import os
import csv
import gradio as gr
from gradio import inputs, outputs
import huggingface_hub
from huggingface_hub import Repository
from datetime import datetime
DATASET_REPO_URL = "https://huggingface.co/datasets/julien-c/persistent-space-dataset"
DATA_FILENAME = "data.csv"
DATA_FILE = os.path.join("data", DATA_FILENAME)
HF_TOKEN = os.environ.get("HF_TOKEN")
print("is none?", HF_TOKEN is None)
print("hfh", huggingface_hub.__version__)
# 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>
"""
with open(os.path.join(gr.networking.STATIC_TEMPLATE_LIB, "frontend", "index.html"), "a") as f:
f.write(SCRIPT)
repo = Repository(
local_dir="data", clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
)
def generate_html() -> str:
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>{row['name']}</span>"
html += f"<span class='message'>{row['message']}</span>"
html += "</div>"
html += "</div>"
return html
def store_message(name: str, message: str):
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()
print(commit_url)
return generate_html()
iface = gr.Interface(
store_message,
[
inputs.Textbox(placeholder="Your name"),
inputs.Textbox(placeholder="Your message", lines=2),
],
"html",
css="""
.message {background-color:cornflowerblue;color:white; padding:4px;margin:4px;border-radius:4px; }
""",
title="Reading/writing to a HuggingFace dataset repo from Spaces",
description=f"This is a demo of how to do simple *shared data persistence* in a Gradio Space, backed by a dataset repo.",
article=f"The dataset repo is [{DATASET_REPO_URL}]({DATASET_REPO_URL}) (open in new tab)",
)
iface.launch()