Create app.py

app.py

@@ -0,0 +1,103 @@
+import os
+import csv
+import gradio as gr
+from gradio import inputs
+
+
+import huggingface_hub
+print("hfh", huggingface_hub.__version__)
+from huggingface_hub import hf_hub_download, upload_file
+from datetime import datetime
+
+DATASET_REPO_ID = "datasets/elonmuskceo/persistent-space-dataset"
+DATASET_REPO_URL = f"https://huggingface.co/{DATASET_REPO_ID}"
+DATA_DIRNAME = "data"
+DATA_FILENAME = "data.csv"
+DATA_FILE = os.path.join(DATA_DIRNAME, DATA_FILENAME)
+
+HF_TOKEN = os.environ.get("HF_TOKEN")
+
+
+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)
+
+
+try:
+    hf_hub_download(
+        repo_id=DATASET_REPO_ID,
+        filename=DATA_FILENAME,
+        cache_dir=DATA_DIRNAME,
+        force_filename=DATA_FILENAME
+    )
+except:
+    # file not found, we'll create it on the fly.
+    print("file not found, probably")
+
+
+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 = upload_file(
+            DATA_FILE,
+            path_in_repo=DATA_FILENAME,
+            repo_id=DATASET_REPO_ID,
+            token=HF_TOKEN,
+        )
+
+        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})",
+)
+
+iface.launch()