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import gradio as gr
from huggingface_hub import InferenceClient

# 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

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,
  )

  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

# Define inputs (user interface elements)
system_prompt_input = gr.Textbox(label="System Prompt", max_lines=1, interactive=True)
slider_temperature = 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")
slider_max_tokens = gr.Slider(label="Max new tokens", value=9048, minimum=256, maximum=9048, step=64, interactive=True, info="The maximum numbers of new tokens")
slider_top_p = 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")
slider_repetition_penalty = gr.Slider(label="Repetition penalty", value=1.2, minimum=1.0, maximum=2.0, step=0.05, interactive=True, info="Penalize repeated tokens")
inputs = [system_prompt_input] + [slider_temperature, slider_max_tokens, slider_top_p, slider_repetition_penalty]

# Define output (generated text)
output_text = gr.Textbox(label="Output")

# Create the Gradio interface
gr.Interface(
  fn=generate,
  chatbot=gr.Chatbot(show_label=True, show_share_button=True, show_copy_button=True, likeable=True, layout="panel"),
  inputs=inputs,
  outputs=output_text,
  title="ConvoLite",
  description="Remember! The AI might give incorrect information about people, locations, history, etc...",
  concurrency_limit=20,
  theme=gr.themes.Soft()
).launch(show_api=False,)