blocks experiment

app.py

@@ -1,7 +1,14 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 import os
-from smolagents import tool, CodeAgent, HfApiModel, GradioUI, MultiStepAgent
+from smolagents import (
+    tool,
+    CodeAgent,
+    HfApiModel,
+    GradioUI,
+    MultiStepAgent,
+    stream_to_gradio,
+)
 from sqlalchemy import (
     create_engine,
     MetaData,
@@ -120,6 +127,9 @@ if __name__ == "__main__":
 
     agent = CodeAgent(
         tools=[sql_engine_tool],
+        #         system_prompt="""
+        # You are a text to sql converter
+        # """,
         model=model,
         max_steps=1,
         verbosity_level=1,
@@ -127,13 +137,14 @@ if __name__ == "__main__":
     # agent.run("What is the average each customer paid?")
     # GradioUI(agent).launch()
 
-    def enter_message(message, chat_history, engine):
+    def enter_message(message, chat_history):
         print()
         print("enter_message debug")
-        print(message)
-        print(chat_history)
+        print("engine", engine)
+        print("message:", message)
+        print("chat_history", chat_history)
         chat_history.append({"role": "user", "content": message})
-        x = agent.run(message, additional_args=dict(engine=engine))
+        x = stream_to_gradio(agent, message, additional_args=dict(engine=engine))
         print(type(x))
         print("\n\n\n", x, "\n\n\n")
         return "", x
@@ -142,5 +153,5 @@ if __name__ == "__main__":
         chatbot = gr.Chatbot(type="messages")
         input = gr.Textbox()
         button = gr.Button("reply")
-        button.click(enter_message, [input, chatbot, engine], [input, chatbot, engine])
+        button.click(enter_message, [input, chatbot], [input, chatbot])
     b.launch()