use MODEL_NAME from env instead of hardconding

agent.py

@@ -224,8 +224,8 @@ FORMAT:
 
 def call_llm(prompt):
     completion = client.chat.completions.create(
-        #model=os.getenv("MODEL_NAME"),
-        model="llama-3.1-8b-instant",
+        model=os.getenv("MODEL_NAME"),
+        #model="llama-3.1-8b-instant",
         messages=[{"role": "user", "content": prompt}],
         temperature=0.2,
         response_format={"type": "json_object"}

agent_llm.py

@@ -66,6 +66,7 @@ FORMAT:
 def call_llm(prompt):
     completion = client.chat.completions.create(
         model=os.getenv("MODEL_NAME"),
+        #model="llama-3.1-8b-instant",
         messages=[{"role": "user", "content": prompt}],
         temperature=0.2,
         response_format={"type": "json_object"}
@@ -204,16 +205,16 @@ def run_agent():
         obs, reward, done, info = env.step(action)
 
     
-        print(f"\nOBS: {obs}")
-        print(f"\nACTION: {action}")
-        print(f"\nREWARD: {reward}")
-        print(f"\nDONE: {done}")
+        #print(f"\nOBS: {obs}")
+        #print(f"\nACTION: {action}")
+        #print(f"\nREWARD: {reward}")
+        #print(f"\nDONE: {done}")
 
     
     #print("FINAL:", info)
-    print(f"\nFINAL: {info if info else 'No info returned'}")
+    #print(f"\nFINAL: {info if info else 'No info returned'}")
     
-    print(f"\nMETRICS: {env.get_metrics()}")
+    #print(f"\nMETRICS: {env.get_metrics()}")
 
 
 if __name__ == "__main__":

inference.py

@@ -18,8 +18,8 @@ def main():
     env = CustomerSupportEnv()
     obs = env.reset()
 
-    #model_name = os.getenv("MODEL_NAME", "unknown-model")
-    model_name="llama-3.1-8b-instant"
+    model_name = os.getenv("MODEL_NAME", "unknown-model")
+    #model_name="llama-3.1-8b-instant"
 
     task_name = "customer-support"
     benchmark = "openenv"