How to Run a Local AI Chatbot on Windows with PowerToys and Ollama

Artificial intelligence continues to reshape how we interact with our computers, but for many users, the specter of cloud dependence and privacy tradeoffs has made adoption a tricky prospect. In an era when chatbots like ChatGPT and Microsoft Copilot dominate digital conversations—and practically demand a live internet connection—one experiment stands out: running an AI chatbot locally, integrated directly into the Windows environment. This journey unpacks the experience of transforming PowerToys Run into a personal, on-device AI assistant, drawing on the detailed walkthrough and critical reflections from those who have blazed this trail.

The Push Toward Local AI: Why Bother?​

For Windows enthusiasts and privacy advocates, the reliance of mainstream AI chatbots on the cloud is a double-edged sword. Centralized services offer convenience and power, but they come at the cost of user data sovereignty and an always-on internet requirement. Local AI models offer a compelling counterpoint—a chance to harness LLM capabilities entirely within the confines of one’s own PC.
PowerToys Run, a Swiss Army knife of a utility that has quietly gained favor as an ultra-efficient app launcher and “Start Menu alternative” for Windows 11, serves as the unlikely foundation for this proof of concept. By harnessing it as a front end for a locally running language model, users can now hit a keyboard shortcut and start conversing with AI—without a single byte leaving their machine.
This approach promises both privacy and productivity. But, as with most homebrew solutions, some assembly (and a little patience) is required.

What Makes This Setup Tick: PowerToys Run Meets Ollama​

The core genius of this project lies in two open-source pieces stitched together:

• PowerToys Run: A fast launcher that makes searching, running apps, and now interacting with AI, almost instantaneous from anywhere in Windows.
• Ollama: A command-line application that downloads and runs large language models (LLMs) like Llama 3.1 locally, leveraging your PC’s processing power.

To bridge these, a key ingredient is the “PowerToys-Run-LocalLLm” plugin. This third-party extension allows PowerToys Run to pass your requests to Ollama and display the model's responses right in its own window.

Step-by-Step: Setting Up the Local Chatbot​

1. Install Ollama​

Ollama’s official GitHub repository offers straightforward installation instructions. It prioritizes ease of use and broad compatibility, though for optimal performance, a recent AMD or NVIDIA GPU is highly recommended. While theoretically possible to run on weaker hardware, slow or clunky performance could prove a major obstacle for more casual users.

2. Download a Language Model​

The default plugin configuration targets Llama 3.1, a widely available open LLM developed by Meta. The process boils down to a simple PowerShell command:
ollama pull llama3.1
While Llama 3.1 isn’t the newest model on the block, it offers an excellent tradeoff between capability and performance. Advanced users can easily swap it for other supported LLMs—customization is just a config change away.

3. Deploy the PowerToys Plugin​

PowerToys Run plugins live inside a designated folder on your local machine (commonly under %LOCALAPPDATA%\Microsoft\PowerToys\PowerToys Run\Plugins). Download and extract the “PowerToys-Run-LocalLLm” plugin from its GitHub repo into this directory. Restart PowerToys for the plugin to activate.

4. Configure for Better Usability​

A notable stumbling block is that long AI-generated responses can get truncated. Since the results box in PowerToys Run does not scroll by default, you need to manually increase the “Number of results shown before scrolling” setting in PowerToys. This expands the visible response area. If your answer still runs off the edge, the copy button allows you to grab the entire output and paste it into a text editor.

The User Experience: Speed, Integration, and Limitations​

Launching Your Local AI​

Invoking the AI is frictionless: trigger PowerToys Run as usual (often with Alt+Space), type llm followed by your question, and hit enter. The plugin routes your prompt to Ollama, which generates the reply using the local model and then returns the answer for on-screen display.

Performance Realities​

Here’s where the dream meets the sometimes-awkward reality of local inference. Even on powerful hardware—such as an NVIDIA RTX 5080 GPU—responses are not as instant as their cloud-based cousins. The plugin’s design delivers the entire response at once, rather than streaming it word by word as the terminal interface would do. This creates the perception of sluggishness, as users stare at a blank box until the model completes, making fast back-and-forth AI conversation less fluid. With less robust hardware, lag is pronounced.
Critical point: This is not a technical flaw per se, but a byproduct of both the plugin’s implementation and the heavy computational load of running LLMs on consumer GPUs. Local AI comes with inherent hardware demands—and without the resources of a datacenter, even modern PCs can struggle with the biggest models.

Interface Quirks​

The result display is what one might politely call “utilitarian.” Out of the box, answers are visually clipped, since PowerToys Run was never intended as a chat window. Until scrolling support is implemented, users must make do with a larger box setting or resort to copying the answer out to another app. This is hardly seamless and serves as a reminder that this remains more proof of concept than polished product.
That said, the team behind PowerToys—and the vibrant open-source plugin community—have a track record of rapidly iterating toward better usability. User feedback may well see this become a smoother, more “chatbot-like” experience in the not-too-distant future.

Security and Privacy: A Case for Local AI​

Arguably the most compelling reason to pursue this local-first approach is control. With Ollama and your chosen LLM running entirely on your device, prompts and responses stay private. For sensitive tasks—medical inquiries, confidential business brainstorming, intellectual property work—this could be a game-changer.
There are, however, important caveats:

• Model Transparency: Not all open models are created equal. While Llama 3.1 is well-documented, other third-party models may have “unknown unknowns” regarding data sources, biases, or vulnerabilities.
• Local Threats: Running an LLM on-device does not shield you from the risks that would arise if your machine was compromised. Malware or misconfiguration could still expose your data.
• Update Hygiene: Because all computation happens locally, updating HLLMs for security, bugfixes, or performance improvements becomes your own responsibility—a double-edged sword for those less inclined to regular maintenance.

Nevertheless, privacy-minded users have good reason to celebrate an alternative to always-on, always-watching cloud chatbots.

Productivity: Does Local AI Enhance the Windows Workflow?​

The integration of a local chatbot directly into PowerToys Run disrupts a decades-old separation in the Windows productivity landscape. Traditionally, invoking generative AI meant tabbing over to a web browser, launching a dedicated app, or leaning on cloud-based helpers (like Microsoft Copilot) that feel bolted-on rather than truly native.
By contrast, typing a quick question from within PowerToys Run embeds AI into the daily flow: researching shortcuts, generating snippets of code, summarizing documentation, or composing quick emails, all without leaving the current workspace.

• Faster Context Switches: With AI answers reachable via a keyboard command, users can resolve queries without losing focus or cluttering their screen with extra applications.
• Offline Capability: Traveling, working on air-gapped machines, or just wrestling with erratic internet? Local models ensure you’re never left without your digital assistant.
• Custom Model Choices: Unlike “one-size-fits-all” web products, you pick the LLM that fits your needs—whether that’s raw accuracy, smaller memory footprint, or specific domain knowledge.

Early Adopter Pain Points​

Still, this setup isn’t for everyone. Even enthusiasts will encounter a handful of friction points:

• Initial Configuration: While not especially difficult, setting up Ollama and the PowerToys plugin requires comfort with downloading packages, navigating directories, and tweaking options.
• Hardware Requirements: Running modern LLMs acceptably fast still requires a strong GPU (and plenty of RAM). On low-end devices, expect glacial response times.
• UI/UX Limitations: The PowerToys Run interface, as of now, isn’t optimized as an AI chat window. Longer conversations, file uploads, or advanced formatting are simply beyond its scope.

It’s a raw but promising start—a kind of “Windows 11 AI hacker’s playground”—that notably does not replace full-featured chatbots like ChatGPT or Copilot, especially for lengthy or complex tasks.

Comparing to Mainstream Alternatives: Local vs. Cloud Chatbots​

Feature	PowerToys Run + Ollama (Local)	ChatGPT / Copilot (Cloud)
Privacy	High, all data stays local	Low/Variable, data sent to servers
Speed	Moderate to slow, hardware-dependent	Fast, cloud computing resources
Cost	Free (beyond hardware costs)	Free/Paid plans, pay for premium
Model Customization	User chooses models, easily swapped	No user control over models
Offline Functionality	Yes	No
Ease of Use	Requires setup, technical	Ready out of the box
Reliability/Support	Community-driven	Corporate/official support
Advanced Features	Limited by plugins and hardware	Rich ecosystem, media uploads, etc

This contrast makes clear that, while local AI is currently a niche or enthusiast solution, it fills a growing desire for autonomy and flexibility. For IT pros, developers, and privacy wonks, the tradeoffs may be well worth it.

The Future: A Glimpse or a Glimmer?​

Microsoft has shown enormous interest in embedding AI throughout the Windows experience—witness the rapid expansion of Copilot and the company’s partnership with OpenAI. Yet, as PowerToys remains one of its most powerful open-source playgrounds, community-driven experiments like this could well foreshadow official builds in the near future.
If future PowerToys or Windows 11 releases build on this groundwork—with deeper integration, native streaming output, and even better model management—the line between “cloud” and “local” AI could blur significantly. Such developments would offer users an alternative to the privacy-compromised, always-on-connectivity world of today’s AI assistants.

Risks and Responsible Adoption​

Local LLMs offer significant upsides but also demand consideration around ethical use, system resource allocation, and evolving security risks. For instance:

• Biases and Misinformation: Open-source language models can perpetuate or exacerbate falsehoods, especially when not routinely updated or fine-tuned.
• Resource Drain: Running an LLM may spike system temperature, hog memory, or slow down other tasks, especially on less capable machines.
• Security Exposure: Plugins downloaded from unofficial repositories, or running out-of-date AI models, represent potential attack vectors.
• Lack of Guardrails: Unlike commercial bots, local LLMs may not implement robust “safety” layers or filtering, making them less suitable for child-friendly use or sensitive environments.

Users must weigh these risks and practice good digital hygiene: keeping plugins up to date, vetting models, and keeping system backups.

Final Thoughts: A Promising, If Imperfect, Step Forward​

Integrating a local AI chatbot into PowerToys Run is, at heart, a demonstration of what’s possible at the technological edge of Windows productivity. The solution is not (yet) the fastest or the most polished—but it undeniably showcases the power of open-source collaboration and the expanding toolkit available to Windows enthusiasts.
While most mainstream users will continue relying on cloud-based Copilot, ChatGPT, and their ilk, a growing community will find strong incentive to keep their AI local, private, and directly at hand. Each friction encountered—whether an unscrolled chatbox, sluggish outputs, or cryptic config files—is both a challenge and an opportunity for innovation.
If privacy, customization, and a sense of digital independence matter to you, turning PowerToys Run into an on-device AI chatbot is a fascinating, empowering experiment. As both companies and independent developers race to improve local inference and interface fluidity, what feels like proof of concept today may be tomorrow’s must-have Windows feature.

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Source: Windows Central I turned PowerToys Run into an AI chatbot that runs entirely on my PC