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 = "your_sql_model_name"  # 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)

    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)

    return response

# Define the chatbot and SQL execution interfaces using Gradio
chatbot_interface = gr.Interface(
    fn=chatbot_response,
    inputs=gr.Textbox(prompt="You:"),
    outputs=gr.Textbox(),
    live=True,
    capture_session=True,
    title="Chatbot",
    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
if __name__ == "__main__":
    combined_interface.launch()