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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()
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