Update app.py

app.py

@@ -4,47 +4,23 @@
 import gradio as gr
 from transformers import pipeline
 import torch
+import huggingfacehub as infer
 import threading
 import time
 import tensorflow as tf
+mport gradio as gr
+from transformers import pipeline
 
-# Check GPU availability
-print(torch.cuda.is_available())
-print(tf.test.gpu_device_name())
-
-# Initialize the text generation pipeline with the specified model
-pipe = pipeline("text-generation", model="chargoddard/Yi-34B-Llama", device=0)
-
-# Rate limiting parameters
-rate_limit = 5  # Number of requests per second
-last_request_time = 0
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    global last_request_time
 
-    # Apply rate limiting
-    elapsed_time = time.time() - last_request_time
-    if elapsed_time < 1.0 / rate_limit:
-        time.sleep(1.0 / rate_limit - elapsed_time)
 
-    last_request_time = time.time()
 
-    messages = [{"role": "system", "content": system_message}]
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+# Initialize the text generation pipeline with the specified model
+pipe = pipeline("text-generation", model="chargoddard/Yi-34B-Llama", device=0)
 
-    messages.append({"role": "user", "content": message})
+def respond(
+    message,
 
     response = ""
 
@@ -57,25 +33,19 @@ def respond(
         top_p=top_p,
     )
 
+
     response = result[0]['generated_text']
     yield response
 
 # Gradio interface setup
+
+
 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=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)",
-        ),
     ],
 )
 
-# Launch the Gradio interface
-demo.launch()
+
+if __name__ == "__main__":
+    demo.launch()