app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM

# Load language model
tokenizer = AutoTokenizer.from_pretrained("meta-llama/Meta-Llama-3-8B")
model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B")

# Function to generate SQL queries
def generate_sql_query(prompt):
    input_text = "generate SQL query: " + prompt
    input_ids = tokenizer.encode(input_text, return_tensors="pt")
    output = model.generate(input_ids, max_length=100, num_return_sequences=1, temperature=0.9)
    generated_query = tokenizer.decode(output[0], skip_special_tokens=True)
    return generated_query

# Gradio UI for chatbot
def generate_sql_query_interface(prompt):
    if prompt:
        generated_query = generate_sql_query(prompt)
        return generated_query
    else:
        return "Please enter a prompt."

inputs = gr.inputs.Textbox(lines=5, label="Enter your prompt:")
output = gr.outputs.Textbox(label="Generated SQL Query:")

gr.Interface(fn=generate_sql_query_interface, inputs=inputs, outputs=output, title="SQL Query Generator Chatbot").launch()