Skip to main content

Running a fully local AI Code Assistant with Continue–Part 2–Configuring the VSCode extension

In a previous posted I introduced you to Continue in combination with Ollama, as a way to run a fully local AI Code Assistant. In a first post I showed you how to download and install the necessary models and how to integrate it inside VSCode. We had a look at the chat integration and autocomplete. Today I want to continue by having a look at how we can configure the VSCode Addin.

I originally had planned to write about another feature of Continue, but when I opened VSCode today, I got the following error message:

Whoops! It seems that the configured language model was not available locally on my machine. And indeed when I took a look at the list of installed models, the ‘starcoder2:3b’ model wasn’t there:

Instead I had the ‘starcoder2:latest’ model installed. So let’s use this moment to show how you can configure the Continue VSCode Addin.

Therefore click on the ‘Gear’ icon in the bottom right corner of the Continue chat screen:

This will open a config.json file where we can edit and tweak a lot of the functionality in Continue:

Remark: For the full config.json schema, have a look here.

In our case, we only want to update the model used for the tab autocomplete:

Just hit Save to apply the changes.

Yes! Our autocomplete is back:

Great! Now we can focus on the next post where we take a look at the Edit and Actions features.

Remark: If you encounter any other issue, it is always a good idea to first check the console logs or LLM prompt logs:


 

More information

https://docs.continue.dev/troubleshooting

Popular posts from this blog

Podman– Command execution failed with exit code 125

After updating WSL on one of the developer machines, Podman failed to work. When we took a look through Podman Desktop, we noticed that Podman had stopped running and returned the following error message: Error: Command execution failed with exit code 125 Here are the steps we tried to fix the issue: We started by running podman info to get some extra details on what could be wrong: >podman info OS: windows/amd64 provider: wsl version: 5.3.1 Cannot connect to Podman. Please verify your connection to the Linux system using `podman system connection list`, or try `podman machine init` and `podman machine start` to manage a new Linux VM Error: unable to connect to Podman socket: failed to connect: dial tcp 127.0.0.1:2655: connectex: No connection could be made because the target machine actively refused it. That makes sense as the podman VM was not running. Let’s check the VM: >podman machine list NAME         ...

Cache stampede: when our cache turned against us

While investigating some performance issues, we ran into an ASP.NET Core API that cached a fairly expensive aggregation query for 60 seconds. Under normal load, that was fine: one request rebuilds the cache, everyone else reads from it. Under peak load, dozens of requests would arrive in that same expiry window, all see a cache miss, and all fire the same expensive query in parallel. The database didn't like that. That was the moment when our caching layer stopped helping and started hurting. A burst of requests comes in at the same time, all miss the cache, and all go hammer the database or the downstream API at once. That's a cache stampede . The cache was supposed to protect our backend, and for a few hundred milliseconds it did the opposite. Why this happens IMemoryCache.GetOrCreate (and its async sibling) looks like it protects you, but it doesn't add any locking on its own. Look at the naive version: public async Task<Report> GetReportAsync(string key) ...

Azure DevOps/ GitHub emoji

I’m really bad at remembering emoji’s. So here is cheat sheet with all emoji’s that can be used in tools that support the github emoji markdown markup: All credits go to rcaviers who created this list.