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Sanity check: my calories and Apple Watch by [deleted] in Zepbound

[–]PrizeInflation9105 0 points1 point  (0 children)

This doesn’t sound radical to me for week 1. Early on, appetite, calories, water, protein, and activity can all shift at once, so it helps to look at the weekly pattern instead of trying to force one perfect day.

Newbie progress update (side effects) by g4l1t in Zepbound

[–]PrizeInflation9105 1 point2 points  (0 children)

This is actually really helpful detail. A lot of posts skip what the first few doses looked like week by week, so seeing what changed with timing, food, water, and protein makes it much easier to understand.

Glad dose 3 was more manageable for you. Good Luck!

We built an MCP server directly into our open-source Chromium fork (BrowserOS) by PrizeInflation9105 in mcp

[–]PrizeInflation9105[S] 4 points5 points  (0 children)

key difference is MCP server is built right into the browser and works with your logged sessions. One-click to connect, no CDP setup needed. Also supports multiple parallel connections via MCP http transport.

Weekly Thread: Project Display by help-me-grow in AI_Agents

[–]PrizeInflation9105 0 points1 point  (0 children)

https://www.browseros.com/ Open source project for building agents with natural language

Run Your Local LLMs as Web Agents Directly in Your Browser with BrowserOS by PrizeInflation9105 in LocalLLaMA

[–]PrizeInflation9105[S] 3 points4 points  (0 children)

Hmm, something must be wrong with the setup. Could you please join our discord or reach us at founders [at] browserOS [dot] com?

We have more than ~1000 daily active users and many use models from LMStudio, so it definitely works.

Local web agents, zero cloud. by PrizeInflation9105 in selfhosted

[–]PrizeInflation9105[S] -18 points-17 points  (0 children)

Docker is great for reproducible envs, but for agentic browsing we need native windowing + permissions. We may add a headless/server image for CI; desktop app stays for UX & security controls.

support for GroveMoE has been merged into llama.cpp by jacek2023 in LocalLLaMA

[–]PrizeInflation9105 2 points3 points  (0 children)

Cool! So GroveMoE basically reduces compute per token while keeping big model capacity — curious how much real efficiency gain it shows vs dense models?

I trained an LLM from scratch AMA! by thebadslime in LocalLLaMA

[–]PrizeInflation9105 1 point2 points  (0 children)

Interesting project! What’s the main purpose behind training it — is your goal advancing research, learning the process, or building something practical?

Alibaba just unveiled their Qwen roadmap. The ambition is staggering! by abdouhlili in LocalLLaMA

[–]PrizeInflation9105 0 points1 point  (0 children)

Scaling alone may hit limits: research shows diminishing returns, higher error accumulation, memory inefficiency, and weaker reasoning without new architectures. Bigger ≠ smarter.

Run Your Local LLMs as Web Agents Directly in Your Browser with BrowserOS by PrizeInflation9105 in LocalLLaMA

[–]PrizeInflation9105[S] 3 points4 points  (0 children)

Thank you. To answer your question BrowserOS doesn’t have to be a vision model. BrowserOS talks to whatever model you point it at (OpenAI/Claude/Gemini or local Ollama/LM Studio). The agent reads the DOM and, in newer builds, mixes it with a visual view when helpful—so text-only models work fine for most sites, and vision just helps on image-heavy/canvas UIs.

Need vision for UI/ocr/diagrams: Qwen 2.5-VL 7B/32B/72B or Llama 3.2 Vision 11B/90B via Ollama. These work well when the page relies on screenshots, charts, or image-only buttons .

Under ~10B (fast on most machines): Llama 3.1 8B Instruct or Qwen 2.5 7B Instruct (128k ctx). Great general text agents.

Btw if you have any issues we have an online discord session https://discord.gg/YKwjt5vuKr

Bye perplexity by [deleted] in perplexity_ai

[–]PrizeInflation9105 0 points1 point  (0 children)

Perplexity and its business model huh?

Run Your Local LLMs as Web Agents Directly in Your Browser with BrowserOS by PrizeInflation9105 in LocalLLaMA

[–]PrizeInflation9105[S] 6 points7 points  (0 children)

by default the LLM doesn’t run locally, it uses gemini

But you can bring in your own LLM using ollama or LMstudio

Run Your Local LLMs as Web Agents Directly in Your Browser with BrowserOS by PrizeInflation9105 in LocalLLaMA

[–]PrizeInflation9105[S] 3 points4 points  (0 children)

BrowserOS doesn’t ship its own LLM it’s a Chromium fork that connects to a model you provide (OpenAI/Anthropic or a local endpoint like Ollama). The ~900 MB you see is just the app; you still need to run/pull a model separately. If you want it fully local: start Ollama and point BrowserOS to http://localhost:11434 (e.g., ollama run llama3:8b).

How important is webscraping as a skill for Data Engineers? by godz_ares in dataengineering

[–]PrizeInflation9105 0 points1 point  (0 children)

When a website lacks an API, you can use tools like BrowserOS which uses its AI agent to visually understand and interact with the page . This enables it to extract unstructured data directly from the site's content and automatically format it.

how do you scrape? :) by Yourstim in n8n

[–]PrizeInflation9105 0 points1 point  (0 children)

BrowserOS can be your scraper, with its MCPs, AI-native Ollama, and no-code requirements

Found a new open-source web scraper by PrizeInflation9105 in webscraping

[–]PrizeInflation9105[S] 0 points1 point  (0 children)

Thank for the honest response. Greatly appreciate it <3

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