Show HN: Self tuning chat exposing it's semantic and agentic cache
The article discusses a new self-tuning chat system that utilizes semantic and agentic caching. It highlights the differences between Valkey, Redis, and Dragonfly, focusing on performance and functionality. Additionally, it provides insights into cache metrics and migration strategies between different database systems.
- ▪The chat system is backed by live documentation with semantic caching and tool result caching.
- ▪Valkey is compared to Redis and Dragonfly in terms of performance and capabilities.
- ▪The article includes information on cache metrics and how to migrate from Redis to Dragonfly.
Opening excerpt (first ~120 words) tap to expand
RESP-compatible DBs and BetterDBValkey · Redis · Dragonfly · BetterDB docs · semantic and kv/agentic cache demoAsk about Valkey, Redis, Dragonfly, or BetterDBBacked by live documentation with semantic caching and tool result caching. Watch the metrics panel to see cache hits in real time.What is Valkey and how does it differ from Redis?How does Dragonfly compare to Valkey for performance?Explain the FT.SEARCH KNN vector search syntaxWhat does BetterDB's semantic cache do?How do I migrate from Redis to Dragonfly?When should I use a Bloom filter vs a Set?How does valkey-search differ from RediSearch?Ask a questionSendCache MetricsAll-timeThis sessionAsk a question to see per-turn cache metrics.Powered by @betterdb/agent-cache & @betterdb/semantic-cacheAlso in Python: agent-cache-py ·…
Excerpt limited to ~120 words for fair-use compliance. The full article is at BetterDB Playground.
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