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| import streamlit as st | |
| import pandas as pd | |
| import sqlite3 | |
| import plotly.express as px | |
| import json | |
| # Set paths to the default files | |
| DEFAULT_PROMPT_PATH = "prompt_engineering.json" | |
| DEFAULT_METADATA_PATH = "default_metadata.csv" | |
| DEFAULT_DATA_PATH = "default_data.csv" | |
| # Load the prompt engineering JSON file (use default if no user-uploaded prompt file) | |
| with open(DEFAULT_PROMPT_PATH) as f: | |
| prompt_data = json.load(f) | |
| # Function to find a query based on the user prompt | |
| def get_query_from_prompt(user_prompt): | |
| for item in prompt_data['prompts']: | |
| if item['question'].lower() in user_prompt.lower(): | |
| return item['query'] | |
| return None # Return None if no matching query is found | |
| # Step 1: Upload metadata.csv file (or use default) | |
| metadata_file = st.file_uploader("Upload your metadata.csv file", type=["csv"]) | |
| if metadata_file is None: | |
| metadata = pd.read_csv(DEFAULT_METADATA_PATH) | |
| st.write("Using default metadata.csv file.") | |
| else: | |
| metadata = pd.read_csv(metadata_file) | |
| st.write("Metadata loaded successfully!") | |
| st.dataframe(metadata) | |
| # Step 2: Upload CSV data file (or use default) | |
| csv_file = st.file_uploader("Upload your CSV file", type=["csv"]) | |
| if csv_file is None: | |
| data = pd.read_csv(DEFAULT_DATA_PATH) | |
| st.write("Using default data.csv file.") | |
| else: | |
| data = pd.read_csv(csv_file) | |
| st.write("Data Preview:") | |
| st.dataframe(data.head()) | |
| # Step 3: Load CSV data into a SQLite database (SQL agent) | |
| conn = sqlite3.connect(':memory:') # Use an in-memory SQLite database | |
| data.to_sql('sales_data', conn, index=False, if_exists='replace') | |
| # Step 4: Get user prompt and map to SQL query | |
| user_prompt = st.text_input("Enter your natural language prompt:") | |
| # Step 5: Process the prompt and generate SQL query dynamically | |
| if user_prompt: | |
| query = get_query_from_prompt(user_prompt) | |
| if query: | |
| result = pd.read_sql(query, conn) | |
| st.write("Query Results:") | |
| st.dataframe(result) | |
| # If the query involves plotting (like "plot sales"), show the chart | |
| if "plot" in user_prompt.lower(): | |
| fig = px.bar(result, x='Date', y='Sales', title="Sales Over Time") | |
| st.plotly_chart(fig) | |
| else: | |
| st.write("Sorry, I couldn't find a matching query for your prompt.") | |