Codellm
User Local LLM and OPENAI to power your favorite IDE VSC.
Codellm launched on May 1, 2024 with 2 votes. The site was still online in September 2026, 2 years on.
What it does
This Visual Studio Code extension integrates with the Large Language Model (OLLAMA), an open-source language model, offering both offline and online functionality. It's designed to simplify generating code or answering queries directly within the editor.
Extension for Visual Studio Code - Use local LLM models or OpenAI right inside the IDE to enhance and automate your coding with AI-powered assistance
This Visual Studio Code extension integrates with the Large Language Model ( OLLAMA ), an open-source language model, offering both offline and online functionality. It's designed to simplify generating code or answering queries directly within the editor. This extension makes it easy for developers at any skill level to integrate advanced language models into their development process, enhancing productivity and creativity. Ask Codellm is also available when nothing is selected. For the other four commands, you can customize the exact prompt that will be sent to the AI by editing the extension settings in VSCode Preferences. There, you can also change the model that will be used for the…from marketplace.visualstudio.com
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1CodeJan 2026 · github.com · ▲569Just to clarify the background a bit. This project wasn’t planned as a big standalone release at first. On January 16, Ollama added support for an Anthropic-compatible API, and I was curious how far this could be pushed in practice. I decided to try plugging local Ollama models directly into a Claude Code-style workflow and see if it would actually work end to end. Here is the release note from Ollama that made this possible: https://ollama.com/blog/claude Technically, what I do is pretty straightforward: - Detect which local models are available in Ollama. - When…
Ollama – Run LLMs on your Mac2023 · github.com · ▲284Hi HN A few folks and I have been working on this project for a couple weeks now. After previously working on the Docker project for a number of years (both on the container runtime and image registry side), the recent rise in open source language models made us think something similar needed to exist for large language models too. While not exactly the same as running linux containers, running LLMs shares quite a few of the same challenges. There are "base layers" (e.g. models like Llama 2), specific configuration to run correctly (parameters, temperature, context window sizes etc). There's…
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