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Build apps with 500 models locally. No tracking, no cloud, just code

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I built CodinIT because I wanted that "Bolt-like" experience, but on my own terms.100% Open SourceThe core idea: You should be able to prompt a full-stack application into existence, but the environment should be local, the models should be swappable (Ollama/LM Studio support was a priority), and the output should be standard code you actually own.A few things I focused on:Context Management: One of the hardest parts was figuring out how to feed the right file context back to the LLM without blowing out the token limit. I’ve implemented a custom indexing approach to keep the "vibe coding" flow snappy.The "Local" Win: Since it runs locally, you can use it on a plane or in a coffee shop without burning through a data plan or worrying about API latency.Stack: It’s primarily focused on the Node.js ecosystem right now, as that's where I found the most consistent generation results.It’s definitely a work in progress. Specifically, I'm still fine-tuning how it handles large-scale refactors across multiple files, which is where most AI coders tend to trip up.I’m really curious to hear from this community—do you actually prefer using local models for this kind of work, or is the "intelligence gap" between a local Llama 3 and Claude 4.5 Sonnet still too big for your daily use?Site: https://codinit.dev

HN · launched Dec 21, 2025 · 6 upvotes (top 73%) · 0 views

Niche: ai app builders · 190 launches, 8 in the last 7 days ▼ -56% · Explore this niche →

Category and tags

  • Horizontal
  • Model & infra
  • Developer
  • AI-native
  • Commercial product

Visit website ↗ Source listing ↗

Could you build this?

Partial The chat UI and prompting interface are straightforward, but building an in-browser or local containerized full-stack execution sandbox (like WebContainers or Docker runtime orchestrator) with multi-model local LLM integration is non-trivial.

What it would actually take: The system requires a desktop or web orchestrator (Node.js/Go/Electron) that interacts with local LLM runtimes (Ollama/LM Studio via standard OpenAI-compatible endpoints) and a sandboxed execution environment (Docker or WebContainers via Node runtime in the browser) capable of installing NPM/Pip packages, running dev servers, hot-reloading, and handling file system diffs reliably. The hardest part is building resilient agentic file-editing loops that handle hallucinations when using smaller local models.

Discussion

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Competitors

Other products that read as similar to this one : 310 launches clear the similarity bar, closest 8 shown.

Attention rank: #255 of 311 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 52 days after the earliest competitor.

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