Built a Mac app that actually uses Ollama for work, not just chat — with a calibration step for models with flaky tool calling

Most Ollama frontends I've tried are chat UIs with tool calling bolted on as an afterthought, which is fine until you actually try to make a small local model do multi-step work and it silently emits broken JSON. I built Ghost around the opposite assumption: the tool harness is the point, chat is the wrapper. What that looks like with Ollama specifically: On first launch it runs a probe against your loaded model to fingerprint what it can actually handle (native tool calls vs JSON mode vs prompt-injected tools). Small models that advertise function calling but flake in practice get routed through the mode they can actually pass. Means Qwen 2.5, Hermes, Llama 3.1 in the 7–8B range become genuinely usable with tools instead of hit-or-miss. ~78 tools available to the model: file ops, document generation (docx/pdf/pptx/xlsx), Calendar, Reminders, Notes, iMessage, screen OCR, some Mac controls. Four permission tiers, everything off by default, undo journal on write actions. RAG is local SQLite + FTS5 over folders you opt in. No embeddings API call, no vector DB, no subscription. Model never touches your filesystem directly — it emits a tool call and Swift code on my side runs the actual op. Same model on the same host can't reach anything you didn't grant. No API key, no network egress when you use Ollama. If you also have LM Studio installed it'll pick that up too. Full disclosure: it's my app, paid ($14.99 one-time, 24-hour trial, no subscription). Posting because the Ollama integration is the path I actually built for and I'd like feedback from people using Ollama for real work. Especially interested in which models you've had tool-calling grief with — good candidates to add to my probe test set. Links: integratedagentics.com/ghost · github.com/ryuhemingway/Ghost-App submitted by /u/Tunashavetoes [link] [comments]

Source: r/ollama | 2026-08-14

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