Update app.py

app.py

@@ -2,7 +2,6 @@ from huggingface_hub import InferenceClient
 import gradio as gr
 from deep_translator import GoogleTranslator
 
-# Initialize the Hugging Face Inference Client with the specific model
 client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
 
 # Function to translate Arabic text to English
@@ -13,7 +12,6 @@ def translate_to_english(text):
 def translate_to_arabic(text):
     return GoogleTranslator(source='english', target='arabic').translate(text)
 
-# Function to format the prompt with conversation history
 def format_prompt(message, history):
     prompt = "<s>"
     for user_prompt, bot_response in history:
@@ -22,8 +20,9 @@ def format_prompt(message, history):
     prompt += f"[INST] {message} [/INST]"
     return prompt
 
-# The main function to generate responses
-def generate(prompt, history=None, temperature=0.1, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0):
+def generate(
+    prompt, history, temperature=0.1, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0,
+):
     # Initialize history as an empty list if it's None
     if history is None:
         history = []
@@ -45,26 +44,23 @@ def generate(prompt, history=None, temperature=0.1, max_new_tokens=256, top_p=0.
     # Translate the Arabic prompt to English
     english_prompt = translate_to_english(prompt)
 
-    # Format the prompt with the conversation history
     formatted_prompt = format_prompt(english_prompt, history)
-    
+
     stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
     output = ""
-    
+
     for response in stream:
         output += response.token.text
-    
+
     # Translate the English response back to Arabic
     arabic_output = translate_to_arabic(output)
 
     # Update the history state with the latest exchange
     history.append((prompt, arabic_output))
 
-    # Return the response and the updated state
     return arabic_output, history
 
-# Additional input widgets for controlling the generation parameters
-additional_inputs = [
+additional_inputs=[
     gr.Slider(
         label="Temperature",
         value=0.9,
@@ -87,7 +83,7 @@ additional_inputs = [
         label="Top-p (nucleus sampling)",
         value=0.90,
         minimum=0.0,
-        maximum=1.0,
+        maximum=1,
         step=0.05,
         interactive=True,
         info="Higher values sample more low-probability tokens",
@@ -103,20 +99,9 @@ additional_inputs = [
     )
 ]
 
-# Creating and launching the Gradio interface
-iface = gr.Interface(
+gr.ChatInterface(
     fn=generate,
-    inputs=[
-        gr.Textbox(lines=2, placeholder="Enter your prompt in Arabic"),
-        gr.State()  # State input to maintain the conversation history
-    ] + additional_inputs,
-    outputs=[
-        gr.Textbox(placeholder="Generated response in Arabic"),
-        gr.State()  # State output to maintain the conversation history
-    ],
-    title="Try Arabic Misteral",
-    description="Interact with an advanced AI model in Arabic. Adjust the settings below to tailor the responses. Your prompts will be translated to English, processed by the AI, and the response will be translated back to Arabic."
-)
-
-# Launch the interface
-iface.launch()
+    chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
+    additional_inputs=additional_inputs,
+    title="DorjGPT interface"
+).launch(show_api=True)