agf-wiring-apple-llm
SolidUse when wiring LLM features into the Apple client (macOS / iOS) — streaming chat via the FastAPI multi-LLM gateway, or on-device inference (Apple Foundation Models / Core ML). Provides the route decision (gateway vs on-device), streaming transport pattern, env/config contract, offline & cost guardrails, and minimum verifications before declaring the integration done.
Install
Quality Score: 85/100
Skill Content
Details
- Author
- pcliangx
- Repository
- pcliangx/AppGenesisForge
- Created
- 4 months ago
- Last Updated
- 1 months ago
- Language
- Python
- License
- MIT
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
agf-wiring-multi-llm-sdk
Use when wiring up or switching between China-domestic LLM providers (DeepSeek, Doubao/Volc Ark, Qwen/DashScope, MiniMax). Provides OpenAI-compatible adapter pattern, env-var contracts, fallback strategy, cost guardrails, and minimum verifications before declaring integration done.
llm-integration
Use when integrating an LLM API into an application. Covers streaming, retries and rate limits, timeouts, caching, fallback across providers, and the production concerns that a tutorial integration ignores.
llm-patterns
Patterns for building production-grade LLM features — prompt engineering, retrieval-augmented generation (RAG), evaluation harnesses, guardrails, cost control, hallucination mitigation, structured output, agentic loops. Stack-agnostic; recipes target Anthropic Claude (Opus 4.7 / Sonnet 4.6 / Haiku 4.5) and OpenAI as the two reference providers. Use when adding an LLM feature, designing a RAG system, writing an eval suite, or hardening an agent loop. Pairs with claude-sdk-integration (raw Claude SDK) and observability (LLM telemetry).