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Upload sql_t5.py

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  1. sql_t5.py +141 -0
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+ import streamlit as st
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+ from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
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+ import torch
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+ import os
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+
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+ def make_query(context, question):
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+ result_query = f'''You are a SQL expert with extensive experience, you need to create a query to answer the question.
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+
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+ ### Database schema (PostgreSQL):
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+ {context}
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+
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+ ### Question:
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+ {question}
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+
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+ ### SQL Query: '''
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+ return result_query
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+
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+ st.set_page_config(page_title="SQL-to-Text with T5", page_icon="🤖")
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+ st.title("SQL Query Generator with T5")
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+
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+ examples = [
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+ {
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+ "question": "Who was the music director in 1971 for the movie Kalyani?",
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+ "description": "CREATE TABLE table_name_7 (Music VARCHAR, year VARCHAR, movie__in_kannada__ VARCHAR)"
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+ },
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+ {
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+ "question": "What's the highest with a capacity of greater than 4,000 and an average of 615?",
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+ "description": "CREATE TABLE table_name_20 (highest INTEGER, average VARCHAR, capacity VARCHAR)"
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+ },
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+ {
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+ "question": "If the letters is φαν, what is the founding date?",
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+ "description": "CREATE TABLE table_2538117_7 (founding_date VARCHAR, letters VARCHAR)"
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+ },
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+ {
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+ "question": "How many weeks had a game on November 26, 1978, and an attendance higher than 26,248?",
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+ "description": "CREATE TABLE table_name_88 (week VARCHAR, date VARCHAR, attendance VARCHAR)"
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+ },
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+ {
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+ "question": "How many television service are in italian and n°is greater than 856.0?",
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+ "description": "CREATE TABLE table_15887683_15 (television_service VARCHAR, language VARCHAR, n° VARCHAR)"
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+ },
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+ {
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+ "question": "What date was Bury the home team?",
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+ "description": "CREATE TABLE table_name_67 (date VARCHAR, away_team VARCHAR)"
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+ },
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+ {
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+ "question": "What regular season result had an average attendance less than 942?",
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+ "description": "CREATE TABLE table_name_16 (reg_season VARCHAR, avg_attendance INTEGER)"
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+ },
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+ {
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+ "question": "What is the value for 2011 when `a` is the value for 2009, and 4r is the value for 2013?",
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+ "description": "CREATE TABLE table_name_89 (Id VARCHAR)"
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+ },
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+ {
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+ "question": "Who wrote episode with production code 1.01?",
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+ "description": "CREATE TABLE table_28089666_1 (written_by VARCHAR, production_code VARCHAR)"
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+ },
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+ {
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+ "question": "find the names of museums which have more staff than the minimum staff number of all museums opened after 2010.",
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+ "description": "CREATE TABLE museum (name VARCHAR, num_of_staff INTEGER, open_year INTEGER)"
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+ }
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+ ]
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+
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+ @st.cache_resource
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+ def load_model():
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+ script_dir = os.path.dirname(os.path.abspath(__file__))
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+ model_path = os.path.join(script_dir, "model")
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+
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+ if not os.path.exists(model_path):
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+ raise FileNotFoundError(f"Model directory not found at {model_path}")
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+
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+ try:
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+ tokenizer = AutoTokenizer.from_pretrained("google-t5/t5-small")
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+ model = AutoModelForSeq2SeqLM.from_pretrained(model_path)
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+ model.eval()
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+ return model, tokenizer
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+ except Exception as e:
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+ raise RuntimeError(f"Error loading model: {str(e)}")
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+
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+ try:
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+ model, tokenizer = load_model()
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+ except Exception as e:
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+ st.error(f"Failed to load model: {str(e)}")
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+ st.stop()
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+
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+ if 'current_description' not in st.session_state:
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+ st.session_state.current_description = """CREATE TABLE table_name_28 (played INTEGER, points VARCHAR, position VARCHAR)"""
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+ if 'current_question' not in st.session_state:
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+ st.session_state.current_question = "Which Played has a Points of 2, and a Position smaller than 8?"
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+
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+ def load_example(example):
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+ st.session_state.current_description = example["description"]
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+ st.session_state.current_question = example["question"]
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+
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+ st.subheader("Примеры:")
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+ cols = st.columns(2)
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+ for i, example in enumerate(examples):
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+ col = cols[i % 2]
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+ if col.button(
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+ f"Пример {i+1}: {example['question'][:30]}...",
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+ key=f"example_{i}",
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+ ):
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+ load_example(example)
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+ st.rerun()
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+
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+ with st.form("query_form"):
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+ description = st.text_area(
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+ "Описание таблицы (столбцы и их типы):",
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+ st.session_state.current_description,
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+ height=150,
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+ key="desc_input"
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+ )
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+
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+ question = st.text_input(
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+ "Ваш вопрос:",
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+ st.session_state.current_question,
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+ key="question_input"
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+ )
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+
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+ submitted = st.form_submit_button("Сгенерировать запрос")
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+
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+ if submitted:
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+ if description and question:
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+ input_text = make_query(description, question)
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+ try:
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+ input_ids = tokenizer.encode(input_text, return_tensors="pt")
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+ with st.spinner("Генерация запроса..."):
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+ outputs = model.generate(
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+ input_ids,
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+ max_length=200,
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+ num_beams=5,
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+ early_stopping=True,
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+ pad_token_id=tokenizer.eos_token_id,
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+ )
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+ generated_sql = tokenizer.decode(outputs[0], skip_special_tokens=True)
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+ st.subheader("Результат:")
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+ st.code(generated_sql, language="sql")
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+ except Exception as e:
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+ st.error(f"Ошибка при генерации: {str(e)}")
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+ else:
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+ st.warning("Пожалуйста, заполните описание таблицы и вопрос")