verscuht das decision_LLM zu fixen

math-tutor/backend/app/LLM_services/decision_LLM.py

@@ -36,7 +36,6 @@ def needs_more_context(context_sheet: str) -> dict:
             f"{context_sheet}\n\n"
         }
     )
-    messages.append({"role": "user", "content": "Treffe eine Entscheidung. Zu der letzten Nachricht"})
 
     resp, tool_outputs = llm_client.chat_with_tools(
         messages=messages,

math-tutor/backend/app/deterministic_services/llm_client.py

@@ -52,7 +52,14 @@ def chat(
     if settings.temperature is not None:
         kwargs["options"] = {"temperature": settings.temperature}
 
-    response = client.chat(**_filter_kwargs(client.chat, kwargs))
+    filtered_kwargs = _filter_kwargs(client.chat, kwargs)
+    if tools and "tools" not in filtered_kwargs:
+        raise RuntimeError(
+            "Configured ollama Python client does not support tool calling (chat(..., tools=...)). "
+            "Update the 'ollama' package or switch to a backend/model path with tool support."
+        )
+
+    response = client.chat(**filtered_kwargs)
     return {"raw": response, "message": _extract_message(response)}
 
 

math-tutor/backend/test/decision_test.py

@@ -21,14 +21,6 @@ def _resolve_sheet(args: argparse.Namespace) -> dict[str, Any]:
         return sheet
     raise ValueError("Bitte --sheet oder --chat-id angeben.")
 
-
-def _last_user_inputs(history: list[dict[str, Any]], count: int) -> list[str]:
-    if count <= 0:
-        return []
-    user_msgs = [msg.get("content", "") for msg in history if msg.get("role") == "user"]
-    return [text for text in user_msgs[-count:] if text]
-
-
 def main() -> None:
     parser = argparse.ArgumentParser(description="Isolierter Decision-LLM Test mit Context Sheet.")
     parser.add_argument("--sheet", help="Pfad zu einem Context Sheet JSON.")