import gradio as gr
import pandas as pd
from google.cloud import storage
import io
import os
import tempfile

gcs_bucket_name = "ow-stu-us-ce1-ai-platform"

# File path in GCS bucket
gcs_file_path = "deepak_6593/db.csv"


# process of getting credentials
def get_credentials():
    creds_json_str = os.getenv("BOB") # get json credentials stored as a string
    if creds_json_str is None:
        raise ValueError("GOOGLE_APPLICATION_CREDENTIALS_JSON not found in environment")

    # create a temporary file
    with tempfile.NamedTemporaryFile(mode="w+", delete=False, suffix=".json") as temp:
        temp.write(creds_json_str) # write in json format
        temp_filename = temp.name 

    return temp_filename
    
# pass
os.environ["GOOGLE_APPLICATION_CREDENTIALS"]= get_credentials()

# Ensure the GCS bucket exists
gcs_client = storage.Client()
gcs_bucket = gcs_client.bucket(gcs_bucket_name)

def get_data():
    blob = gcs_bucket.blob(gcs_file_path)
    return pd.read_csv(io.BytesIO(blob.download_as_bytes()))

with gr.Blocks() as demo:
    gr.Markdown("# 📈 Real-Time Line Plot")
    with gr.Row():
        with gr.Column():
            gr.DataFrame(get_data, every=1)
        with gr.Column():
            gr.LinePlot(get_data, every=1, x="category", y="score", y_title="score(marks)", overlay_point=True, width=500, height=500)

demo.queue().launch()