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README.md

@@ -1,11 +1,10 @@
 ---
-title: Fetch Pup
-emoji: 🐶
+title: This is Fetch
+emoji: 🐕
 colorFrom: gray
 colorTo: yellow
 sdk: static
 pinned: false
-short_description: Dog-loving baseline chatbot. A zero-backend static demo
 ---
 
 # This is Fetch
@@ -17,21 +16,20 @@ Space. It runs entirely in the browser — no GPU, no Python, no backend.
 
 ## How it works
 
-Fetch answers using the same logic as the original Python reference:
+Fetch answers using a layered response pipeline:
 
+- A lightweight **intent matcher** that handles greetings, small talk, and
+  questions like "what can you do".
 - A small **keyword lookup** table (dogs, breeds, care, trivia, reactions).
   If the user's question contains a known keyword, the matching fact is
   returned verbatim.
-- Three **fallback replies** cover the "I don't know" case.
-- **Four-turn context** is kept in memory for the session.
+- Three **fallback replies** cover everything else.
 
-The generative path (BlenderBot-400M-distill in the original, or an
-LLM-backed helper in the Claude preview) is intentionally disabled in this
-static build. Static Spaces don't run Python or serve models, so the
-deterministic keyword-lookup path is the honest option here.
+There is no model running in this build. Static Spaces don't run Python or
+serve models, so the deterministic response pipeline is the honest option here.
 
-If you want the generative version, deploy the original `app.py` to a
-Gradio Space instead (`sdk: gradio`, CPU hardware is fine).
+The generative version, powered by Meta's BlenderBot-400M-distill, runs
+separately as a [Docker Space](https://huggingface.co/spaces/ElisaTrippetti/Fetch-Good-Boi).
 
 ## Files
 
@@ -48,4 +46,4 @@ Gradio Space instead (`sdk: gradio`, CPU hardware is fine).
 ## Credits
 
 Design and frontend: a set of explorations for *This is Fetch*.
-Reference model: [facebook/blenderbot-400M-distill](https://huggingface.co/facebook/blenderbot-400M-distill).
+Reference model: [facebook/blenderbot-400M-distill](https://huggingface.co/facebook/blenderbot-400M-distill).

chat-engine.jsx

@@ -1,7 +1,7 @@
 // chat-engine.jsx — shared chat logic for all Fetch variants.
-// Mirrors the Python reference: 4-turn context, keyword lookup, fallbacks.
-// Two backends: "claude" (window.claude.complete) and "local" (keyword
-// lookup + fallback only — the path HuggingFace Static Spaces will take).
+// Response pipeline: intent matching → keyword lookup → fallbacks.
+// Two backends: "claude" (window.claude.complete) and "local" (intent
+// matching + keyword lookup + fallbacks — the path HF Static Spaces take).
 
 const KNOWLEDGE_BASE = [
   ["domesticate",  "Dogs have been domesticated for at least 15,000 years, making them the oldest domesticated animal."],
@@ -34,6 +34,33 @@ const FALLBACKS = [
   "I'm not sure about that, but dogs are great!",
 ];
 
+const INTENTS = [
+  {
+    patterns: [/\b(hi|hello|hey)\b/i, /good (morning|afternoon|evening)/i],
+    response: "Hi! I'm Fetch Pup. Ask me something about dogs, or try the suggestions below.",
+  },
+  {
+    patterns: [/how are you/i, /how('s| is) it going/i, /what'?s up/i],
+    response: "Tail's wagging, thanks for asking! Got a dog question for me?",
+  },
+  {
+    patterns: [/what can you do/i, /what do you (know|do)/i, /\bhelp\b/i],
+    response: "I know a bunch of dog facts. Ask a question or try the suggestions — I'll do my best.",
+  },
+  {
+    patterns: [/who are you/i, /what are you/i],
+    response: "I'm Fetch Pup — a static chatbot demo. No model running, just intent matching and keyword lookup. But I know my dogs!",
+  },
+];
+
+function matchIntent(query) {
+  const q = query || "";
+  for (const intent of INTENTS) {
+    if (intent.patterns.some(p => p.test(q))) return intent.response;
+  }
+  return null;
+}
+
 const SUGGESTIONS = [
   "Tell me about border collies",
   "How good is a dog's sense of smell?",
@@ -93,6 +120,9 @@ function buildPrompt(history, userInput, fact, personality) {
 }
 
 async function generateReply({ userInput, history, backend, personality }) {
+  const intent = matchIntent(userInput);
+  if (intent) return { text: intent, fact: null };
+
   const fact = retrieveFact(userInput);
 
   if (backend === "claude" && typeof window !== "undefined" && window.claude?.complete) {
@@ -170,18 +200,18 @@ function useFetchChat({ backend = "claude", personality = "subtle" } = {}) {
   return { messages, pending, debug, send, reset };
 }
 
-// Rotating suggestion carousel — 3 chips visible, rotates on interval.
+// Suggestion carousel — picks 3 at random on each interval tick.
 function useRotatingSuggestions({ visible = 3, intervalMs = 4200 } = {}) {
-  const [offset, setOffset] = React.useState(0);
+  const [current, setCurrent] = React.useState(() =>
+    [...SUGGESTIONS].sort(() => Math.random() - 0.5).slice(0, visible)
+  );
   React.useEffect(() => {
-    const id = setInterval(() => setOffset(o => (o + 1) % SUGGESTIONS.length), intervalMs);
+    const id = setInterval(() =>
+      setCurrent([...SUGGESTIONS].sort(() => Math.random() - 0.5).slice(0, visible)),
+      intervalMs
+    );
     return () => clearInterval(id);
-  }, [intervalMs]);
-  const current = React.useMemo(() => {
-    const out = [];
-    for (let i = 0; i < visible; i++) out.push(SUGGESTIONS[(offset + i) % SUGGESTIONS.length]);
-    return out;
-  }, [offset, visible]);
+  }, [visible, intervalMs]);
   return current;
 }
 

debug-panel.jsx

@@ -125,9 +125,9 @@ function DebugAbout({ palette }) {
   return (
     <div style={{ lineHeight: 1.6, color: palette.fg, display: "flex", flexDirection: "column", gap: 10 }}>
       <div>Fetch Pup is a static browser demo — there is no model running.</div>
-      <div>Responses come from a small keyword lookup table: if your question contains a known word, the matching fact is returned verbatim. Otherwise you get one of three fallback replies.</div>
-      <div>The generative version, powered by Meta's BlenderBot-400M-distill, runs separately as a Gradio Space.</div>
-      <div style={{ color: palette.dim }}>▎ Designed with Claude Design · Built with Claude Code</div>
+      <div>Responses come from two layers: an intent matcher that handles greetings and small talk, and a keyword lookup table that returns dog facts verbatim. If neither matches, you get one of three fallback replies.</div>
+      <div>The generative version, powered by Meta's BlenderBot-400M-distill, runs separately as a <a href="https://huggingface.co/spaces/ElisaTrippetti/Fetch-Good-Boi" target="_blank" rel="noopener noreferrer" style={{ color: palette.accent, textDecoration: "underline" }}>Docker Space</a>.</div>
+      <div style={{ color: palette.dim }}>Designed with Claude Design · Built with Claude Code</div>
     </div>
   );
 }

variant-terminal.jsx

@@ -91,9 +91,9 @@ function TerminalVariant({ backend, personality, density, accent, fontPair, bubb
           margin: 0, fontFamily: "inherit", color: palette.dim,
           whiteSpace: "pre-wrap", marginBottom: 16,
         }}>
-{`// fetch pup is the first static chatbot i put together, and i use it as a learning baseline.
-// it comes with a small keyword lookup layer and a set of fallback responses.
-// type a question and hit enter, or try the suggestions below.
+{`// hey! i'm fetch pup — a dog-loving chatbot demo and learning baseline.
+// i do intent matching, keyword lookup, and fallbacks — no model, all browser.
+// ask me something, or try the suggestions below.
 `}
         </pre>