Till JS 56ffcbac39 feat: add Ollama memory optimization, LLM metrics, and chat streaming ... Three improvements to the unified LLM infrastructure: 1. Ollama memory optimization (scripts/mac-mini/configure-ollama.sh): - OLLAMA_KEEP_ALIVE=5m → models unload after 5min idle (saves 3-16GB RAM) - OLLAMA_NUM_PARALLEL=1 → predictable memory usage - OLLAMA_MAX_LOADED_MODELS=1 → max 1 model in RAM at a time 2. Request-level metrics in @manacore/shared-llm: - LlmRequestMetrics interface (model, latency, tokens, fallback detection) - LlmMetricsCollector class with summary stats (for health endpoints) - Optional onMetrics callback in LlmModuleOptions - Automatic metrics emission in chatMessages() (success + error) 3. Chat streaming (token-by-token SSE): - Backend: POST /chat/completions/stream SSE endpoint - OllamaService.createStreamingCompletion() via llm.chatStreamMessages() - ChatService.createStreamingCompletion() with upfront credit consumption - Web: chatApi.createStreamingCompletion() SSE consumer - Chat store: sendMessage() now streams tokens into assistant message - UI updates reactively as each token arrives Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>		2026-03-24 09:41:33 +01:00
..
backend	feat: add Ollama memory optimization, LLM metrics, and chat streaming	2026-03-24 09:41:33 +01:00
landing	feat(analytics): add automatic CTA tracking to all 10 landing pages	2026-03-22 19:13:24 +01:00
mobile	refactor(auth): standardize mobile auth return format to { success, error }	2026-03-23 12:59:13 +01:00
web	feat: add Ollama memory optimization, LLM metrics, and chat streaming	2026-03-24 09:41:33 +01:00