app.py

import os
import gradio as gr
from sqlalchemy import text, inspect, create_engine
from smolagents import tool, CodeAgent, HfApiModel
import pandas as pd
import tempfile
from database import engine, initialize_database

# Ensure the database initializes (won't crash if empty)
initialize_database()

# Function to execute an uploaded SQL script
def execute_sql_script(file_path):
    """
    Executes an uploaded SQL file to initialize the database.

    Args:
        file_path (str): Path to the SQL file.

    Returns:
        str: Success message or error description.
    """
    try:
        with engine.connect() as con:
            with open(file_path, "r") as f:
                sql_script = f.read()
                con.execute(text(sql_script))
        return "SQL file executed successfully. Database updated."
    except Exception as e:
        return f"Error: {str(e)}"

# Function to get table names dynamically
def get_table_names():
    """
    Returns a list of tables available in the database.

    Returns:
        list: List of table names.
    """
    inspector = inspect(engine)
    return inspector.get_table_names()

# Function to get table schema dynamically
def get_table_schema(table_name):
    """
    Returns a list of column names for a given table.

    Args:
        table_name (str): Name of the table.

    Returns:
        list: List of column names.
    """
    inspector = inspect(engine)
    columns = inspector.get_columns(table_name)
    return [col["name"] for col in columns]

# Function to fetch data dynamically from any table
def get_table_data(table_name):
    """
    Retrieves all rows from a specified table as a Pandas DataFrame.

    Args:
        table_name (str): Name of the table.

    Returns:
        pd.DataFrame: Table data or an error message.
    """
    try:
        with engine.connect() as con:
            result = con.execute(text(f"SELECT * FROM {table_name}"))
            rows = result.fetchall()

        columns = get_table_schema(table_name)

        if not rows:
            return pd.DataFrame(columns=columns)

        return pd.DataFrame(rows, columns=columns)
    except Exception as e:
        return pd.DataFrame({"Error": [str(e)]})

# Function to handle SQL file uploads and execute them
def handle_file_upload(file):
    """
    Handles SQL file upload, executes SQL, and updates database schema.

    Args:
        file (File): Uploaded SQL file.

    Returns:
        tuple: Execution result message and updated table data.
    """
    temp_file_path = tempfile.mkstemp(suffix=".sql")[1]
    with open(temp_file_path, "wb") as temp_file:
        temp_file.write(file.read())
    
    result = execute_sql_script(temp_file_path)
    tables = get_table_names()

    if tables:
        table_data = {table: get_table_data(table) for table in tables}
    else:
        table_data = {"Error": ["No tables found after execution. Ensure your SQL file creates tables."]}

    return result, table_data

# Initialize CodeAgent for SQL query generation
agent = CodeAgent(
    tools=[sql_engine],
    model=HfApiModel(model_id="Qwen/Qwen2.5-Coder-32B-Instruct"),
)

# Gradio UI
with gr.Blocks() as demo:
    gr.Markdown("## SQL Query Interface")

    with gr.Row():
        user_input = gr.Textbox(label="Ask a question about the data")
        query_output = gr.Textbox(label="Result")

    user_input.change(fn=handle_query, inputs=user_input, outputs=query_output)

    gr.Markdown("## Upload SQL File to Execute")
    file_upload = gr.File(label="Upload SQL File")
    upload_output = gr.Textbox(label="Execution Result")

    # Dynamic table display
    table_output = gr.Dataframe(label="Database Tables (Dynamic)")

    file_upload.change(fn=handle_file_upload, inputs=file_upload, outputs=[upload_output, table_output])

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860, share=True)