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Technical review of Ollama concierge agent #3484

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Merged
jasonrandrews merged 1 commit into from
Jul 10, 2026
Merged

Technical review of Ollama concierge agent #3484

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16 changes: 6 additions & 10 deletions content/learning-paths/cross-platform/ai-agent-cpu-orchestration/2-setup.md
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Expand Up @@ -12,15 +12,6 @@ In this section, you'll prepare everything the agent needs before running it: a

These steps are identical on an Apple silicon MacBook, an Arm Linux machine, and an NVIDIA DGX Spark.

## Get a Serper API key

The agent searches the web through [Serper](https://serper.dev/), a Google Search API. The free tier is enough to complete this Learning Path.

1. Go to [serper.dev](https://serper.dev/) and create a free account.
2. Open your dashboard and copy your API key.

You'll set this key as an environment variable later in this section, so the agent can read it without the key being written into the code.

## Create a project directory and virtual environment

A virtual environment keeps the agent's dependencies isolated from your system Python, so you always run against the right package versions.
Expand Down Expand Up @@ -53,7 +44,12 @@ pip install requests beautifulsoup4

## Set your Serper API key

Export your API key as an environment variable in the same terminal session:
The agent searches the web through [Serper](https://serper.dev/), a Google Search API. The free tier is enough to complete this Learning Path.

1. Go to [serper.dev](https://serper.dev/) and create a free account.
2. Once logged in, you will see the dashboard. On the left, click **API Keys**.
3. Copy the Default key.
4. Export your API key as an environment variable in the same terminal session as your virtual environment:

```bash
export SERPER_API_KEY="your-serper-api-key"
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25 changes: 16 additions & 9 deletions content/learning-paths/cross-platform/ai-agent-cpu-orchestration/3-ollama.md
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Expand Up @@ -20,26 +20,33 @@ Running locally has three benefits that matter for an agent:

## Install and start Ollama

Install [Ollama](https://ollama.com/) and start its server using one of the following options. The server exposes a local API at `http://localhost:11434` that the agent connects to.
Install [Ollama](https://ollama.com/) and start its server. The server exposes a local API at `http://localhost:11434` that the agent connects to.

1. Install Ollama using one of the following options:

{{< tabpane code=true >}}
{{< tab header="Homebrew (Recommended)" language="bash">}}
# Install Ollama
{{< tab header="Homebrew" language="bash">}}
brew install ollama

# Start the server as a background service (no terminal to keep open)
brew services start ollama
{{< /tab >}}
{{< tab header="Install script" language="bash">}}
# Install Ollama
curl -fsSL https://ollama.com/install.sh | sh
{{< /tab >}}
{{< /tabpane >}}

2. Start the Ollama server using the same method you used to install it:

# Start the server (leave this running, and open a second terminal)
{{< tabpane code=true >}}
{{< tab header="Homebrew" language="bash">}}
brew services start ollama
{{< /tab >}}
{{< tab header="Install script" language="bash">}}
ollama serve
{{< /tab >}}
{{< /tabpane >}}

With [Homebrew](https://brew.sh/), `brew services` runs Ollama in the background, so you can use the same terminal throughout. With the install script, `ollama serve` runs in the foreground, so keep that terminal open and use a second terminal for the remaining commands.
With [Homebrew](https://brew.sh/), `brew services` runs Ollama in the background, so you can use the same terminal throughout. To stop it later, run `brew services stop ollama`.

With the install script, `ollama serve` runs in the foreground. Keep that terminal open and use a second terminal for the remaining commands. To stop it later, press **Ctrl+C** in the terminal running `ollama serve`.

## Pull the Gemma model

Expand Down
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