How to use CPIN: serve a human-approved answer verbatim
CPIN pins a golden answer that's served word-for-word for matching questions, with an audit trail of who approved it.
Notes from the nest · 980 posts
Engineering notes written by the people building Crowkis. Comparisons, use cases, economics, internals, security, operations, and nothing written just to rank.
CPIN pins a golden answer that's served word-for-word for matching questions, with an audit trail of who approved it.
On v0.2.2, throwing 16 threads at Crowkis got the same throughput as one. That's a real ceiling, we found it in our own harness, and here's both why it happened and how the embedding-deferral work lifts it.
Building contract analysis tools on the Mistral SDK? Add a semantic cache so the same clause questions across documents stop costing full price.
Building customer support bots on Ollama? Add a semantic cache so repeat questions from every customer, all day stop costing full price.
Building ecommerce assistants on Semantic Kernel? Add a semantic cache so the same product and policy questions across shoppers stop costing full price.
Building email drafting tools on LangChain? Add a semantic cache so similar drafts requested over and over stop costing full price.
PII scrubbing and right-to-erasure (CPII), reports what personal data is cached and executes right-to-erasure on request, so compliance is a command. Here's how Crowkis does it and why it matters for cost and safety.
Chat history is more than the last N turns. CSESSION stores a multi-turn buffer per session, bounded and TTL'd, with both recent-window reads and semantic search across the whole conversation.
CSOURCE links cache entries to the source they derived from, so when the source changes you can purge everything built on it in one move.
Building onboarding assistants on the Mistral SDK? Add a semantic cache so every new hire asking the same first questions stop costing full price.
Building coding assistants on Ollama? Add a semantic cache so the same explanations and boilerplate reasoning, dozens of times a day stop costing full price.
Building healthcare Q&A assistants on Semantic Kernel? Add a semantic cache so recurring policy and triage questions stop costing full price.
Building code review bots on LangChain? Add a semantic cache so the same review patterns across pull requests stop costing full price.
Multi-tenant isolation, namespaces keys per tenant and tags every entry, so one customer's answer can never be served to another. Here's how Crowkis does it and why it matters for cost and safety.
CTOOLSET caches a tool result keyed by tool plus exact arguments; CTOOLGET returns it, so a deterministic call runs once and serves many.
Add documents, auto-chunk them, search with metadata filters and reranking, a working retrieval pipeline without a separate vector database.
Building meeting-notes summarizers on the Mistral SDK? Add a semantic cache so similar summaries requested repeatedly stop costing full price.
Building RAG document search on Ollama? Add a semantic cache so the same questions re-running retrieval over the same corpus stop costing full price.
Building legal document assistants on Semantic Kernel? Add a semantic cache so the same clauses and questions across matters stop costing full price.
Building data analysis agents on LangChain? Add a semantic cache so repeated tool calls and the same analytical questions stop costing full price.