GitHub VS LM Studio
Compare GitHub VS LM Studio and see what are their differences
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GitHub LM StudioBased on our record, GitHub seems to be a lot more popular than LM Studio. While we know about 2473 links to GitHub, we've tracked only 57 mentions of LM Studio. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Is published at https://github.com/.keys so an SSH server to which you connect could do a reverse lookup. This is the reason why my ~/.ssh/config has those 2 lines at the end:- Source: Hacker News / 5 days agoHost *.
All of this assumes you can actually inspect what the agent did โ the real inputs after resolution, the real tool outputs, the real intermediate steps. That is the other half of the workflow. AgentLens captures the trace: every model and tool step, resolved inputs, raw outputs. agent-eval scores and gates the output; AgentLens gives you the unforgeable, agent-didn't-author trace data for Tier 1+2 to score against... - Source: dev.to / 6 days ago
# git: the API token, plus the credential used for the push Kubectl create secret generic foreman-github \ --from-literal=GITHUB_TOKEN="$GITHUB_TOKEN" -n foreman-system Kubectl create secret generic foreman-git-credentials \ --from-literal=token="$GITHUB_TOKEN" -n foreman-system Helm upgrade foreman llmkube/foreman -n foreman-system --reuse-values \ --set agent.githubToken.secretName=foreman-github \ ... - Source: dev.to / 6 days ago
This is why eval and observability ship as a unit, not as separate purchases. agent-eval scores and gates the output โ the tiers above, drift, hallucination. AgentLens captures the trace of how the agent got there: every model step and tool call, the resolved inputs, the raw outputs, the trajectory. Two things fall out of that:. - Source: dev.to / 16 days ago
The real fragility is in trying to constrain arguments. The docs are explicit that a pattern like Bash(curl http://github.com/ *) fails to do what it looks like it does. It won't match curl -X GET http://github.com/... (option before the URL), curl https://github.com/... (different protocol), curl -L http://bit.ly/xyz (redirects to GitHub), URL=http://github.com && curl $URL (variable), or curl http://github.com... - Source: dev.to / 17 days ago
They hid it well at the bottom of the page: https://lmstudio.ai/. - Source: Hacker News / 18 days ago
A good place to browse is the LocalLLaMa subreddit. [0] A good software to start is LM Studio [1]. Another popular alternative is Ollama [2]. A better software when you're used to it all is llama.cpp as it's usually a bit faster and more frequently updated [3]. A good place to get models is HuggingFace, particularly the Unsloth models [4] Most popular models lately to run on "regular" gaming PC's, workstations,... - Source: Hacker News / about 1 month ago
LM Studio wraps the same inference engine in a desktop application with a visual model browser, one-click downloads from Hugging Face, and a built-in chat interface. - Source: dev.to / about 2 months ago
LM Studio is the reference standard for running local models. It's not really an "AI client" in the workspace sense โ it's a local inference engine with a chat UI attached. Its MLX backend on Apple Silicon is noticeably faster than Ollama for many models, especially on larger ones, though both now use MLX on Mac so the gap has narrowed over time. The built-in model browser lets you discover, download, and run... - Source: dev.to / about 2 months ago
Fully offline: Point it at Ollama or LM Studio. Zero cost, nothing leaves your network. - Source: dev.to / about 2 months ago
GitLab - Create, review and deploy code together with GitLab open source git repo management software | GitLab
Ollama - The easiest way to run large language models locally
BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.
GPT4All - A powerful assistant chatbot that you can run on your laptop
VS Code - Build and debug modern web and cloud applications, by Microsoft
Jan.ai - Run LLMs like Mistral or Llama2 locally and offline on your computer, or connect to remote AI APIs like OpenAIโs GPT-4 or Groq.