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Ollama lets you run large language models locally on your machine. It’s the primary and default provider for Page Assist, offering easy installation and model management.

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Prerequisites

  • Ollama installed on your system
  • At least one model downloaded in Ollama
  • Sufficient RAM for your chosen model (typically 8GB+ recommended)

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Installation

If you haven’t installed Ollama yet:
1

Download Ollama

Visit ollama.ai and download the installer for your operating system.
2

Install Ollama

Run the installer and follow the installation instructions.
3

Download a Model

Open your terminal and download a model:
ollama pull llama3.2
Popular models include:
  • llama3.2 - Meta’s latest Llama model
  • mistral - Mistral 7B
  • phi3 - Microsoft’s Phi-3
  • qwen2.5 - Alibaba’s Qwen model
4

Verify Installation

Check that Ollama is running:
ollama list
This should display your downloaded models.

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Default Configuration

Page Assist automatically detects Ollama running on the default address: 
http://127.0.0.1:11434
No additional configuration is needed if Ollama is running on this default port.

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Custom Ollama URL

If you’re running Ollama on a different port or remote server:
1

Open Settings

Click the Page Assist icon in your browser toolbar, then click the Settings icon.
2

Navigate to Ollama Settings

Find the Ollama URL configuration section in the main settings.
3

Update URL

Enter your custom Ollama URL:
http://127.0.0.1:11435
4

Save Configuration

Click Save to apply the changes.

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Multiple Ollama Instances

You can connect to multiple Ollama instances simultaneously:
1

Open Settings

Click the Page Assist icon, then click Settings.
2

Navigate to OpenAI Compatible API

Go to the “OpenAI Compatible API” tab.
3

Add Provider

Click the “Add Provider” button.
4

Select Ollama

Choose “Ollama” from the provider dropdown.
5

Enter Ollama URL

Enter the URL of your additional Ollama instance:
http://192.168.1.200:11434
6

Save Provider

Click Save. Page Assist will automatically fetch available models from this instance.

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Model Selection

Page Assist automatically detects all models available in your Ollama instance.

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Viewing Available Models

Models appear in the model selector dropdown. Page Assist filters out embedding-only models (like nomic-embed-text) from the chat model list.

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Setting a Default Model

To set a default model:
  1. Open Settings
  2. Find “Default Model” configuration
  3. Select your preferred model from the dropdown
  4. Optionally disable “Ask for model selection every time” to always use the default

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Model Nicknames

You can assign custom names to models for easier identification:
  1. Navigate to model management in Settings
  2. Select a model
  3. Enter a custom nickname
  4. The nickname will appear in the model selector

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Disabling Models

To hide specific models from the selector:
  1. Go to Settings > Models
  2. Find the model you want to hide
  3. Toggle it off
  4. The model won’t appear in model selection but remains in Ollama

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Embedding Models

Page Assist automatically identifies embedding models for RAG (Retrieval-Augmented Generation) features: 
# Download an embedding model
ollama pull nomic-embed-text
Embedding models are used for:
  • Knowledge base search
  • Document similarity
  • RAG chat features

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Connection Troubleshooting

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Ollama Not Detected

If Page Assist can’t connect to Ollama:
1

Verify Ollama is Running

Check if Ollama is running:
ollama list
If this fails, start Ollama using your system’s application launcher.
2

Check the URL

Ensure the URL in Page Assist settings matches your Ollama address. The default is:
http://127.0.0.1:11434
Note: Page Assist automatically converts localhost to 127.0.0.1.
3

Test Connection

Open your browser and navigate to:
http://127.0.0.1:11434
You should see “Ollama is running”.
4

Check Firewall

Ensure your firewall isn’t blocking port 11434.
5

Restart Extension

Try reloading the Page Assist extension from your browser’s extensions page.

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Models Not Appearing

If models don’t show up:
  1. Verify models are downloaded: ollama list
  2. Refresh the Page Assist interface
  3. Check if Ollama is enabled in Settings
  4. Ensure models aren’t manually disabled in model management

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Performance Issues

For better performance:
  • Use quantized models (e.g., llama3.2:q4_0)
  • Close other resource-intensive applications
  • Consider using smaller models (7B or 3B parameter models)
  • Ensure adequate RAM for your model size

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Advanced Configuration

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Custom Model Parameters

You can customize model behavior through Ollama’s Modelfile: 
# Create a custom model with specific parameters
ollama create mymodel -f Modelfile
Example Modelfile: 
FROM llama3.2
PARAMETER temperature 0.7
PARAMETER top_p 0.9
SYSTEM You are a helpful assistant.

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Remote Ollama Setup

To expose Ollama for remote access: 
# Set environment variable (Linux/Mac)
export OLLAMA_HOST=0.0.0.0:11434
ollama serve
For Windows, set the environment variable in System Properties.

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Best Practices

  1. Keep Models Updated: Regularly check for model updates using ollama pull <model>
  2. Monitor Resources: Watch RAM usage when running large models
  3. Use Appropriate Sizes: Match model size to your hardware capabilities
  4. Leverage Multiple Models: Keep different models for different tasks (coding, chat, etc.)
  5. Clean Up Unused Models: Remove models you don’t use to save disk space: ollama rm <model>

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Next Steps

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