final_feedback.py

import os
import csv
import gradio as gr
from gradio import components
from huggingface_hub import Repository, hf_hub_download
from datetime import datetime
from final_msgs import FEED_HEADER


DATASET_REPO_URL = "https://huggingface.co/datasets/sjw/data.csv"
DATASET_REPO_ID = "sjw/data.csv"
DATA_FILENAME = "data.csv"
DIRNAME = "data"
DATA_FILE = os.path.join(DIRNAME, DATA_FILENAME)
HF_TOKEN = os.environ.get("HF_TOKEN")


# overriding/appending to the gradio template
SCRIPT = """
<script>
if (!window.hasBeenRun) {
    window.hasBeenRun = true;
    console.log("should only happen once");
    document.querySelector("button.submit").click();
}
</script>
"""


try:
    hf_hub_download(
        repo_id=DATASET_REPO_ID,
        filename=DATA_FILENAME,
    )
except:
    print("file not found")


repo = Repository(
    local_dir=DIRNAME, 
    clone_from=DATASET_REPO_URL, 
    use_auth_token=HF_TOKEN
)


def generate_html() -> str:
    """Generate HTML content for the chat."""
    with open(DATA_FILE) as csvfile:
        reader = csv.DictReader(csvfile)
        rows = []
        for row in reader:
            rows.append(row)
        rows.reverse()
        if len(rows) == 0:
            return "no messages yet"
        else:
            html = "<div class='chatbot'>"
            for row in rows:
                html += "<div>"
                html += f"<span><b>{row['name']}</b></span> "  # Make the name bold and add a space after it
                html += f"<span class='message'>{row['message']}</span>"
                html += "</div>"
            html += "</div>"
            return html


def store_message(name: str, message: str):
    """Store the message and regenerate HTML content."""
    if name and message:
        with open(DATA_FILE, "a") as csvfile:
            writer = csv.DictWriter(csvfile, fieldnames=["name", "message", "time"])
            writer.writerow(
                {"name": name, "message": message, "time": str(datetime.now())}
            )
        commit_url = repo.push_to_hub()
    return generate_html()


with gr.Blocks() as feedback_page:
    gr.Markdown(FEED_HEADER)
    #gr.Markdown(f"Live Dataset: [{DATASET_REPO_URL}]({DATASET_REPO_URL})")
    name_input = components.Textbox(label="Username")
    message_input = components.Textbox(label="Feedback", lines=2)
    output_html = gr.HTML()
    submit_button = gr.Button("Submit")
    submit_button.click(store_message, inputs=[name_input, message_input], outputs=output_html)

#feedback_page.launch()