FAQs - Continue

Networking Issues

Configure Certificates

If you’re seeing a fetch failed error and your network requires custom certificates, you will need to configure them in your config file. In each of the objects in the "models" array, add requestOptions.caBundlePath like this:

models:
  - name: My Model
    ...
    requestOptions:
      caBundlePath: /path/to/cert.pem

You may also set requestOptions.caBundlePath to an array of paths to multiple certificates. Windows VS Code Users: Installing the win-ca extension should also correct this issue.

VS Code Proxy Settings

If you are using VS Code and require requests to be made through a proxy, you are likely already set up through VS Code’s Proxy Server Support. To double-check that this is enabled, use cmd/ctrl + , to open settings and search for “Proxy Support”. Unless it is set to “off”, then VS Code is responsible for making the request to the proxy.

code-server

Continue can be used in code-server, but if you are running across an error in the logs that includes “This is likely because the editor is not running in a secure context”, please see their documentation on securely exposing code-server.

Changes to assistants not showing in VS Code

If you’ve made changes to assistants (adding, modifying, or removing them) but the changes aren’t appearing in the Continue extension in VS Code, try reloading the VS Code window:

Open the command palette (cmd/ctrl + shift + P)
Type “Reload Window”
Select the reload option

This will restart VS Code and reload all extensions, which should make your assistant changes visible. By default the Continue window is on the left side of VS Code, but it can be dragged to right side as well, which we recommend in our tutorial. In the situation where you have previously installed Continue and moved it to the right side, it may still be there. You can reveal Continue either by using cmd/ctrl+L or by clicking the button in the top right of VS Code to open the right sidebar.

I’m getting a 404 error from OpenAI

If you have entered a valid API key and model, but are still getting a 404 error from OpenAI, this may be because you need to add credits to your billing account. You can do so from the billing console. If you just want to check that this is in fact the cause of the error, you can try adding $1 to your account and checking whether the error persists.

I’m getting a 404 error from OpenRouter

If you have entered a valid API key and model, but are still getting a 404 error from OpenRouter, this may be because models that do not support function calling will return an error to Continue when a request is sent. Example error: HTTP 404 Not Found from https://openrouter.ai/api/v1/chat/completions

Indexing issues

If you are having persistent errors with indexing, our recommendation is to rebuild your index from scratch. Note that for large codebases this may take some time. This can be accomplished using the following command: Continue: Rebuild codebase index.

Agent mode is unavailable or tools aren’t working

If Agent mode is grayed out or tools aren’t functioning properly, this is likely due to model capability configuration issues.

Continue uses system message tools as a fallback for models without native tool support, so most models should work with Agent mode automatically.

Check if your model has tool support

Not all models support native tool/function calling, but Continue will automatically use system message tools as a fallback
Try adding capabilities: ["tool_use"] to your model config to force tool support
Verify your provider supports function calling or that system message tools are working correctly

Tools Not Working

If tools aren’t being called:

Ensure tool_use is in your capabilities
Check that your API endpoint actually supports function calling
Some providers may use different function calling formats

Images Not Uploading

If you can’t upload images:

Add image_input to capabilities
Ensure your model actually supports vision (e.g., gpt-4-vision, claude-3)
Check that your provider passes through image data

Add capabilities

If Continue’s autodetection isn’t working correctly, you can manually add capabilities in your config.yaml:

models:
  - name: my-model
    provider: openai
    model: gpt-4
    capabilities:
      - tool_use
      - image_input

Verify with provider

Some proxy services (like OpenRouter) or custom deployments may not preserve tool calling capabilities. Check your provider’s documentation.

Verifying Current Capabilities

To see what capabilities Continue detected for your model:

Check the mode selector tooltips - they indicate if tools are available
Try uploading an image - if disabled, the model lacks image_input
Check if Agent mode is available - requires tool_use

See the Model Capabilities guide for complete configuration details.

Android Studio - “Nothing to show” in Chat

This can be fixed by selecting Actions > Choose Boot runtime for the IDE then selecting the latest version, and then restarting Android Studio. See this thread for details.

I received a “Codebase indexing disabled - Your Linux system lacks required CPU features (AVX2, FMA)” notification

We use LanceDB as our vector database for codebase search features. On x64 Linux systems, LanceDB requires specific CPU features (FMA and AVX2) which may not be available on older processors. Most Continue features will work normally, including autocomplete and chat. However, commands that rely on codebase indexing, such as @codebase, @files, and @folder, will be disabled. For more details about this requirement, see the LanceDB issue #2195.

Ollama Issues

For a comprehensive guide on setting up and troubleshooting Ollama, see the Ollama Guide.

Unable to connect to local Ollama instance

If you’re getting “Unable to connect to local Ollama instance” errors:

Verify Ollama is running: Check http://localhost:11434 in your browser - you should see “Ollama is running”
Start Ollama properly: Use ollama serve (not just ollama run model-name)
Check your config: Ensure your config.yaml has the correct setup:

models:
  - name: llama3
    provider: ollama
    model: llama3:latest

Connection failed to remote Ollama (EHOSTUNREACH/ECONNREFUSED)

When connecting to Ollama on another machine:

Configure Ollama to listen on all interfaces:
- Set environment variable: OLLAMA_HOST=0.0.0.0:11434
- For systemd: Edit /etc/systemd/system/ollama.service and add under [Service]:
  Environment="OLLAMA_HOST=0.0.0.0:11434" Environment="OLLAMA_ORIGINS=*"
- Restart Ollama: sudo systemctl restart ollama
Update your Continue config:

models:
  - name: llama3
    provider: ollama
    apiBase: http://192.168.1.136:11434  # Use your server's IP
    model: llama3:latest

Check firewall settings: Ensure port 11434 is open on the server

Ollama not working in WSL

For WSL users having connection issues:

Windows 11 22H2+ (Recommended)

Create or edit %UserProfile%\.wslconfig:

[wsl2]
networkingMode=mirrored

Then restart WSL: wsl --shutdown

Older Windows/WSL versions

In PowerShell (as Administrator):

# Add firewall rules
New-NetFireWallRule -DisplayName 'WSL Ollama' -Direction Inbound -LocalPort 11434 -Action Allow -Protocol TCP
New-NetFireWallRule -DisplayName 'WSL Ollama' -Direction Outbound -LocalPort 11434 -Action Allow -Protocol TCP

# Get WSL IP (run 'ip addr' in WSL to find eth0 IP)
# Then add port proxy (replace <WSL_IP> with your actual IP)
netsh interface portproxy add v4tov4 listenport=11434 listenaddress=0.0.0.0 connectport=11434 connectaddress=<WSL_IP>

Docker container can’t connect to host Ollama

When running Continue or other tools in Docker that need to connect to Ollama on the host: Windows/Mac: Use host.docker.internal:

models:
  - name: llama3
    provider: ollama
    apiBase: http://host.docker.internal:11434
    model: llama3:latest

Linux: Use the Docker bridge IP (usually 172.17.0.1):

models:
  - name: llama3
    provider: ollama
    apiBase: http://172.17.0.1:11434
    model: llama3:latest

Docker run command: Add host mapping:

docker run -d --add-host=host.docker.internal:host-gateway ...

Parse errors with remote Ollama

If you’re getting parse errors with remote Ollama:

Verify the model is installed on the remote:
```
OLLAMA_HOST=192.168.1.136:11434 ollama list
```

Install missing models:

OLLAMA_HOST=192.168.1.136:11434 ollama pull llama3

Check URL format: Ensure you’re using http:// not https:// for local network addresses

Local Assistant

Managing Local Secrets and Environment Variables

For running Continue completely offline without internet access, see the Running Continue Without Internet guide. Continue supports multiple methods for managing secrets locally, searched in this order:

Workspace .env files: Place a .env file in your workspace root directory
Workspace Continue folder: Place a .env file in <workspace-root>/.continue/.env
Global .env file: Place a .env file in ~/.continue/.env for user-wide secrets
Process environment variables: Use standard system environment variables

Creating `.env` files

Create a .env file in one of these locations:

Per-workspace: <workspace-root>/.env or <workspace-root>/.continue/.env
Global: ~/.continue/.env

Example .env file:

OPENAI_API_KEY=sk-...
ANTHROPIC_API_KEY=sk-ant-...
CUSTOM_API_URL=https://api.example.com

Using secrets in config.yaml

Reference your local secrets using the secrets namespace:

models:
  - provider: openai
    apiKey: ${{ secrets.OPENAI_API_KEY }}

Hub-managed secrets

For centralized team secret management, use ${{ inputs.SECRET_NAME }} syntax in your config.yaml and manage them at https://hub.continue.dev/settings/secrets:

models:
  - provider: openai
    apiKey: ${{ inputs.OPENAI_API_KEY }}

Important notes

Never commit .env files to version control - add them to .gitignore
The .env file uses standard dotenv format (KEY=value, no quotes needed)
Secrets are loaded when Continue starts, so restart your IDE after changes
Local .env files take precedence over Hub secrets when both exist

Troubleshooting secrets

If your API keys aren’t being recognized:

Check the .env file is in the correct location
Ensure there are no quotes around values in the .env file
Restart your IDE after adding/changing secrets
Verify the variable name matches exactly (case-sensitive)
Check that your .env file has proper line endings (LF, not CRLF on Windows)

Using Model Addons Locally

You can leverage model addons from the Continue Hub in your local assistant configurations using the uses: syntax. This allows you to reference pre-configured model blocks without duplicating configuration.

Requirements

You must be logged in to Continue
Internet connection is required (model addons are fetched from the hub)

Usage

In your local config.yaml, reference model addons using the format provider/model-name:

name: My Local Assistant
version: 0.0.1
schema: v1
models:
  - uses: ollama/llama3.1-8b
  - uses: anthropic/claude-3.5-sonnet
  - uses: openai/gpt-4

With local configuration

You can combine hub model addons with local models:

name: My Local Assistant
version: 0.0.1
schema: v1
models:
  # Hub model addon
  - uses: anthropic/claude-3.5-sonnet
  
  # Local model configuration
  - name: Local Ollama
    provider: ollama
    model: codellama:latest
    apiBase: http://localhost:11434

Override addon settings

You can override specific settings from the model addon:

models:
  - uses: ollama/llama3.1-8b
    override:
      apiBase: http://192.168.1.100:11434  # Use remote Ollama server
      roles:
        - chat
        - autocomplete

This feature allows you to maintain consistent model configurations across teams while still allowing local customization when needed.

How do I reset the state of the extension?

Continue stores its data in the ~/.continue directory (%USERPROFILE%\.continue on Windows). If you’d like to perform a clean reset of the extension, including removing all configuration files, indices, etc, you can remove this directory, uninstall, and then reinstall.

Still having trouble?

You can also join our Discord community here for additional support and GitHub Discussions. Alternatively, you can create a GitHub issue here, providing details of your problem, and we’ll be able to help you out more quickly.

Getting Started

Features

Customization

Help

​Networking Issues

​Configure Certificates

​VS Code Proxy Settings

​code-server

​Changes to assistants not showing in VS Code

​I installed Continue, but don’t see the sidebar window

​I’m getting a 404 error from OpenAI

​I’m getting a 404 error from OpenRouter

​Indexing issues

​Agent mode is unavailable or tools aren’t working

​Check if your model has tool support

​Tools Not Working

​Images Not Uploading

​Add capabilities

​Verify with provider

​Verifying Current Capabilities

​Android Studio - “Nothing to show” in Chat

​I received a “Codebase indexing disabled - Your Linux system lacks required CPU features (AVX2, FMA)” notification

​Ollama Issues

​Unable to connect to local Ollama instance

​Connection failed to remote Ollama (EHOSTUNREACH/ECONNREFUSED)

​Ollama not working in WSL

​Windows 11 22H2+ (Recommended)

​Older Windows/WSL versions

​Docker container can’t connect to host Ollama

​Parse errors with remote Ollama

​Local Assistant

​Managing Local Secrets and Environment Variables

​Creating .env files

​Using secrets in config.yaml

​Hub-managed secrets

​Important notes

​Troubleshooting secrets

​Using Model Addons Locally

​Requirements

​Usage

​With local configuration

​Override addon settings

​How do I reset the state of the extension?

​Still having trouble?

Networking Issues

Configure Certificates

VS Code Proxy Settings

code-server

Changes to assistants not showing in VS Code

I installed Continue, but don’t see the sidebar window

I’m getting a 404 error from OpenAI

I’m getting a 404 error from OpenRouter

Indexing issues

Agent mode is unavailable or tools aren’t working

Check if your model has tool support

Tools Not Working

Images Not Uploading

Add capabilities

Verify with provider

Verifying Current Capabilities

Android Studio - “Nothing to show” in Chat

I received a “Codebase indexing disabled - Your Linux system lacks required CPU features (AVX2, FMA)” notification

Ollama Issues

Unable to connect to local Ollama instance

Connection failed to remote Ollama (EHOSTUNREACH/ECONNREFUSED)

Ollama not working in WSL

Windows 11 22H2+ (Recommended)

Older Windows/WSL versions

Docker container can’t connect to host Ollama

Parse errors with remote Ollama

Local Assistant

Managing Local Secrets and Environment Variables

Creating `.env` files

Using secrets in config.yaml

Hub-managed secrets

Important notes

Troubleshooting secrets

Using Model Addons Locally

Requirements

Usage

With local configuration

Override addon settings

How do I reset the state of the extension?

Still having trouble?