Model Releases
What are the most frustrating silent failures you've encountered with local LLMs?
I've been building a small tool opensource project that sits between applications and local LLM servers (starting with Ollama) to diagnose silent inference failures instead of just showing logs. Thing
I've been building a small tool opensource project that sits between applications and local LLM servers (starting with Ollama) to diagnose silent inference failures instead of just showing logs. Things like: context limits empty outputs reasoning budget issues misconfigured context windows Before I spend more time building it, I'd like to understand what problems people actually run into**.** For example, the one that cost me a week: Ollama truncates a prompt that does not fit the context window and still returns 200. No warning. It drops from the front, so the system prompt goes first. prompt_eval_count in the response tells you how many tokens the model actually read, and nobody looks at it. Curious whether people here have hit others in the same category. what do u think about this project ? I can share GitHub link aswell submitted by /u/klncgty [link] [comments]
Related
- Built a Mac app that actually uses Ollama for work, not just chat — with a calibration step for models with flaky tool calling
- I built an MCP bridge that connects AI coding tools (Kiro, Claude, Cursor) to a local Ollama instance — still in development, feedback welcome
- A tool to get Claude Code-style reliability from fully local models
- Released a Windows Agent Server for Reins/Ollama with Self-Healing Execution Loop (Standalone .EXE included)
Source: r/ollama | 2026-08-27