Update app.py

app.py

@@ -18,8 +18,8 @@ from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
 profile = "bstraehle"
 
 action_1 = "Prompt base model"
-action_2 = "Prompt fine-tuned model"
-action_3 = "Fine-tune base model"
+action_2 = "Fine-tune base model"
+action_3 = "Prompt fine-tuned model"
 
 system_prompt = "You are a text to SQL query translator. Given a question in English, generate a SQL query based on the provided SCHEMA. Do not generate any additional text. SCHEMA: {schema}"
 user_prompt = "What is the total trade value and average price for each trader and stock in the trade_history table?"
@@ -37,9 +37,7 @@ def prompt_model(model_id, system_prompt, user_prompt, schema):
       {"role": "user", "content": user_prompt},
       {"role": "assistant", "content": ""}
     ]
-
-    print(messages)
-    
+  
     output = pipe(messages)
     
     return output[0]["generated_text"][-1]["content"]
@@ -82,9 +80,9 @@ def process(action, system_prompt, user_prompt, schema, base_model_id, fine_tune
     if action == action_1:
         result = prompt_model(base_model_id, system_prompt, user_prompt, schema)
     elif action == action_2:
-        result = prompt_model(fine_tuned_model_id, system_prompt, user_prompt, schema)
-    elif action == action_3:
         result = fine_tune_model(base_model_id)
+    elif action == action_3:
+        result = prompt_model(fine_tuned_model_id, system_prompt, user_prompt, schema)
     
     return result