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Learn how to self-host Langfuse, connect it to vLLM, and build full LLM observability with traces, tokens, latency, and dashboards -- from scratch.

Learn how to train Kimi-K2 using DeepSeek-V3, Mixture-of-Experts, and MuonClip for efficient, scalable open-source LLM development.

Harden a semantic cache for LLMs: add TTL validation, confidence scoring, deduplication, and poisoning prevention for production-ready LLM systems.

Build a semantic cache for LLMs using FastAPI, Redis, and cosine similarity to cut latency and cost with exact-match and semantic cache hits.