Update app.py

app.py

@@ -1,32 +1,28 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import re
+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
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
+# Function to create an Inference Client based on selected model
+def create_inference_client(model_name):
+    return InferenceClient(model_name)
 
+# Function to generate a response
 def respond(
     message,
-    history: list[tuple[str, str]],
     system_message,
+    model,
     max_tokens,
     temperature,
     top_p,
 ):
-    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]})
+    # Create InferenceClient based on model selection
+    client = create_inference_client(model)
 
+    messages = [{"role": "system", "content": system_message}]
     messages.append({"role": "user", "content": message})
-
+    
     response = ""
-
     for message in client.chat_completion(
         messages,
         max_tokens=max_tokens,
@@ -35,30 +31,23 @@ def respond(
         top_p=top_p,
     ):
         token = message.choices[0].delta.content
-
         response += token
+        print(response)
         yield response
 
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-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)",
-        ),
+# Gradio interface setup
+demo = gr.Interface(
+    fn=respond,
+    inputs=[
+        gr.Textbox(label="User Message"),
+        gr.Textbox(value="한국어 문맥상 부자연스러운 부분을 찾으시오. 오류 문장과 개수는 <incorrect grammar> </incorrect grammar> tag, 즉 <incorrect grammar> - 오류 문장과 설명 </incorrect grammar> 안에 담겨 있으며, <wrong count> </wrong count> tag, 즉 <wrong count> 오류 개수 </wrong count> 이다.", label="System message"),
+        gr.Dropdown(choices=["davidkim205/kgrammar-2-1b", "davidkim205/kgrammar-2-3b"], value="davidkim205/kgrammar-2-1b", label="Model Selection"),
+        gr.Slider(minimum=1, maximum=2048, value=1024, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=1.0, step=0.1, label="Temperature"),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
     ],
+    outputs="textbox"
 )
 
-
 if __name__ == "__main__":
     demo.launch()