Update app.py

app.py

@@ -12,80 +12,63 @@ 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/ChatbotMemory.csv"
-DATASET_REPO_ID = "awacke1/ChatbotMemory.csv"
-DATA_FILENAME = "ChatbotMemory.csv"
-DATA_FILE = os.path.join("data", DATA_FILENAME)
-HF_TOKEN = os.environ.get("HF_TOKEN")
 
-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,
-        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
-)
+# -------------------------------------------- For Memory - you will need to set up a dataset and HF_TOKEN ---------
+#DATASET_REPO_URL = "https://huggingface.co/datasets/awacke1/ChatbotMemory.csv"
+#DATASET_REPO_ID = "awacke1/ChatbotMemory.csv"
+#DATA_FILENAME = "ChatbotMemory.csv"
+#DATA_FILE = os.path.join("data", DATA_FILENAME)
+#HF_TOKEN = os.environ.get("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['inputs']}</span>"
-                html += f"<span class='outputs'>{row['outputs']}</span>"
-                html += "</div>"
-            html += "</div>"
-            return html
-            
+#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,
+#        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 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.strip(), "message": message.strip(), "time": str(datetime.now())}
-            )
-        # uncomment line below to begin saving.  If creating your own copy you will need to add a access token called "HF_TOKEN" to your profile, then create a secret for your repo with the access code naming it "HF_TOKEN"  For the CSV as well you can copy the header and first few lines to your own then update the paths above which should work to save to your own repository for datasets.    
-        commit_url = repo.push_to_hub()
-    return ""
+#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.strip(), "message": message.strip(), "time": str(datetime.now())}
+#            )
+# uncomment line below to begin saving.  If creating your own copy you will need to add a access token called "HF_TOKEN" to your profile, then create a secret for your repo with the access code naming it "HF_TOKEN"  For the CSV as well you can copy the header and first few lines to your own then update the paths above which should work to save to your own repository for datasets.    
+#        commit_url = repo.push_to_hub()
+#    return ""
     
-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 = 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})",
+#)
+# --------------------------------------------------- For Memory
 
 mname = "facebook/blenderbot-400M-distill"
 model = BlenderbotForConditionalGeneration.from_pretrained(mname)
@@ -135,7 +118,7 @@ gr.Interface(
     title=title,
     allow_flagging="never",
     description=f"Gradio chatbot backed by memory in a dataset repository.",
-    article=f"The dataset repo is [{DATASET_REPO_URL}]({DATASET_REPO_URL})"
+#    article=f"The dataset repo is [{DATASET_REPO_URL}]({DATASET_REPO_URL})"
     ).launch()
         
 #demo = gr.Blocks()