Update app.py

app.py

@@ -1,34 +1,19 @@
 import gradio as gr
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-# Load the chatbot model
-chatbot_model_name = "facebook/bart-large-mnli"
-chatbot_tokenizer = AutoTokenizer.from_pretrained(chatbot_model_name)
-chatbot_model = AutoModelForCausalLM.from_pretrained(chatbot_model_name)
-
-# Load the SQL model
-sql_model_name = "microsoft/tapex-large-sql-execution"  # Replace with the name of the SQL model you want to use
-sql_tokenizer = AutoTokenizer.from_pretrained(sql_model_name)
-sql_model = AutoModelForCausalLM.from_pretrained(sql_model_name)
-
 def chatbot_response(user_message):
-    # Generate chatbot response using the chatbot model
-    inputs = chatbot_tokenizer.encode("User: " + user_message, return_tensors="pt")
-    outputs = chatbot_model.generate(inputs, max_length=100, num_return_sequences=1)
-    response = chatbot_tokenizer.decode(outputs[0], skip_special_tokens=True)
+    model_name = "gpt2"  # You can change this to any other model from the list above
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForCausalLM.from_pretrained(model_name)
 
-    return response
-
-def execute_sql(user_query):
-    # Execute SQL query using the SQL model
-    inputs = sql_tokenizer(user_query, return_tensors="pt")
-    outputs = sql_model.generate(inputs['input_ids'], attention_mask=inputs['attention_mask'], max_length=1000)
-    response = sql_tokenizer.decode(outputs[0], skip_special_tokens=True)
+    inputs = tokenizer.encode("User: " + user_message, return_tensors="pt")
+    outputs = model.generate(inputs, max_length=100, num_return_sequences=1)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
 
     return response
 
-# Define the chatbot and SQL execution interfaces using Gradio
-chatbot_interface = gr.Interface(
+# Define the chatbot interface using Gradio
+iface = gr.Interface(
     fn=chatbot_response,
     inputs=gr.Textbox(prompt="You:"),
     outputs=gr.Textbox(),
@@ -38,19 +23,6 @@ chatbot_interface = gr.Interface(
     description="Type your message in the box above, and the chatbot will respond.",
 )
 
-sql_execution_interface = gr.Interface(
-    fn=execute_sql,
-    inputs=gr.Textbox(prompt="Enter your SQL query:"),
-    outputs=gr.Textbox(),
-    live=True,
-    capture_session=True,
-    title="SQL Execution",
-    description="Type your SQL query in the box above, and the chatbot will execute it.",
-)
-
-# Combine the chatbot and SQL execution interfaces
-combined_interface = gr.Interface([chatbot_interface, sql_execution_interface], layout="horizontal")
-
-# Launch the combined Gradio interface
+# Launch the Gradio interface
 if __name__ == "__main__":
-    combined_interface.launch()
+    iface.launch()