Update app.py

app.py

@@ -1,58 +1,95 @@
 from huggingface_hub import InferenceClient
+
 import gradio as gr
+
 import datetime
 
 # Initialize the InferenceClient
+
 client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
 
 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
+
+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, system_prompt, temperature=0.9, max_new_tokens=9048, top_p=0.95, repetition_penalty=1.0):
-    temperature = max(float(temperature), 1e-2)
-    top_p = float(top_p)
-    generate_kwargs = dict(
-        temperature=temperature,
-        max_new_tokens=max_new_tokens,
-        top_p=top_p,
-        repetition_penalty=repetition_penalty,
-        do_sample=True,
-        seed=42,
-    )
-
-    # Get current time
-    now = datetime.datetime.now()
-    formatted_time = now.strftime("%H.%M.%S, %B, %Y")
-    system_prompt = f"server log: ~This message was sent at {formatted_time}. The actual year is 2024.~"
-
-    formatted_prompt = format_prompt(f"{system_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 (prompt, output)
+
+temperature = max(float(temperature), 1e-2)
+
+top_p = float(top_p)
+
+generate_kwargs = dict(
+
+temperature=temperature,
+
+max_new_tokens=max_new_tokens,
+
+top_p=top_p,
+
+repetition_penalty=repetition_penalty,
+
+do_sample=True,
+
+seed=42,
+
+)
+
+# Get current time
+
+now = datetime.datetime.now()
+
+formatted_time = now.strftime("%H.%M.%S, %B, %Y")
+
+system_prompt = f"server log: This message was sent at {formatted_time}. The actual year is 2024."
+
+formatted_prompt = format_prompt(f"{system_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_inputs = [
-    gr.Textbox(label="System Prompt", max_lines=1, interactive=True),
-    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=9048, minimum=256, maximum=9048, 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")
+
+gr.Textbox(label="System Prompt", max_lines=1, interactive=True),
+
+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=9048, minimum=256, maximum=9048, 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")
+
 ]
 
-app = gr.Blocks(theme=gr.themes.Soft())
-with app:
-    chatbot = gr.Chatbot()
-    text_input = gr.Textbox(label="Your message")
+gr.ChatInterface(
+
+fn=generate,
+
+chatbot=gr.Chatbot(show_label=True, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
+
+additional_inputs=additional_inputs,
+
+title="ConvoLite",
 
-    def process_message(message, history):
-        for response in generate(message, history, additional_inputs[0].value):
-            yield response
+concurrency_limit=20,
 
-    text_input.submit(process_message, inputs=[text_input, chatbot], outputs=[chatbot, text_input])
-    app.launch(show_api=False)
+).launch(show_api=False,)