Update model.py

model.py

@@ -1,23 +1,33 @@
 import random
-from utilities import prepare_text_input, generate_recommendation
 
-# Mock objects (None used in mock version)
-def load_model():
-    return None, None, None
+def generate_recommendation(stage, emails, meetings):
+    if stage == "Negotiation":
+        return "Follow up with final pricing discussion."
+    elif stage == "Proposal/Price Quote":
+        return "Schedule one more meeting to present value."
+    elif meetings == 0:
+        return "Schedule a meeting to initiate engagement."
+    elif emails < 2:
+        return "Send follow-up email to re-engage."
+    else:
+        return "Continue monitoring engagement signals."
 
 def predict(data, model, tokenizer, summarizer):
-    text_input = prepare_text_input(data)
+    score = random.randint(50, 95)
+    confidence = round(random.uniform(0.65, 0.95), 2)
 
-    # Simulated scoring logic
-    score = random.randint(45, 95)
-    confidence = round(random.uniform(0.6, 0.95), 2)
-    risk = (
-        "Low" if score > 75 else
-        "Medium" if score >= 55 else
-        "High"
-    )
+    if score >= 75:
+        risk = "Low"
+    elif score >= 55:
+        risk = "Medium"
+    else:
+        risk = "High"
 
-    recommendation = generate_recommendation(data)
+    recommendation = generate_recommendation(
+        data["stage"],
+        data["emails_last_7_days"],
+        data["meetings_last_30_days"]
+    )
 
     return {
         "score": score,