app.py~

from huggingface_hub import InferenceClient
import gradio as gr
import os

API_URL = {
    "Mistral" : "https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.3",
    "Mixtral" : "https://api-inference.huggingface.co/models/mistralai/Mixtral-8x7B-Instruct-v0.1",
    "Mathstral" : "https://api-inference.huggingface.co/models/mistralai/mathstral-7B-v0.1",
}

HF_TOKEN = os.environ['HF_TOKEN']

mistralClient = InferenceClient(
    API_URL["Mistral"],
    headers = {"Authorization" : f"Bearer {HF_TOKEN}"},
)

mixtralClient = InferenceClient(
    model = API_URL["Mixtral"],
    headers = {"Authorization" : f"Bearer {HF_TOKEN}"},
)

mathstralClient = InferenceClient(
    model = API_URL["Mathstral"],
    headers = {"Authorization" : f"Bearer {HF_TOKEN}"},
)

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, temperature=0.9, max_new_tokens=256, top_p=0.95,
             repetition_penalty=1.0, model = "Mathstral"):
    # Selecting model to be used
    if(model == "Mistral"):
      client = mistralClient
    elif(model == "Mixstral"):
      client = mixtralClient
    elif(model == "Mathstral"):
      client = mixtralClient

    
    temperature = float(temperature) # Generation arguments
    if temperature < 1e-2:
        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(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.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=2048,
        minimum=0,
        maximum=4096,
        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.Dropdown(
        choices = ["Mistral","Mixtral", "Mathstral"],
        value = "Mathstral",
        label = "Le modèle à utiliser",
        interactive=True,
        info = "Mistral : pour des conversations génériques, "+ 
               "Mixtral : conversations plus rapides et plus performantes, "+ 
               "Mathstral : raisonnement mathématiques et scientifique"
    ),
]

css = """
  #mkd {
    height: 500px;
    overflow: auto;
    border: 1px solid #ccc;
  }
"""

with gr.Blocks(css=css) as demo:
    gr.HTML("<h1><center>Mathstral Test</center><h1>")
    gr.HTML("<h3><center>Dans cette démo, vous pouvez poser des questions mathématiques et scientifiques à Mathstral. 🧮</center><h3>")
    gr.ChatInterface(
        generate,
        additional_inputs=additional_inputs,
        theme = gr.themes.Soft(),
        cache_examples=False,
        examples=[ [l.strip()] for l in open("exercices.md").readlines()],
        chatbot = gr.Chatbot(
            latex_delimiters=[
                {"left" : "$$", "right": "$$", "display": True },
                {"left" : "\\[", "right": "\\]", "display": True },
                {"left" : "\\(", "right": "\\)", "display": False },
                {"left": "$", "right": "$", "display": False }
                ]
            )
    )

demo.queue(max_size=100).launch(debug=True)