Solution updated with real LLM and dependencies: update hitl_agent.py

hitl_agent.py

@@ -19,16 +19,16 @@ class GameState(TypedDict):
     ending: str
 
 # LLM instance
-class DummyLLM:
-    def invoke(self, prompt: str):
-        # Very simple deterministic responses based on prompt content
-        if "Generate a short hook" in prompt:
-            return type("Resp", (), {"content": "A mysterious cat appears on a spaceship.\nOPTIONS:\n1) Open the door\n2) Look around\n3) Sleep deeper"})
-        if "Write a short ending" in prompt:
-            return type("Resp", (), {"content": "The cat discovers a hidden alien artifact.\nThe end."})
-        return type("Resp", (), {"content": ""})
+# Use real LLM
+import os
+from langchain_openai import ChatOpenAI
 
-llm = DummyLLM()
+llm = ChatOpenAI(
+    model=os.getenv("OPENAI_MODEL", "gpt-3.5-turbo"),
+    base_url=os.getenv("OPENAI_BASE_URL") or None,
+    api_key=os.getenv("OPENAI_API_KEY", "not-needed"),
+    temperature=0,
+)
 
 
 def generate_scene(state: GameState) -> GameState: