AI has become one of the most divisive and controversial emerging tech developments of our age. And not without reason – its impacts on the environment and on society are hotly debated and still not completely understood.

It’s one of the reasons that ethical AI is such a promising field right now. Using free tools on any medium-specced machine, you can beef up your workflows without burdening data centres in exchange for your privacy.

Perhaps you too are already using local LLMs as a more environmentally responsible content aid. They’re a great choice for assisting in activity creation in “mainstream” languages; the latest small models can comfortably match the output of the online beasts like Claude and ChatGPT.

But you may have already run up against the “black box” limitation. Out of the box, locally run LLMs have only their own resources, and no connection to the outside world for retrieving up-to-date info or fact-checking.

Tooling AI

There is a solution – and if you’re running models in LM Studio, it’s pretty easy to implement. A number of tools, or plug-ins, are available to extend the capabilities of your models. They range from simple everyday functions like a current date check, to internet searching and even file system access. When browsing models in LM Studio, tags indicate which are ready for tool use – which, in practice, is nearly all recent releases.

One word of caution – it’s important to take some care in selecting and installing tools. Community users are generally the tool developers, rather than the LLM providers. As such, you should always do due diligence and check sources before installing them. Building these assumptions into practice has been a baptism of fire for users at the bleeding edge of AI – you may well have come across recent stories about insecurities in certain third-party tools for the ‘agentic’ system, OpenClaw.

That said, LM Studio hosts a library of third-party tools on its website that should have passed community checks. These include a Wikipedia search, which instantly gives your queries a fact-checking foundation (allowing for the occasional Wikipedia factual error or two!). If that’s not enough, then there’s that full web search tool too. To use this, you need to set up a search provider – the free and ethical SearXNG is recommended, and it’s worth the fiddling around to set it up. (Again, exercise plenty of care when allowing your local models to consume external data.)

And back to that prosaic old date check – it’s actually more useful than you might at first think. As LLMs are trained on static text data, they have a memory cut-off. There’s generally an ‘awareness’ of this (insofar as we can call it that). Try, for instance, asking a local model what was in the news yesterday. It might well respond by stating its knowledge cut-off date (if it doesn’t make something up). Install a date checker and you add a corrective to this behaviour. That web search is much more effective if a model ‘knows’ when now is.

New tools are being developed all the time, bringing local model use even closer in line with online AI portals. For many, that’s a big step closer to becoming a viable, ethical replacement for them. Explore, experiment and share – I’d love to know what other tools you’ve found useful in the comments!