feat: configurable llm

.env

@@ -6,4 +6,5 @@ MISTLE_LOGIN_PROMPT=Wie heisst Du denn ("neu" fuer neuen Spieler) ?
 MISTLE_EXIT_COMMAND=schlaf ein
 MISTLE_AGENT_MODE=true
 MISTLE_AGENT=intelligent
-MISTRAL_API_KEY=eohe7Di7vuznINFqW5VyQIPenbyPX3le
+MISTRAL_API_KEY=eohe7Di7vuznINFqW5VyQIPenbyPX3le
+MISTLE_LLM_MODEL=mistral/mistral-small

.vscode/settings.json

@@ -0,0 +1,3 @@
+{
+    "wolf.disableHotModeWarning": true
+}

README.md

@@ -55,6 +55,7 @@ All variables can be placed in the `.env` file (one `KEY=value` per line) or pro
 | `MISTLE_EXIT_COMMAND` | ❌ | Command issued during graceful shutdown (after pressing `Ctrl-C`). Useful for `quit`/`save` macros. |
 | `MISTLE_AGENT_MODE` | ❌ | Enable full-time agent thread when set to truthy values (`1`, `true`, `yes`, `on`). Defaults to interactive-only mode. |
 | `MISTLE_AGENT` | ❌ | Select which agent class to instantiate when agent mode is active. Accepted values: `simple` (default), `explore`, `communication`, `intelligent`/`intelligentcommunication` (LLM-backed), or custom spec `module:ClassName`. |
+| `MISTLE_LLM_MODEL` | ❌ | Override the `litellm` model used by the intelligent agent (defaults to `mistral/mistral-small-2407`). |
 | `MISTRAL_API_KEY` | ❌ | API key used by `IntelligentCommunicationAgent` (via `litellm`) when calling the `mistral/mistral-small-2407` model. |
 
 ## Agent Development

app.py

@@ -153,23 +153,32 @@ def build_agent(agent_spec: str) -> Agent:
         return SimpleAgent()
 
     builtin_agents = {
-        "explore": ("agent", "ExploreAgent"),
-        "communication": ("agent", "CommunicationAgent"),
-        "intelligent": ("intelligent_agent", "IntelligentCommunicationAgent"),
+        "explore": ("agent", "ExploreAgent", {}),
+        "communication": ("agent", "CommunicationAgent", {}),
+        "intelligent": (
+            "intelligent_agent",
+            "IntelligentCommunicationAgent",
+            {"model": os.environ.get("MISTLE_LLM_MODEL", "mistral/mistral-tiny")},
+        ),
         "intelligentcommunication": (
             "intelligent_agent",
             "IntelligentCommunicationAgent",
+            {"model": os.environ.get("MISTLE_LLM_MODEL", "mistral/mistral-tiny")},
         ),
     }
 
     if key in builtin_agents:
-        module_name, class_name = builtin_agents[key]
+        module_name, class_name, kwargs = builtin_agents[key]
         try:
             module = import_module(module_name)
             agent_cls = getattr(module, class_name)
         except AttributeError as exc:  # pragma: no cover - optional dependency
             raise RuntimeError(f"{class_name} is not available in agent module") from exc
-        return _instantiate_agent(agent_cls, normalized)
+        agent = _instantiate_agent(agent_cls, normalized, kwargs)
+        model_name = kwargs.get("model") if kwargs else None
+        if model_name:
+            print(f"[Agent] Using LLM model: {model_name}")
+        return agent
 
     if ":" in normalized:
         module_name, class_name = normalized.split(":", 1)
@@ -182,11 +191,14 @@ def build_agent(agent_spec: str) -> Agent:
     raise RuntimeError(f"Unknown agent spec '{agent_spec}'.")
 
 
-def _instantiate_agent(agent_cls: Type[Agent], agent_spec: str) -> Agent:
+def _instantiate_agent(
+    agent_cls: Type[Agent], agent_spec: str, kwargs: Optional[dict] = None
+) -> Agent:
     if not issubclass(agent_cls, Agent):
         raise RuntimeError(f"{agent_spec} is not an Agent subclass")
     try:
-        return agent_cls()
+        kwargs = kwargs or {}
+        return agent_cls(**kwargs)
     except TypeError as exc:
         raise RuntimeError(f"Failed to instantiate {agent_spec}: {exc}") from exc
 

intelligent_agent.py

@@ -54,7 +54,7 @@ class IntelligentCommunicationAgent(Agent):
         if not self.pending_replies:
             return None
         player, _ = self.pending_replies.popleft()
-        reply_text = self._generate_reply(player)
+        reply_text = self._sanitize_reply(self._generate_reply(player))
         self._append_history(player, "assistant", reply_text)
         reply = f"teile {player} mit {reply_text}"
         print(f"[Agent] Replying to {player} with model output")
@@ -86,6 +86,12 @@ class IntelligentCommunicationAgent(Agent):
 
         return content or self.fallback_reply
 
+    def _sanitize_reply(self, text: str) -> str:
+        if not text:
+            return self.fallback_reply
+        collapsed = " ".join(text.split())
+        return collapsed or self.fallback_reply
+
     def _build_messages(self, player: str) -> list[dict[str, str]]:
         history = self.conversation_history.get(player)
         messages: list[dict[str, str]] = [{"role": "system", "content": self.system_prompt}]