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| import streamlit as st | |
| from text2sql import ChatBot | |
| from transformers import ( | |
| AutoTokenizer, | |
| AutoModelForSequenceClassification, | |
| logging as hf_logging | |
| ) | |
| from langdetect import detect | |
| from utils.translate_utils import translate_zh_to_en | |
| from utils.db_utils import add_a_record | |
| from langdetect.lang_detect_exception import LangDetectException | |
| import os | |
| # -------- Streamlit Web Application -------- | |
| text2sql_bot = ChatBot() | |
| baidu_api_token = None # Your Baidu API token (if needed for translation) | |
| # Define some database schemas for demonstration purposes | |
| db_schemas = { | |
| "singer": """ | |
| CREATE TABLE "singer" ( | |
| "Singer_ID" int, | |
| "Name" text, | |
| "Birth_Year" real, | |
| "Net_Worth_Millions" real, | |
| "Citizenship" text, | |
| PRIMARY KEY ("Singer_ID") | |
| ); | |
| CREATE TABLE "song" ( | |
| "Song_ID" int, | |
| "Title" text, | |
| "Singer_ID" int, | |
| "Sales" real, | |
| "Highest_Position" real, | |
| PRIMARY KEY ("Song_ID"), | |
| FOREIGN KEY ("Singer_ID") REFERENCES "singer"("Singer_ID") | |
| ); | |
| """, | |
| # More schemas can be added here | |
| } | |
| # Streamlit interface | |
| st.title("Text-to-SQL Chatbot") | |
| st.sidebar.header("Select a Database") | |
| selected_db = st.sidebar.selectbox("Choose a database:", list(db_schemas.keys())) | |
| st.sidebar.text_area("Database Schema", db_schemas[selected_db], height=600) | |
| # Get user input for the question | |
| question = st.text_input("Enter your question:") | |
| db_id = selected_db | |
| if question: | |
| # Store the question in the database (or perform any additional processing) | |
| add_a_record(question, db_id) | |
| try: | |
| # If translation is required, handle it here | |
| if baidu_api_token and detect(question) != "en": | |
| question = translate_zh_to_en(question, baidu_api_token) | |
| except LangDetectException as e: | |
| st.warning(f"Language detection error: {e}") | |
| # Get the model's response (in this case, SQL query or logits) | |
| response = text2sql_bot.get_response(question, db_id) | |
| st.write(f"**Database:** {db_id}") | |
| st.write(f"**Results:** {response}") |