import gradio as gr
import numpy as np
import matplotlib.pyplot as plt
import cv2
from io import BytesIO
import uuid
import csv
import os
import requests
import json

AIRTABLE_TOKEN = os.environ.get("AIRTABLE_TOKEN")

def send_to_airtable(data):
    url = "https://api.airtable.com/v0/appHgBulDLVnlf3uS/simt_ap05032024"
    headers = {
        "Authorization": f"Bearer {AIRTABLE_TOKEN}",
        "Content-Type": "application/json"
    }
    data = json.dumps(data)
    print(data)
    response = requests.post(url, headers=headers, data=data)
    print(response.text)
    return response.text

# Path to the CSV file for storing session data
data_file_path = 'queries_data.csv'

# Function to initialize the CSV file if it does not exist
def initialize_data_file():
    if not os.path.exists(data_file_path):
        with open(data_file_path, 'w', newline='') as file:
            writer = csv.writer(file)
            writer.writerow(['session_id', 'x', 'y'])

# Ensure the data file is initialized
initialize_data_file()

def log_data(session_id, x, y):
    with open(data_file_path, 'a', newline='') as file:
        writer = csv.writer(file)
        writer.writerow([session_id, x, y])
        
    #send to airtable
    data = {
        "fields": {
            "session_id": session_id,
            "x": x,
            "y": y
        }
    }
    send_to_airtable(data)

def draw_points(points, query_count, session_id=""):
    plt.figure(figsize=(12, 8))
    if points:
        x_vals, y_vals = zip(*points)
        cmap = plt.get_cmap('viridis')
        for i, (x_val, y_val) in enumerate(points):
            plt.scatter(x_val, y_val, color=cmap(i / len(points)))
            plt.text(x_val, y_val + 50, str(i + 1), fontsize=7, ha='center')

        plt.xlabel('x')
        plt.ylabel('f(x)')
        plt.ylim(-1000, 1000)
        plt.grid(True)
        plt.axhline(0, color='black', linewidth=0.5)
        plt.axvline(0, color='black', linewidth=0.5)
        plt.title(f'Sampled Points - Query {query_count[0] + 1} ({session_id})')
        buf = BytesIO()
        plt.savefig(buf, format='png')
        plt.close()
        buf.seek(0)
        image = np.frombuffer(buf.getvalue(), dtype=np.uint8)
        image = cv2.imdecode(image, cv2.IMREAD_COLOR)
        return image

def f(x, scale=1000):
    x_scaled = x / scale
    polynomial = (x_scaled**4 - 10*x_scaled**3 + 35*x_scaled**2 - 50*x_scaled + 24) / 4000
    sinusoidal = 800 * np.sin(abs(x_scaled)/10) + 500 * np.cos(x_scaled/8) + 200 * np.sin(x_scaled/2)
    y_value = 800 * np.tanh((polynomial + sinusoidal) / 1000)
    return y_value


def custom_function(x, query_count, points, session_state, nqueries=10):
    session_id = session_state['session_id'] if session_state['session_id'] else str(uuid.uuid4())[:6]
    session_state['session_id'] = session_id  # Update state with the current or new session ID

    if query_count[0] >= nqueries:
        return None, query_count, "Query limit reached", "", session_state

    try:
        x = float(x)
    except ValueError:
        return None, query_count, "Invalid input: Please enter a numeric value", "", session_state

    y_value = f(x)
    points.append((x, y_value))
    log_data(session_id, x, y_value)
    img = draw_points(points, query_count, session_id)
    query_count[0] += 1
    remaining_queries = nqueries - query_count[0]
    points_list = '\n'.join([f"x: {p[0]:.0f}, y: {p[1]:.3f}" for p in points])
    return img, query_count, f"{remaining_queries} queries remaining", points_list, session_state

with gr.Blocks() as app:
    query_count = gr.State([0])
    points = gr.State([])
    session_state = gr.State({'session_id': None})  # Initialize state for session_id

    with gr.Row():
        x_input = gr.Number(label="X")
        submit_button = gr.Button("Submit")
        
    with gr.Row():
        remaining_queries_label = gr.Label(elem_id="remaining_queries")
        points_display = gr.Textbox(label="Queried Points", lines=10, interactive=False, value="", elem_id="queried_points")
        
    with gr.Row():
        output_image = gr.Image(label="Plot", elem_id="plot_image", width="100vw")

    submit_button.click(
        custom_function,
        inputs=[x_input, query_count, points, session_state],
        outputs=[output_image, query_count, remaining_queries_label, points_display, session_state]
    )

app.launch(share=True)