feat: norms and goals to llm

base goals and norms can be defined in llm_instructions.py
cleaned the code

ref: N25B-215

src/control_backend/agents/llm/llm_instructions.py

@@ -0,0 +1,44 @@
+class LLMInstructions:
+    """
+    Defines structured instructions that are sent along with each request
+    to the LLM to guide its behavior (norms, goals, etc.).
+    """
+
+    @staticmethod
+    def default_norms() -> str:
+        return f"""
+        Be friendly and respectful.
+        Make the conversation feel natural and engaging.
+        """.strip()
+
+    @staticmethod
+    def default_goals() -> str:
+        return f"""
+        Try to learn the user's name during conversation.
+        """.strip()
+
+    def __init__(self, norms: str | None = None, goals: str | None = None):
+        self.norms = norms if norms is not None else self.default_norms()
+        self.goals = goals if goals is not None else self.default_goals()
+
+    def build_developer_instruction(self) -> str:
+        """
+        Builds a multi-line formatted instruction string for the LLM.
+        Includes only non-empty structured fields.
+        """
+        sections = [
+            "You are a Pepper robot engaging in natural human conversation.",
+            "Keep responses between 1–5 sentences, unless instructed otherwise.\n",
+        ]
+
+        if self.norms:
+            sections.append("Norms to follow:")
+            sections.append(self.norms)
+            sections.append("")
+
+        if self.goals:
+            sections.append("Goals to reach:")
+            sections.append(self.goals)
+            sections.append("")
+
+        return "\n".join(sections).strip()