Update app.py

app.py

@@ -2,6 +2,89 @@ from transformers import BlenderbotTokenizer, BlenderbotForConditionalGeneration
 import torch
 import gradio as gr
 
+
+# PersistDataset -----
+import os
+import csv
+import gradio as gr
+from gradio import inputs, outputs
+import huggingface_hub
+from huggingface_hub import Repository, hf_hub_download, upload_file
+from datetime import datetime
+DATASET_REPO_URL = "https://huggingface.co/datasets/awacke1/Carddata.csv"
+DATASET_REPO_ID = "awacke1/Carddata.csv"
+DATA_FILENAME = "Carddata.csv"
+DATA_FILE = os.path.join("data", 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>
+"""
+#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:
+    print("file not found")
+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()
+    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()
+# -------
+
+
 mname = "facebook/blenderbot-400M-distill"
 model = BlenderbotForConditionalGeneration.from_pretrained(mname)
 tokenizer = BlenderbotTokenizer.from_pretrained(mname)