Update app.py

app.py

@@ -18,10 +18,9 @@ import random
 import json
 from datetime import datetime
 from pathlib import Path
-
+from openai import OpenAI
 import streamlit as st
 import pandas as pd
-import openai
 from huggingface_hub import upload_file, HfApi
 
 # ---------------------------
@@ -87,7 +86,9 @@ def upload_log_to_hf(local_path: Path, participant_id: str):
 # ---------------------------
 # OpenAI helper
 # ---------------------------
-openai.api_key = os.getenv("OPENAI_API_KEY")
+
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+client = OpenAI(api_key=OPENAI_API_KEY)
 
 def call_llm_for_order(role: str, local_state: dict, info_sharing_visible: bool, demand_history: list, max_tokens=40, temperature=0.7):
     """
@@ -114,7 +115,7 @@ def call_llm_for_order(role: str, local_state: dict, info_sharing_visible: bool,
     )
 
     try:
-        resp = openai.ChatCompletion.create(
+        resp = client.chat.completions.create(
             model=OPENAI_MODEL,
             messages=[
                 {"role": "system", "content": "You are an automated Beer Game agent who decides weekly orders."},
@@ -124,7 +125,7 @@ def call_llm_for_order(role: str, local_state: dict, info_sharing_visible: bool,
             temperature=temperature,
             n=1
         )
-        raw = resp.choices[0].message.get("content", "").strip()
+        raw = resp.choices[0].message.content.strip()
     except Exception as e:
         raw = f"OPENAI_ERROR: {str(e)}"
         # fallback later
@@ -478,12 +479,12 @@ with col_sidebar:
             # quick test prompt
             try:
                 test_prompt = "You are a helpful agent. Reply with '42'."
-                resp = openai.ChatCompletion.create(
+                resp = client.chat.completions.create(
                     model=OPENAI_MODEL,
                     messages=[{"role":"user","content":test_prompt}],
                     max_tokens=10
                 )
-                st.write("LLM raw:", resp.choices[0].message.get("content"))
+                st.write("LLM raw:", resp.choices[0].message.content)
             except Exception as e:
                 st.error(f"LLM test failed: {e}")