Update inference.py

inference.py

@@ -1,6 +1,8 @@
 import torch
-from transformers import AutoTokenizer, OpenAIGPTLMHeadModel
+from transformers import AutoTokenizer
 from evo_model import EvoTransformerV22
+from openai import OpenAI
+import os
 
 # Load Evo model
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
@@ -12,7 +14,7 @@ evo_model.eval()
 # Load tokenizer
 tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
 
-# 🧠 Evo logic
+# 🧠 Evo logic (binary classification with sigmoid)
 def get_evo_response(query, context):
     combined = query + " " + context
     inputs = tokenizer(combined, return_tensors="pt", truncation=True, padding="max_length", max_length=128)
@@ -20,24 +22,24 @@ def get_evo_response(query, context):
 
     with torch.no_grad():
         logits = evo_model(input_ids)
-        pred = torch.argmax(logits, dim=1).item()
+        pred = int(torch.sigmoid(logits).item() > 0.5)
 
-    return f"Evo suggests: Option {pred + 1}"  # Assumes binary classification (0 or 1)
+    return f"Evo suggests: Option {pred + 1}"
 
-# 🤖 GPT-3.5 comparison (optional)
-import openai
-openai.api_key = "sk-..."  # Replace with your OpenAI API key
+# 🤖 GPT-3.5 comparison using openai>=1.0.0
+openai_api_key = os.environ.get("OPENAI_API_KEY", "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")  # Replace with real key or set via HF secrets
+client = OpenAI(api_key=openai_api_key)
 
 def get_gpt_response(query, context):
     try:
         prompt = f"Context: {context}\n\nQuestion: {query}\n\nAnswer:"
-        response = openai.ChatCompletion.create(
+        response = client.chat.completions.create(
             model="gpt-3.5-turbo",
-            messages=[{"role": "user", "content": prompt}],
+            messages=[
+                {"role": "user", "content": prompt}
+            ],
             temperature=0.3
         )
-        return response['choices'][0]['message']['content'].strip()
+        return response.choices[0].message.content.strip()
     except Exception as e:
         return f"Error from GPT: {e}"
-
-        #