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Prerequisites ​

Install Ollama ​

Download and install Ollama from ollama.ai/download.

After installation, start the Ollama server:

bash
# Option A: open the Ollama desktop app (macOS / Windows)
# Option B: run from the terminal
ollama serve

Verify it's running:

bash
curl http://localhost:11434
# Expected: "Ollama is running"

(Optional) Log in to Ollama Cloud ​

Cloud models are hosted by Ollama and require authentication:

bash
ollama login

Follow the prompts in your browser. Once logged in, Cloud models appear in the sidebar's Cloud Models panel.

Install GitHub Copilot Chat ​

The extension integrates with the GitHub Copilot Chat extension. Make sure it is installed and signed in.

Install Opilot ​

Search for "Opilot" in the VS Code Extensions panel, or run:

bash
code --install-extension selfagency.opilot

The Ollama activity bar icon (🦙) will appear automatically on next startup.


Step 1: Pull Your First Model ​

Click the Ollama icon in the activity bar to open the sidebar. Navigate to the Library panel, find a model, and click the Pull (⬇) button on any variant.

Recommended starter models:

Use CaseModelSize
General chatllama3.2:3b~2 GB
Code chat (fast)qwen2.5-coder:7b~5 GB
Code completionsqwen2.5-coder:1.5b~1 GB
Visionllava:7b~5 GB
Reasoningdeepseek-r1:7b~5 GB

While a model is pulling you'll see streaming progress inside a VS Code notification. You can continue working — pulls happen in the background.


Step 2: Start a Conversation ​

Via the Model Picker ​

  1. Open GitHub Copilot Chat (Ctrl+Alt+I / Cmd+Alt+I)
  2. Click the model selector dropdown in the chat input
  3. Select any model prefixed with 🦙 Ollama
  4. Start chatting normally

The model picker shows all locally cached Ollama models alongside the standard Copilot models.

Via the @ollama Chat Participant ​

Type @ollama at the beginning of a Copilot Chat message to direct it straight to your local Ollama instance:

text
@ollama explain the design of this TypeScript module

The @ollama participant is sticky — once you invoke it in a thread, subsequent messages in the thread continue using it automatically.

→ See @ollama Chat Participant for the full guide.


Step 3: (Optional) Enable Inline Completions ​

To get real-time code suggestions as you type, configure a completion model:

  1. Open Settings (Ctrl+, / Cmd+,) and search for ollama.completionModel
  2. Enter a small, fast model name (e.g. qwen2.5-coder:1.5b)
  3. Make sure ollama.enableInlineCompletions is true

Smaller quantized models (1–3 B parameters) respond quickly enough for a smooth completion experience. See Inline Completions for tuning tips.


Step 4: (Optional) Create a Custom Modelfile ​

Modelfiles let you define a custom model persona, system prompt, and inference parameters. Click the + button in the Modelfiles sidebar panel to launch the wizard.

→ See Modelfile Manager for the full guide.


Remote Ollama Instances ​

To connect to a remote Ollama server, update the ollama.host setting:

  1. Open Settings and search for ollama.host
  2. Enter your remote URL (e.g., http://my-server:11434)
  3. If the server requires authentication, run "Ollama: Manage Ollama Auth Token" from the Command Palette to store your bearer token securely

→ See Settings for all available configuration options.

Released under the MIT License