Spaces:
Sleeping
Sleeping
File size: 3,165 Bytes
3b4ac2c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 |
import gradio as gr
from huggingface_hub import InferenceClient
import os
from dotenv import load_dotenv
# Charger les variables d'environnement
load_dotenv()
# Vérifie si la clé API est définie dans l'environnement
api_token = os.getenv("HF_API_TOKEN")
model_name = "mistralai/Mistral-7B-Instruct-v0.3"
if not api_token:
raise ValueError("API token is required. Please set it in your .env file.")
# Initialiser le client d'inférence
client = InferenceClient(token=api_token, model=model_name)
# Fonction de réponse
def respond(message, history, system_message, max_tokens, temperature, top_p):
messages = [{"role": "system", "content": system_message}]
for user, assistant in history:
if user:
messages.append({"role": "user", "content": user})
if assistant:
messages.append({"role": "assistant", "content": assistant})
messages.append({"role": "user", "content": message})
response = ""
try:
for message in client.chat_completion(
messages, max_tokens=max_tokens, stream=True, temperature=temperature, top_p=top_p
):
token = message.choices[0].delta.content
response += token
yield response
except Exception as e:
yield f"Error: {str(e)}"
# Interface utilisateur avec Gradio
demo = gr.Blocks()
with demo:
# Header avec le logo et le slogan
with gr.Row():
gr.Image("logo.png", show_label=False, interactive=False, elem_id="logo", scale=1)
gr.Markdown(
"""
<div style="text-align: center;">
<h1 style="color: #0fa86b;">SHAURI</h1>
<p style="font-size: 16px; color: #000;">Un test avec le modèle Mistral via l'API Hugging Face</p>
</div>
"""
)
# Composant Chatbot
chatbot = gr.Chatbot(label="Chat History")
# Zone de saisie utilisateur
with gr.Row():
user_input = gr.Textbox(label="Your Message", placeholder="Type your message here...", lines=1)
# Réglages du système et paramètres
with gr.Row():
system_message = gr.Textbox(
value="You are a friendly Chatbot.",
label="System Message",
lines=2,
)
with gr.Row():
max_tokens = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens")
temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)")
# Interaction entre l'utilisateur et le chatbot
def handle_message(message, history, system_msg, max_toks, temp, top_p_val):
if history is None:
history = []
for response in respond(message, history, system_msg, max_toks, temp, top_p_val):
history.append((message, response))
yield history, ""
user_input.submit(
fn=handle_message,
inputs=[user_input, chatbot, system_message, max_tokens, temperature, top_p],
outputs=[chatbot, user_input],
)
if __name__ == "__main__":
demo.launch()
|