t

app.py

@@ -23,18 +23,21 @@ client = OpenAI(
 )
 
 # --- 3. Define the Gradio Function ---
-def get_sql_response(message, history):
+# This function now expects 'history' to be in the new "messages" format
+def get_sql_response(message: str, history: list[dict[str, str]]):
     system_prompt = "You are an expert AI that converts natural language questions into SQL queries. You only respond with the SQL query."
 
-    messages_for_api = [{"role": "system", "content": system_prompt}]
-    for turn in history:
-        messages_for_api.append({"role": "user", "content": turn[0]})
-        messages_for_api.append({"role": "assistant", "content": turn[1]})
-    messages_for_api.append({"role": "user", "content": message})
+    # The history is already in the correct OpenAI format
+    # We just add the system prompt and the new user message
+    messages_for_api = (
+        [{"role": "system", "content": system_prompt}] +
+        history +
+        [{"role": "user", "content": message}]
+    )
 
     try:
         response_stream = client.chat.completions.create(
-            model="prem-1b-sql", # Placeholder
+            model="prem-sql-api", # This should match the name in your Ollama Modelfile
             messages=messages_for_api,
             stream=True
         )
@@ -53,10 +56,11 @@ def get_sql_response(message, history):
 print("Launching Gradio interface...")
 gr.ChatInterface(
     get_sql_response,
-    title="TEXT-SQL Playground (UI)",
+    title="Prem-1B-SQL Playground (UI)",
     description="Ask a natural language question. I will convert it to a SQL query.",
     examples=["Show me the average salary for all employees in the 'Engineering' department.",
-              "List all users who signed up in the last 30 days."]
+              "List all users who signed up in the last 30 days."],
+    type="messages" # This fixes the UserWarning
 ).launch(
     server_name="0.0.0.0",
     server_port=7860,