import json
import logging
import os
import datetime
import gradio as gr
from huggingface_hub import HfApi, HfFolder
# Set up logging
logging.basicConfig(level=logging.INFO)

logger = logging.getLogger(__name__)

# Define the function to convert text to JSON
def text_to_json(text):
    lines = text.strip().split('\n')
    data = [{"text": line} for line in lines]
    timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
    filename = f"converted/output_{timestamp}.json"
    with open(filename, "w") as f:
        json.dump(data, f, indent=4)
    return filename

# Define the function to generate and upload the JSON file
def generate_and_upload(text):
    try:
        if not text:
            raise ValueError("Text input is empty.")
        
        logger.info(f"Received text input: {text}")
        
        # Convert text to JSON and save to file
        json_file = text_to_json(text)
        logger.info(f"JSON file created: {json_file}")
        
        # Authenticate with Hugging Face Hub
        api = HfApi()
        token = os.environ['HUGGINGFACE_API_TOKEN']
        if token is None:
            raise ValueError("Hugging Face API token not found. Please set HUGGINGFACE_API_TOKEN environment variable.")
        
        # Upload the file to the dataset repository
        repo_id = "katsukiai/DeepFocus-X3"
        upload_info = api.upload_file(
            path_or_fileobj=json_file,
            path_in_repo=os.path.basename(json_file),
            repo_id=repo_id,
            repo_type="dataset",
            token=token
        )
        logger.info(f"Upload info: {upload_info}")
        message = f"Upload successful! Filename: {os.path.basename(json_file)}"
        return message, json_file
    except Exception as e:
        logger.error(f"Error uploading file: {e}")
        return f"Error: {e}", None




# Create the Gradio interface
with gr.Blocks() as demo:
    with gr.Tab("About"):
        gr.Markdown("""
        # Text to JSON uploader
        This app allows you to input text, convert it to JSON format, and upload it to the Hugging Face dataset repository.
        
        ## Instructions
        1. Enter your text in the "Generate" tab.
        2. Click the "Generate and Upload" button.
        3. Download the JSON file if desired.
        4. Check the message for upload status.
        
        ## Requirements
        - Hugging Face API token set as environment variable `HUGGINGFACE_API_TOKEN`.
        
        ## Obtaining Hugging Face API Token
        1. Log in to your Hugging Face account.
        2. Go to your profile settings.
        3. Generate a new token or use an existing one.
        4. Set the token as an environment variable named `HUGGINGFACE_API_TOKEN`.
        
        ## Setting Environment Variable
        - **Windows**: Set it in System Properties > Advanced > Environment Variables.
        - **macOS/Linux**: Add `export HUGGINGFACE_API_TOKEN=your_token` to your shell profile (e.g., `.bashrc`, `.zshrc`).
        """)
    
    with gr.Tab("Generate"):
        text_input = gr.Textbox(label="Enter text")
        output_message = gr.Textbox(label="Status message")
        json_file_downloader = gr.File(label="Download JSON", interactive=False)
        generate_button = gr.Button("Generate and Upload")
        generate_button.click(fn=generate_and_upload, inputs=text_input, outputs=[output_message, json_file_downloader])
        
# Launch the Gradio app
demo.launch()