Search: “agents”

I've been working on something for this community (and other self-hosted communities) for almost 5 months now. Personally, I would grade it as probably the closest open source equivalent of Manus and

Hey everyone, Giving AI agents access to MCP tools or shell commands is awesome, but prompt injection is still a huge headache. If an agent reads an untrusted document containing `ignore previous inst

Our research team has been exploring an alternative approach to achieving interactivity and better responsiveness with LLM systems. One of the team members wrote up a post about it: https://research.y

AQuA's preprint uses 'recursive self-improvement' for a bounded research loop. It does not say the research-agent LM rewrites its own weights. The paper separates three objects: The language model dri

I am building a domain-specific AI agent powered by Ollama (using the qwen:2.5 model). For data retrieval, the agent utilizes multiple search APIs: DuckDuckGo Search (DDGS), Tavily, Serper, and Google

Hey all, I’ve been working on this in my spare time and finally feel ready to share it outside my own circles. Arbiter is a single binary for running agents locally. I originally built it because I wa

A community-shared open source CLI agent project posted to r/ollama, designed specifically for use with 8K token context windows in local Ollama-based LLM setups. Version 0.3 focuses on improving Olla

A Reddit post on r/ollama in which a developer shares a self-built, free and open-source dashboard for managing and interacting with AI agents powered by Ollama, enabling fully local and private LLM-b

Over the past several months, we conducted an empirical post-mortem investigation into 109 autonomous AI agent security incidents (cataloged with 193 falsification criteria across tool-use and multi-a

AI tools have given us a lot of slop research, but I'm not talking about that. I'm talking about real productivity acceleration due to AI tools (E.g. iterating ideas that would've taken multiple days

I built a benchmark called EchoNet. An agent gets a factual question, then searches a syntheic web I made before answering. Some of that web is seeded with misinformation: one fake page, a fake page r

Thanks to Unsloth Dynamic 3.0 quants coming in slightly leaner and better preserved, I settled on Qwen 3.8 27B (`UD_Q4_K_XL`) at 100K context as my daily driver for Hermes Agent and OpenCode. On an RT

WebWright is a Chrome browser extension that enables AI agents to automate web tasks directly within the browser, leveraging local models like those available through Ollama. The announcement on r/oll

last night I was messing around with Codex and threw in a stupid prompt: **“hey codex, find me a girlfriend. make no mistake”** I expected the usual AI answer. You know, go outside, join a hobby club,

I’m building a Polish General purpose legal Model that drafts documents, answers questions using legal sources, and has enough coding ability to handle some automation. The workflow is very tool-heavy

Hey everyone, Like a lot of people here, I’ve been experimenting with running models locally through Ollama. Athena started as a small experiment, but it quickly grew into something more, a modular Py

My hobby project skill-issue is an arena FPS in a single C file, about 34k lines, everything procedural. My test for local setups is to have an agent port it to a single file HTML version with three.j

Hi there. I have a Lenovo Yoga laptop (16GB LPDDR5, AMD Ryzen 7 8840HS, integrated GPU). I have downloaded Ollama and installed Qwen 2.5coder:3b llm. I have tried OpenClaw, and Qwen Code but it seems

That is the second comparison and the last one. I will not be spamming again ;) Continuation from: https://www.reddit.com/r/LocalLLaMA/comments/1vu0u2v/qwen_38_27b_pi_agent_vs_opencode/ That is one of

Hi r/LocalLLaMA 👋 Today we’re excited to release Muse Glimmer, a 30B open-weight model built specifically for local agent workflows. We’re releasing the weights to the community under a permissive Apa

Most agent memory setups run a model call on the way in. Something reads the turn, decides whether it's worth keeping, rewrites it into a 'memory', tags it with a type and an importance score. That's

Con ayuda de ChatGPT y con el modelo de Ollama, Qwen3:14b estoy creando un agente que corre local y tiene la iniciativa para pensar, investigar, aprender, generar propuestas y esperar mi autorización

An open-source agent self-reflection harness built on top of Ollama, shared in the r/ollama community, that enables locally run LLMs to evaluate and iteratively refine their own outputs. The project p

https://preview.redd.it/5w22g46ihssh1.png?width=2880&format=png&auto=webp&s=cbae24190847b3d80b919ce72d6703c9d1a5a52d The best agent experiences I tried (Dots/ GrokBot) all had an agent that can actual

We have SWE-bench, Terminal-Bench, OSWorld, BrowseComp, etc. But I haven’t seen a good apples-to-apples benchmark for platforms like OpenAI Agents, Anthropic’s agent stack, AWS AgentCore, Google’s age

Quick setup on linux: STEP 0: install/download llama.cpp, Freecad, your favourite gguf model - possibly with multimedia image reading capabilities (I've used Qwen3.8-27B-UD-Q4_K_M and relative mmproj-

Hi all! I've been building a local agent harness, but before writing the code, I wanted to get some intuition around whether (and how) structuring agent execution as a graph helps vs. standard tool-ca

For 6 months now I've been trying to make agentic coding work for me, using Pi and a handful 30-120B models (Qwens, Nemotrons, Leguna...etc). I'm not greedy either, I stick to decent quants, never qua

Arena AI's agentic benchmark ranks AI models on how well they orchestrate tools for real-world agentic tasks, based on signals like tool reliability, task completion, and steerability. The leaderboard

A discussion on building an AI-powered article generator using CrewAI and Ollama with specialized AI agents for research and writing to generate comprehensive articles on any topic. The solution runs

An open-source browser with built-in AI agents that emphasizes privacy and automation, enabling task automation through natural language without coding. The browser supports multiple AI providers incl

Hermes Agent provides a migration tool that imports OpenClaw setups into Hermes. The tool migrates your persona, memory, skills, configs, and API keys in a single command. The guide covers what gets m

I tested Mellum2.1-12B-A2.5B (Q8) locally using Pi and llama-server. All five tests were one-shot. Results were pretty mixed: - Pelican SVG, Browser OS, Minecraft: Poor results. - Bouncing Hexagon: Ph

Hey everyone! I’ve been working on a 100% local cognitive memory engine designed specifically to give multi-agent systems and NPC societies human-like memory. It's called Eternal Thread. Instead of ju

Following up on my previous post about my budget server setup (Intel N100 + RTX 5060 Ti 16GB), a few of you asked for a deeper dive into my actual inference config and real-world agentic performance.

Hello; I'm a semi-beginner at local AI. I've been experimenting with this tech for a while, and I still haven't found a proper harness that fits my models, hardware, and needs. My use case is pretty s

TL;DR: I am building a Windows-first local AI setup for people who want to try local LLMs without spending days choosing models, setting up Ollama, Docker, WSL, Open WebUI, agents, and tool permission

I’m building DesktopLab, an open-source local-first control plane for development agents. I recorded the setup boundary that most agent demos skip: DesktopLab detects the host, proposes the supported

sample Hey r/Ollama! If you're hooking up local agent tools and using Ollama to drive agentic workflows, you've probably downloaded a bunch of third-party SKILL packages or repos. I built a free open-

Let me try to explain this clearly, simply, and neatly. Originally, I just wanted to build a small WebUI adapter with an admin panel, but things escalated over the last few months. At first, I faced t

I've been building ANCHOR, a web automation agent that runs entirely on Ollama. You describe a task in plain language ('Register Maria Silva, IT department, contractor, and save'), point it at a site,

My setup is two RTX 5070 Ti 16GB cards (the second one is on an OCuLink dock) with 64GB of RAM, Ollama on Windows, and the agent runs on pi in WSL. Until last night the daily model was Qwen3.8 27B UD-

Row-Bot 5.0 is a major rebuild of the local-first AI assistant. The NiceGUI interface is gone, replaced by one React app across desktop, browsers, phones and tablets. The biggest change is how work is

RuntimeAI's September 2026 AI Security Report covered 126 incidents across 38 named organizations — 22 critical, 102 high severity. 53 of those incidents had AI either as the attack tool or the target

This experiment is live, you can inspect all the internal reasoning, memories, attempts here: https://artificium-covering-experiment.gr.bio/ The problem that the agent is trying to solve is a covering

Spent about two weeks convinced I had a prompting problem. My local Qwen3 agent would just stop. No error, no crash, finish_reason came back as 'stop' like the model had decided it was done. Except it