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import streamlit as st
import time # For measuring time taken
from sql_query_generator.config import Instructions
from sql_query_generator.utils import load_json, format_prompt
from sql_query_generator.generator import load_model, generate_sql
# Load Schema and Metadata
try:
schema = load_json("data/table_create.json")
metadata = load_json("data/tables_metadata.json")
except FileNotFoundError:
st.error("Schema or metadata files not found. Please ensure they are in the `data/` directory.")
st.stop()
# Load model and tokenizer
tokenizer, model = load_model()
# Streamlit Interface
st.title("Dynamic SQL Query Generator")
st.markdown("Enter your query below to generate a SQL query based on the provided schema and metadata.")
# Sidebar
with st.sidebar:
# st.header("Options")
# use_gpu = st.checkbox("Use GPU (if available)", value=False)
device = "cpu"
st.header("Example Queries")
st.write("- Get fire budget for Ada county for the year 2023")
st.write("- Retrieve population count for all cities")
# Main Input
question = st.text_input("Enter your query:")
if question:
st.write("Generating SQL for the query...")
start_time = time.time() # Start measuring time
# Format prompt
formatted_prompt = format_prompt(question, schema, metadata, Instructions)
prompt_inputs = {
"formatted_prompt": formatted_prompt,
"schema": schema,
"metadata": metadata,
"instructions": Instructions,
}
# Generate SQL Query
sql_query = generate_sql(question, prompt_inputs, tokenizer, model, device=device)
end_time = time.time() # End measuring time
# Display Results
st.subheader("Generated SQL Query:")
st.code(sql_query, language="sql")
# Show time taken
time_taken = end_time - start_time
st.subheader("Time Taken:")
st.write(f"{time_taken:.2f} seconds")
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