Update app.py

app.py

@@ -34,7 +34,7 @@ def analyze_attrition_with_llm(df_dict, hr_query):
     employees_data = {row["Employee"].strip(): row["Sentiment"] for _, row in df.iterrows()}
     
     prompt = f"HR Query: {hr_query}\nEmployees Data: {json.dumps(employees_data, indent=2)}"
-    response = client.chat.completions.create(
+    '''response = client.chat.completions.create(
         model="gpt-4o-mini",
         messages=[{"role": "user", "content": prompt}],
         functions=[
@@ -54,6 +54,27 @@ def analyze_attrition_with_llm(df_dict, hr_query):
         ],
         function_call="auto"
     )
+    '''
+    response = client.chat.completions.create(
+    model="gpt-4o-mini",
+    messages=[{"role": "user", "content": prompt}],
+    functions=[
+        {
+            "name": "predict_attrition_risk",
+            "description": "Predicts attrition risk based on sentiment and provides explanation.",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "employee_name": {"type": "string", "description": "Employee's name"},
+                    "sentiment": {"type": "string", "description": "Extracted sentiment"},
+                    "explanation": {"type": "string", "description": "Brief explanation"}
+                },
+                "required": ["employee_name", "sentiment", "explanation"]
+            }
+        }
+    ],
+    function_call="auto"
+    )
     print(response)  # Debugging: Print response
 
     # Handle function call response properly