Show HN: I open-sourced two AI agents with real memory (chat and voice, MIT)
A new open-source AI agent called SynapCores has been developed for customer support. This agent operates without dependencies, using a simple Python loop to manage memory and retrieval. It allows for persistent conversation memory, enabling follow-up questions to be answered based on previous interactions.
- ▪SynapCores is a framework-free AI agent designed for customer support.
- ▪The agent utilizes a simple Python loop for memory, retrieval, and text generation.
- ▪It features persistent memory, allowing it to recall past conversations for follow-up queries.
Opening excerpt (first ~120 words) tap to expand
synapcores-agent A real customer-support agent where the database is the memory. Watch the chat on the left; watch the engine remember, retrieve, and route on the right. A real, framework-free AI agent whose brain is SynapCores. Most "AI agent" stacks bolt together a vector DB, a graph DB, a cache, an LLM, and a framework (LangChain, etc.) with a lot of glue. This agent does none of that. It is a thin, dependency-free Python loop where SynapCores is the entire brain — memory, retrieval (RAG), semantic tool routing, state, and text generation — reached over plain HTTP. The point is to be agent-agnostic by being framework-free. There is no LangChain dependency. The agent is a few hundred lines of standard-library Python you can read top to bottom and fork in an afternoon.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.