Inside Custom AI Providers: Multi-Model Routing in aiFetchlyDirect Answer: Power users optimize LLM latency, reasoning quality, and API expenses by configuring aiFetchly's Custom AI Provider engine to route distinct tasks across local and cloud models. By supp1d ago · 3 min readaifetchly-app.hashnode.dev
Inside AI Providers: Zero-Cloud Ollama & vLLM in aiFetchlyDirect Answer: aiFetchly allows software engineers to bypass cloud LLM subscriptions by routing AI Chat through custom OpenAI-compatible inference servers including Ollama, vLLM, and LM Studio. The de2d ago · 3 min readaifetchly-app.hashnode.dev
Inside AI Hooks: Intercepting & Gating Tool Calls in aiFetchlyInside AI Hooks: Intercepting & Gating Tool Calls in aiFetchly Direct Answer: The aiFetchly lifecycle hooks subsystem provides developers with deterministic, in-process runtime governance over AI too3d ago · 3 min readaifetchly-app.hashnode.dev
Step-by-Step: Packaging Custom AI Skills for aiFetchlyDirect Answer: Power users can extend aiFetchly by packaging modular Python or JavaScript AI Skills inside standard ZIP archives containing a validated manifest.json. This step-by-step guide walks thrOct 12 · 3 min readaifetchly-app.hashnode.dev