LineLoom v1.2.0: A Native VS Code Control Center for Local Ollama Autocomplete

LineLoom v1.2.0 is now available as a stable release on GitHub, with updated distribution through Visual Studio Marketplace and Open VSX.

This release focuses on making local AI-powered code completion easier to understand, configure, and control directly from Visual Studio Code.

What is LineLoom?

LineLoom is a free, MIT-licensed, open-source VS Code extension that brings AI-powered inline code suggestions to your editor using Ollama.

Instead of requiring an account with a hosted AI provider, LineLoom allows developers to use their own installed coding models.

The extension provides native inline suggestions, manual and automatic completion triggers, configurable model selection, privacy safeguards, and developer-controlled settings.

Local Ollama inference is the default. Explicitly configured and approved remote HTTPS endpoints are also supported.

What's new in v1.2.0?

1. A more informative native Control Center

One of the most noticeable improvements is the native LineLoom Activity Bar sidebar.

The Control Center brings together information and actions that developers previously needed to access through different commands.

It includes:

Completion and configuration status
Selected default and language-specific models
Active-editor eligibility information
Language controls
Workspace privacy and endpoint status
Shortcuts to diagnostics and connection checks

The sidebar is built around native VS Code UI components and does not initiate inference merely because the user opens it.

2. Clearer generation and connection states

LineLoom now provides more useful information about the completion engine.

The interface can distinguish between states such as ready, generating, disabled, unavailable, and error.

These distinctions matter because having a model name configured does not necessarily mean that Ollama is currently running or reachable.

The new status information aims to make configuration issues easier to identify.

3. Privacy-friendly performance diagnostics

v1.2.0 improves the extension's local session diagnostics.

The completion engine can report aggregated information, including:

Completion requests and suggestions
Cancellation counts
Cache hits
Typed-continuation reuse
Empty results and failures
Optional measured average latency

These statistics are held in memory rather than collected through a built-in telemetry service.

Average latency is shown only when performance diagnostics have been enabled and a valid sample has been collected.

4. Better Ollama error handling

The extension now provides clearer guidance for several categories of problems, including:

Unavailable Ollama servers
Missing models
Request timeouts
Authorization failures
Malformed or oversized responses

The goal is to help developers troubleshoot issues without exposing raw server error responses unnecessarily.

5. Safer model discovery

The model-selection workflow has also been hardened.

LineLoom validates returned model names, avoids duplicate entries, and rejects malformed or unreasonable model catalogs.

It also discards outdated model-discovery results when endpoint settings or remote approval change.

These improvements are particularly important for developers working with configurable inference endpoints.

Supported programming languages

LineLoom supports native inline completions for nine registered language IDs:

Python, JavaScript, TypeScript, Rust, Kotlin, Go, Java, C, and C++.

JSX and TSX are also handled through their corresponding JavaScript and TypeScript configurations.

Go, Java, C, and C++ remain experimental.

C# and Dart are not currently implemented in v1.2.0.

How to install LineLoom

Step 1: Install the extension

Visual Studio Marketplace:

https://marketplace.visualstudio.com/items?itemName=SanskarCodes.lineloom

Open VSX Registry:

https://open-vsx.org/extension/SanskarCodes/lineloom

Alternatively, download the stable VSIX from GitHub:

https://github.com/sanskarIN/LineLoom/releases/tag/v1.2.0

Step 2: Install Ollama

Download Ollama from:

https://ollama.com/download

Step 3: Install a compatible coding model

For example:

ollama pull qwen2.5-coder:1.5b

Model requirements and performance depend on the model and hardware.

Step 4: Configure LineLoom

Open a trusted project in VS Code.

Use the LineLoom Control Center or Quick Actions to choose the installed model and check your Ollama connection.

You can then trigger completions manually or use the configured automatic suggestion behavior.

Privacy and security

LineLoom is local-first, but it's important to understand what that means.

By default, completion context is sent to a locally configured Ollama endpoint.

The extension does not include built-in telemetry or automatically index an entire repository.

It also applies workspace trust checks, path exclusions, and additional inference permission checks.

If you explicitly configure and approve a remote HTTPS endpoint, relevant code context can be transmitted to that server.

For sensitive projects, review the privacy settings before enabling inference.

Testing and release status

v1.2.0 is a stable-channel GitHub release, not a pre-release.

Automated checks include cross-platform CI, mocked Ollama integration, package verification, and a VS Code CLI installation smoke test.

Some manual acceptance work remains open, including real-model completion quality, CPU/GPU latency, hands-on cross-platform editor checks, and accessibility verification.

The project tracks these remaining checks publicly.