r/OpenAssistant

Chimera: an open-source, self-hostable agent that runs on local models (any OpenAI-compatible endpoint) and can fuse several at once
▲ 17 r/OpenAssistant+8 crossposts

Chimera: an open-source, self-hostable agent that runs on local models (any OpenAI-compatible endpoint) and can fuse several at once

I've been building an open-source agent (Apache-2.0) and wanted to share it here because it's designed to be fully local and self-hostable: it talks to any OpenAI-compatible endpoint, so Ollama / llama.cpp / vLLM / LM Studio all work as the backend. No cloud lock-in, your keys and data stay yours.

The core idea is LLM-Fusion: for the hard steps it can run a panel of models on the same prompt, have a judge model cross-check them (consensus / contradictions / blind spots), and a synthesizer write the final answer. Locally this is fun because you can mix a few small local models and let them cross-check each other. A cost/latency-aware router keeps easy turns on a single model so you're not paying panel latency for everything.

Beyond that it's a full agent: plan -> act -> verify-or-revert (it runs your tests and treats the result as ground truth), layered memory (SQLite + FTS recall, cross-session profile, consolidation), a governance kernel, cron/proactive jobs, MCP client + OpenAPI-to-tool import, and an isolated subagent/crew layer (parallel git worktrees with per-worker verify gates). Runs on a laptop or a $5 VPS via Docker.

Honest status: it's alpha - 463 tests, mypy --strict clean, but no production mileage yet. Local reasoning quality obviously depends on the models you point it at, so I'd genuinely love to hear which local models people find good enough to actually drive an agent loop (reliable tool use + self-correction) - that's the make-or-break for going fully local.

Repo: https://github.com/brcampidelli/chimera-agent

▲ 5 r/OpenAssistant+1 crossposts

Let LLMs control Android apps in the background – open-source project, no root required

I built an open-source prototype that connects LLMs (via OpenAI-compatible APIs) to real Android apps – and it runs completely in the background.

The AI doesn’t just generate text – it actually does things: tap, type, scroll, long-press, copy/paste, go back. It’s like giving an LLM a phone to use, but on a virtual screen that doesn’t interfere with what you’re doing on your physical phone.

Key bits:

· Works with any OpenAI-compatible endpoint that supports streaming + tool calls

· The model receives UI node trees (or OCR results) and responds with tool calls

· All actions are executed on the virtual display – not your main screen

· Runs on any Android 10+ device – no root, no special hardware

If you’ve been wanting to experiment with phone-controlling agents but didn’t want to buy a dedicated device, this might be useful.

GitHub: https://github.com/android-notes/ShadowAuto

Demo video: https://github.com/android-notes/ShadowAuto/blob/main/shadowauto.mp4

Happy to discuss the architecture – the VirtualDisplay setup, the tool-call loop, OCR fallback, etc. Let me know what you think!

u/Legal-System-1617 — 1 day ago