Update app.py

app.py

@@ -1,12 +1,32 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+from datasets import load_dataset
+import threading
+import time
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
+# Initialize the InferenceClient for Zephyr model
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
+# Function to load the latest dataset from Hugging Face
+def load_data():
+    dataset = load_dataset("accesscreate012/abhinav-academy-chatbot", split="train")
+    return {entry["question"]: entry["answer"] for entry in dataset}
 
+# Global variable to store the dataset
+data = load_data()
+
+# Function to update dataset every 24 hours
+def auto_update():
+    global data
+    while True:
+        time.sleep(86400)  # Wait for 24 hours before refreshing dataset
+        data = load_data()  # Reload the dataset
+        print("Dataset updated.")
+
+# Start the auto-update thread (runs in the background)
+threading.Thread(target=auto_update, daemon=True).start()
+
+# Chatbot response function using the InferenceClient
 def respond(
     message,
     history: list[tuple[str, str]],
@@ -15,8 +35,8 @@ def respond(
     temperature,
     top_p,
 ):
+    # Prepare the message history for the model
     messages = [{"role": "system", "content": system_message}]
-
     for val in history:
         if val[0]:
             messages.append({"role": "user", "content": val[0]})
@@ -35,30 +55,20 @@ def respond(
         top_p=top_p,
     ):
         token = message.choices[0].delta.content
-
         response += token
         yield response
 
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
+# Gradio interface
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
         gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max Tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
     ],
 )
 
-
+# Launch the interface
 if __name__ == "__main__":
     demo.launch()