Update app.py

app.py

@@ -1,24 +1,27 @@
-import gradio as gr
 from huggingface_hub import InferenceClient
+import gradio as gr
+
+client = InferenceClient(
+    "mistralai/Mistral-7B-Instruct-v0.3"
+)
 
-# Initializing the Hugging Face client
-client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.3")
 
-# Helper function to format the prompt for the model
 def format_prompt(message, history):
-    prompt = "<s>"
-    for user_prompt, bot_response in history:
-        prompt += f"[INST] {user_prompt} [/INST]"
-        prompt += f" {bot_response}</s> "
-    prompt += f"[INST] {message} [/INST]"
-    return prompt
-
-# Function to generate responses using the model
-def generate(prompt, history, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0):
+  prompt = "<s>"
+  for user_prompt, bot_response in history:
+    prompt += f"[INST] {user_prompt} [/INST]"
+    prompt += f" {bot_response}</s> "
+  prompt += f"[INST] {message} [/INST]"
+  return prompt
+
+def generate(
+    prompt, history, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0,
+):
     temperature = float(temperature)
     if temperature < 1e-2:
         temperature = 1e-2
     top_p = float(top_p)
+
     generate_kwargs = dict(
         temperature=temperature,
         max_new_tokens=max_new_tokens,
@@ -27,30 +30,62 @@ def generate(prompt, history, temperature=0.9, max_new_tokens=256, top_p=0.95, r
         do_sample=True,
         seed=42,
     )
+
     formatted_prompt = format_prompt(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
         yield output
     return output
 
-# Additional interface inputs such as sliders
-additional_inputs = [
-    gr.Slider(label="Temperature", value=0.9, minimum=0.0, maximum=1.0, step=0.05, interactive=True, info="Higher values produce more diverse outputs"),
-    gr.Slider(label="Max new tokens", value=256, minimum=0, maximum=1048, step=64, interactive=True, info="The maximum numbers of new tokens"),
-    gr.Slider(label="Top-p (nucleus sampling)", value=0.90, minimum=0.0, maximum=1, step=0.05, interactive=True, info="Higher values sample more low-probability tokens"),
-    gr.Slider(label="Repetition penalty", value=1.2, minimum=1.0, maximum=2.0, step=0.05, interactive=True, info="Penalize repeated tokens")
+
+additional_inputs=[
+    gr.Slider(
+        label="Temperature",
+        value=0.9,
+        minimum=0.0,
+        maximum=1.0,
+        step=0.05,
+        interactive=True,
+        info="Higher values produce more diverse outputs",
+    ),
+    gr.Slider(
+        label="Max new tokens",
+        value=256,
+        minimum=0,
+        maximum=1048,
+        step=64,
+        interactive=True,
+        info="The maximum numbers of new tokens",
+    ),
+    gr.Slider(
+        label="Top-p (nucleus sampling)",
+        value=0.90,
+        minimum=0.0,
+        maximum=1,
+        step=0.05,
+        interactive=True,
+        info="Higher values sample more low-probability tokens",
+    ),
+    gr.Slider(
+        label="Repetition penalty",
+        value=1.2,
+        minimum=1.0,
+        maximum=2.0,
+        step=0.05,
+        interactive=True,
+        info="Penalize repeated tokens",
+    )
 ]
 
-# Setting up the theme with primary color as pink
-theme = gr.Theme(primary_hue="pink")
+theme = gr.Theme(primary_hue="pink", secondary_hue="pink")
 
-# Creating the chat interface with the modified theme
 gr.ChatInterface(
     fn=generate,
     chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
     additional_inputs=additional_inputs,
-    title="Mistral 7B v0.3",
-    theme=theme
-).launch(show_api=False)
+    title="""Mistral 7B v0.3"""
+).launch(show_api=False)