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FrameworX 10.1.5 ships configured to talk to a local Ollama with qwen2.5:7b-instruct by default. This page documents Install-LocalAI.ps1 — the idempotent setup script that gets a fresh machine into that state.

AI Integration → Local AI → First Install Walkthrough (10.1.5 draft)

Quick start

Run Install-LocalAI.ps1 from the FrameworX AISetup folder. The script is idempotent: re-running on an already-set-up machine is safe and finishes in a few seconds.

powershell -ExecutionPolicy Bypass -File "<FX-install>\AISetup\Install-LocalAI.ps1"

Replace <FX-install> with your FrameworX install location, typically C:\Program Files\Tatsoft\FrameworX\fx-10.

What the script does

When all five steps already pass, the script does nothing destructive and returns in seconds.

What to expect on first install

Sample run output

A green run on an already-set-up machine looks like this:

FrameworX Local AI - Install and Verify
Default model: qwen2.5:7b-instruct
Endpoint:      http://localhost:11434/v1/chat/completions

==> Checking port 11434
  ok  Ollama already serving on 11434 (PID 6224)
==> Checking Ollama install
  ok  Ollama present at C:\Users\<user>\AppData\Local\Programs\Ollama\ollama.exe
==> Checking Ollama server is responding
  ok  Ollama server responding on http://localhost:11434
==> Checking model 'qwen2.5:7b-instruct'
  ok  Model present (4.36 GB on disk)
==> Smoke-testing inference (this also primes the model into RAM)
  ok  Inference returned in 10.3s: 'pong'

All green. Total time: 12.9s.
FrameworX is ready to talk to Local AI at http://localhost:11434/v1/chat/completions

Each ok line is a state-check that found things already correct and skipped the work. On a fresh machine, those ok lines are replaced with progress messages from winget install and ollama pull.

Next: configure your model in Designer

After the script reports All green, open Designer and confirm FrameworX can reach the model:

1. Open your solution in Designer.
2. Navigate to Unified Namespace → Data Servers.
3. Find the Local AI tile. The status should resolve to Reachable within a few seconds.
4. Click the tile to edit the endpoint URL, model name, response timeout, or authorization — or to point at a remote / cloud LLM instead of the default local Ollama.

If the tile shows Unreachable, re-run Install-LocalAI.ps1 — the script's smoke test will surface whatever changed (Ollama not started, model not pulled, port held by another process). If it shows Auth required, see SecuritySecrets Authentication for Local AI (10.1.5 draft). Full configuration reference: Local AI Configuration (10.1.5 draft).

If the script reports a port conflict

If port 11434 is already held by a different process (LM Studio, llama.cpp server, oobabooga, an old test server, etc.), the script aborts with a clear message naming the offending process. To resolve:

1. Stop the conflicting service, or move it to a different port.
2. Re-run Install-LocalAI.ps1.

The script intentionally does NOT kill foreign processes on its own — port 11434 is heavily used by the LLM ecosystem and a silent process kill is the wrong default.

Running the model on a different host

By default Ollama binds localhost only. To run Ollama on a separate machine (typically a GPU server) and have FrameworX talk to it over the network:

1. On the Ollama host: set OLLAMA_HOST=0.0.0.0:11434 in the system environment, then restart Ollama.
2. Open inbound TCP 11434 in the Ollama host's firewall.
3. In FrameworX, edit SolutionSettings.ModelSettings to point URL at http://<ollama-host-ip>:11434/v1/chat/completions.

A future revision of this script will accept a -RemoteHost flag to automate steps 1 and 2.

Choosing a different model

The default qwen2.5:7b-instruct is a balance of quality and footprint for typical SCADA hardware. To use a different model:

1. Pull it with Ollama: ollama pull <model-name> (for example, qwen2.5:3b for low-RAM gateways, qwen2.5:14b-instruct for capable servers, llama3.1, mistral, etc.).
2. In FrameworX, edit SolutionSettings.ModelSettings and set the Name field to the new model name.

Any OpenAI-compatible endpoint works — including cloud LLMs (OpenAI, Azure OpenAI, Anthropic via OpenAI-compat proxy). Set URL and Authorization accordingly.

See also

• Local AI — the main reference page (parent of this one).
• AI Integration — the broader AI surface in FrameworX.

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