How to run local LLM web scraping 100% offline with GGUF models (Qwen, DeepSeek)?

[fintechdev]

I work in fintech, and we need to scrape and parse highly sensitive financial portals. Our compliance team has strictly forbidden sending any page data or DOM structures to OpenAI or Anthropic APIs.

I saw that RTILA X supports “offline AI agents.” Can I actually run a model like DeepSeek or Qwen locally to parse this data without the internet?

[RTILA_Support]

Hey @fintechdev! Yes, you absolutely can, and it’s built exactly for strict compliance environments like yours.

RTILA X has a built-in local AI engine powered by a dedicated llama-server sidecar. You don’t need to install Python or mess with command-line tools. Right from the UI, you can download quantized GGUF models (like Qwen, DeepSeek, or Llama 3) directly to your machine.

When you ask the AI to generate a scraping script or parse extracted data, the request is routed to localhost. The sidecar architecture ensures the heavy LLM processing runs in a separate background process, keeping your main UI snappy. It is 100% private - you can literally unplug your ethernet cable and the AI will still write and execute your web automation.

[IEVCEMC]

do we still need to connect with gemmine or can we use RTILA lite right after installing RTILA X?

[CommunityManager]

You can use it right after installing RTILA X, the model will be downloaded and run locally on your machine. If you decide you want to use Gemini or other cloud models later, you can always switch to using an OpenRouter API key.

[IEVCEMC]

I try to use it, but it’s tells me that RTILA model failed to installed…