From 1f3e152fa97c5f1557d9b08be88c7f9ddf62409c Mon Sep 17 00:00:00 2001
From: Daniel Eder <daniel@deder.at>
Date: Tue, 10 Feb 2026 20:08:26 +0100
Subject: [PATCH] Fix LLM model env override for agents and tools

---
 agents.py    |  5 +++++
 mud_tools.py | 16 ++++++++++------
 2 files changed, 15 insertions(+), 6 deletions(-)

diff --git a/agents.py b/agents.py
index 135cd06..3468db1 100644
--- a/agents.py
+++ b/agents.py
@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import itertools
+import os
 import sys
 from abc import ABC, abstractmethod
 from dataclasses import dataclass
@@ -129,6 +130,10 @@ def build_agent(
             name: description
             for name, description in (allowed_tools or {}).items()
         }
+        if model is None:
+            env_model = os.environ.get("MISTLE_LLM_MODEL", "").strip()
+            if env_model:
+                model = env_model
         agent = IntelligentAgent(instruction=instruction, allowed_tools=tool_map)
         if model:
             agent.model = model
diff --git a/mud_tools.py b/mud_tools.py
index 557e6a3..590663e 100644
--- a/mud_tools.py
+++ b/mud_tools.py
@@ -7,6 +7,10 @@ from typing import Optional, Type
 from tools import Tool
 
 
+DEFAULT_LLM_MODEL = "mistral/mistral-small"
+LLM_MODEL_ENV = "MISTLE_LLM_MODEL"
+
+
 TOOL_REGISTRY = {
     "look": {
         "module": "tools",
@@ -50,17 +54,13 @@ TOOL_REGISTRY = {
     "intelligent": {
         "module": "intelligent_tool",
         "class": "IntelligentCommunicationTool",
-        "kwargs": {
-            "model": os.environ.get("MISTLE_LLM_MODEL", "mistral/mistral-small")
-        },
+        "kwargs": {},
         "description": "Uses an LLM to craft a polite reply to private tells.",
     },
     "intelligentcommunication": {
         "module": "intelligent_tool",
         "class": "IntelligentCommunicationTool",
-        "kwargs": {
-            "model": os.environ.get("MISTLE_LLM_MODEL", "mistral/mistral-small")
-        },
+        "kwargs": {},
         "description": "Alias of 'intelligent'. Uses an LLM to craft a polite reply to private tells.",
     },
 }
@@ -81,6 +81,10 @@ def build_tool(spec: str) -> Tool:
         class_name = meta["class"]
         kwargs = dict(meta.get("kwargs", {}))
         kwargs = _apply_builtin_args(key, args, kwargs)
+        if key in {"intelligent", "intelligentcommunication"}:
+            default_model = kwargs.get("model", DEFAULT_LLM_MODEL)
+            env_model = os.environ.get(LLM_MODEL_ENV, "").strip()
+            kwargs["model"] = env_model or default_model
         try:
             module = import_module(module_name)
             tool_cls = getattr(module, class_name)