may source snippets of copyrighted code. While current U.S. legal direction makes direct infringement cases unlikely, it’s prudent to remain cautious about where the code originates.

  3. Privacy
    Anything you share with an AI tool could be integrated into its broader dataset. Never upload confidential information or proprietary code without anonymizing or removing sensitive details.

Best Practices When Prompting ChatGPT

Through trial and error, the webinar revealed a handful of tips to get the best results from AI code builders

  1. Craft a Strong Initial Prompt

    • Be specific about what you want, from the programming language to the functionalities and layout.

    • Bad Example – “Build me a signature pad using Javascript, CSS and HTML with Clear, Undo, Save and Cancel buttons.”

    • Good Example – “Build me a signature pad using HTML, CSS and Javascript. The page should include a header titled "Sign Below" a signing canvas and buttons below the canvas.

The buttons will be the following

Clear – Completely removes all drawings from the canvas

Undo – removes the most recent drawing from the canvas

Submit – Saves the canvas to a .png image and stores it as base64 text. It then should run the function FileMaker.PerformScript("SaveSignature" ; base64code of image);

Cancel – Runs the function FileMaker.PerformScript("CancelSignature" ; "" )

The buttons should have a black background with white writing. They should be on the same row and ordered from left to right Clear, Undo, Submit, Cancel. 

The Clear and Undo buttons should be grouped on the left side of the screen and the Submit and Cancel buttons should be grouped on the right side of the screen.

The background for the page and for the signature pad should be white.

Build me the code for this page in 3 separate files index.html, style.css, script.js“

  1. Provide Existing Code Snippets

    • If you’re modifying existing code, paste that code into ChatGPT’s prompt.

    • AI often “forgets” prior context or overwrites essential lines if you ask it to regenerate the entire codebase.

  2. Make Incremental Requests

    • After generating an initial version, ask for changes in small, specific steps (e.g., “reduce the button size,” “add rounded corners,” or “change the header’s font size”).

    • Requesting many modifications at once can confuse the AI and lead to broken or incomplete solutions.

  3. Ask for Only the Changes

    • Rather than asking for the entire file again, say “Please provide only the lines that need to be updated or added.”

    • This preserves previously working code and reduces the likelihood of accidental regressions.

  4. Avoid Complex Multi-tasking

    • AI code builders can lose track of context during multi-part tasks. Break them down into small, separate requests.

Step-by-Step Example – Building a Signature Pad in FileMaker

Goal – Create a signature pad that captures a user’s drawing, supports undo/clear, and saves the result as a base64-encoded image inside FileMaker.

  1. Outline Requirements

    • HTML – A simple layout with a canvas, header, and four buttons (Clear, Undo, Submit, Cancel).

    • CSS – Basic styling (button size, background color, alignment).

    • JavaScript – Canvas drawing logic (capturing strokes, undo/redo stacks), plus two FileMaker script calls

      • FileMaker.PerformScript("Save Signature", base64Code)

      • FileMaker.PerformScript("Cancel Signature")

  2. Create a Detailed Prompt
    In ChatGPT, specify –
    “Build me a signature pad using HTML, CSS, and JavaScript, including a header titled ‘Sign Below,’ a canvas, and four buttons. The ‘Submit’ button should encode the canvas as base64 and call FileMaker.PerformScript("Save Signature", <base64>), etc.”

  3. Generate Files
    ChatGPT returns – index.html (or combined HTML file)

    • style.css (for layout and styling)

    • script.js (draw logic and button handlers)

  4. Refine & Test

    • If the AI lumps HTML/CSS/JS together, ask for separate files or placeholders for easy inclusion in FileMaker fields.

    • Test your initial code locally (e.g., open the HTML in a browser). Check if Undo/Clear works and if Submit/Cancel behave as expected.

  5. Integrate Into FileMaker

    • Store the HTML, CSS, and JS in FileMaker fields.

    • Use a calculation field or a “web viewer” that substitutes in the CSS/JS code.

    • Ensure “Allow interaction” and “Allow JavaScript to perform FileMaker scripts” are enabled in the web viewer settings.

  6. Add Final Touches

    • Prompt ChatGPT for style updates (e.g., “Make the header smaller and unbold it,” “Group the Clear and Undo buttons on the left,” etc.).

    • Manually adjust any margins or design elements if ChatGPT’s output isn’t pixel-perfect.

Result: A working signature pad that you can open in FileMaker, draw on, and automatically store the output as a base64-encoded image—perfect for e-signatures or doodles.

Beyond Signatures – A Time-Tracking Example

The webinar also showcased a more advanced JavaScript widget – a time-tracking dashboard built entirely via AI-assisted code, then dropped into FileMaker. It features

  • Dynamic plus and delete buttons for line items

  • Light and dark modes

  • Start and Stop Timers

  • The entire front-end (HTML, CSS, JS) generated by ChatGPT with minimal manual intervention

This advanced use case illustrates how quickly you can evolve from small widgets (like a signature pad) to more complex applications—increasing interactivity and user experience within FileMaker, all powered by AI-generated front-end code.

Closing Thoughts

AI tools like ChatGPT can drastically reduce development time and open doors to front-end interactions you might not otherwise build by hand. The key is prompt engineering—learning how to give precise instructions and incremental feedback.

Remember

  • Always keep ethical, legal, and privacy considerations in mind.

  • Triple-check AI-generated code for security issues and correctness.

  • Use a “rinse and repeat” process – prompt, refine, test, and integrate.

By leveraging these best practices, you’ll be well on your way to creating powerful, user-friendly JavaScript widgets that enhance FileMaker’s functionality—without having to become a front-end development expert.

Further Resources

Have questions or want to share your own AI-generated FileMaker widget? Drop a comment or reach out to continue the conversation. Happy coding!



Can Your FileMaker Do This? Enhance Manufacturing Efficiency with AI-Powered Semantic Search

In modern manufacturing, quick and accurate access to data can make the difference between streamlined production and costly delays. Yet, traditional database search methods often fall short, requiring exact keywords and precise input. This is where AI-powered semantic search within Claris FileMaker solutions can transform operations, enabling users to retrieve information using natural language queries.

At Kyo Logic, we’ve implemented semantic search capabilities to revolutionize how manufacturers access and interact with their data. Let’s dive into how this technology works, its applications, and how it can improve your manufacturing processes.

What Is AI-Powered Semantic Search?

Semantic search goes beyond matching exact keywords by understanding the intent and context behind a query. It can also be combined with traditional search for even more uses. Powered by AI and natural language processing (NLP), semantic search interprets phrases, synonyms, and even contextual nuances. In FileMaker, this functionality can be achieved by integrating AI-powered tools like Claris Connect, external AI services (e.g., OpenAI APIs), or scripting custom machine-learning models.

For example:

  • Instead of searching “inventory: steel bolts 2mm,” users could type, “I need small steel bolts for automotive assembly.”

  • Semantic search understands “small” to mean “2mm” and “automotive assembly” to refine results to the relevant inventory category.

Use Case: Intelligent Inventory Management

One of the most impactful applications of semantic search is in inventory management, where manufacturers often deal with thousands of SKUs and components.

Scenario:

A manufacturer needs to locate specific materials—say, heat-resistant steel components for an automotive project. Traditional keyword searches might require exact terms like “steel component heat-resistant.” With semantic search, a user could simply query, “What materials can withstand high heat for automotive use?”

How It Works in FileMaker:

  1. Data Structuring: Inventory data is enriched with metadata, such as material properties, usage, and categories.

  2. AI Model Integration: A pre-trained NLP model is connected to FileMaker via an API or a microservice, such as OpenAI’s GPT API.

  3. Query Processing: When a user inputs a query, the system translates it into structured search parameters (e.g., “find all inventory tagged with ‘heat-resistant’ AND ‘automotive’”).

  4. Results Display: The system provides a ranked list of relevant inventory items, including links to more detailed specifications.

Benefits for Manufacturers

  1. Improved Data Retrieval:

    • Traditional searches depend on exact terms, which can lead to missed results. Semantic search captures broader intent, ensuring the right data is always accessible.

    • Example: A query like “fasteners for aerospace” can return bolts and rivets tagged with “aerospace grade.”

  2. Enhanced Decision-Making:

    • Rapid access to contextualized data allows engineers and managers to make timely and informed decisions, minimizing production bottlenecks.

    • Predictive models can suggest alternatives or complementary components.

  3. Operational Efficiency:

    • By reducing the time spent searching for information, semantic search enables staff to focus on high-value tasks, such as quality assurance or innovation.

Implementing Semantic Search in FileMaker

Here’s how you can get started:

  1. Audit Your Database:

    • Ensure your FileMaker database is well-structured and includes descriptive fields for metadata.

    • Example: Add fields like “material type,” “application,” and “specifications” to inventory tables.

  2. Connect to AI Tools:

    • Use Claris Connect or integrate external AI APIs for semantic processing.

    • Example: OpenAI’s API can process natural language queries and return contextually relevant results.

  3. Develop Custom Scripts:

    • Write FileMaker scripts that send queries to the AI tool, process results, and present them in a user-friendly interface.

    • Use custom layouts to display ranked search results dynamically.

Ready to Transform Your FileMaker System?

Semantic search isn’t just about searching smarter—it’s about enabling faster decisions and boosting operational efficiency. If you’re ready to explore how AI-driven capabilities can integrate into your FileMaker solution, contact us today for a consultation. Let’s take your manufacturing processes to the next level.