Update the CyberForge ML service

app.py

@@ -1093,10 +1093,25 @@ class TransformerModelLoader:
         "such as reputation, hashes or CVEs, say it is unverified instead of guessing."
     )
 
+    # For a person talking to the assistant (interactive requests): a
+    # conversation first. The analyst prompt above stays for background
+    # explanations of scans, alerts and reports.
+    ASSISTANT_PROMPT = (
+        "You are the CyberForge assistant, a friendly, helpful chat assistant built into "
+        "the CyberForge security app. Talk naturally, like a normal chat assistant: reply "
+        "to greetings and small talk briefly and warmly, and offer to help. Answer security "
+        "questions clearly and concisely, in plain sentences, using a short list only for "
+        "steps. When the message includes the user's CyberForge memory, use it only if it "
+        "helps answer. Never claim to have scanned, detected or checked anything that is "
+        "not in the message; if something has not been checked, say so."
+    )
+
     def security_chat(self, query: str, max_tokens: int = 512, time_budget_s: Optional[float] = None, interactive: bool = False) -> Dict:
         """Cybersecurity Q&A, answered by the open-source model running inside
-        this Space (free, no API key). `interactive` when a person is waiting."""
-        return local_llm.chat(self.SYSTEM_PROMPT, query, max_tokens=max_tokens, time_budget_s=time_budget_s, interactive=interactive)
+        this Space (free, no API key). `interactive` when a person is waiting:
+        then it is a conversation (ASSISTANT_PROMPT), not an analyst's report."""
+        system = self.ASSISTANT_PROMPT if interactive else self.SYSTEM_PROMPT
+        return local_llm.chat(system, query, max_tokens=max_tokens, time_budget_s=time_budget_s, interactive=interactive)
 
     def status(self) -> Dict:
         return {