I turned Jev into a (lousy) chatbot

Jev's new JevChat open‑source project turns the Jev language model into a conversational chatbot, with the code now publicly available on GitHub under the kyle-pena-nlp/jevchat repository. For website owners this release means an easy‑to‑deploy, self‑hosted AI conversational agent that can be embedded directly into site pages or support portals without relying on third‑party APIs. Because JevChat runs entirely on your own servers, all user queries and generated responses stay within your infrastructure, eliminating the data‑sharing concerns that come with cloud‑based bots. However, the model’s “lousy” performance and lack of built‑in content filters mean you’ll need to implement your own moderation layers to avoid unintentionally serving low‑quality or inappropriate replies. **Actionable tips:** 1. **Add a dedicated entry in your llms.txt** pointing to the JevChat endpoint (e.g., `User‑Agent: JevChat/1.0; Disallow: /private/`) so crawlers know which paths to avoid. 2. **Deploy a bot‑tracking pixel or server‑side log filter** that tags requests with the JevChat user‑agent, allowing you to separate genuine visitor traffic from AI‑generated queries in your analytics. 3. **Integrate a real‑time moderation webhook** (e.g., OpenAI’s content filter or a custom regex rule) into the JevChat response pipeline to block erotica, hate speech, or other prohibited content before it reaches users.