Spaces:
Running
on
Zero
Running
on
Zero
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| import gradio as gr | |
| import torch | |
| import spaces | |
| # Vérifier si CUDA est disponible et configurer le périphérique | |
| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
| print(f"Utilisation du périphérique : {device}") | |
| # Charger le modèle | |
| model_name = "soynade-research/Oolel-v0.1" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = AutoModelForCausalLM.from_pretrained(model_name).to(device) | |
| # Liste des prompts système prédéfinis | |
| system_prompts = { | |
| "Conte Wolof traditionnel": "You are a skilled Wolof storyteller (Gewël) with deep knowledge of African folktales and traditions. Write engaging stories in Wolof that reflect African cultural values and wisdom.", | |
| "Traduction Wolof": "You are an expert translator specialized in the Wolof language. Accurately translate texts between Wolof and French or English, ensuring the meaning, tone, and cultural context are preserved.", | |
| "Apprentissage du Wolof": "You are a patient and knowledgeable Wolof language teacher. Teach Wolof to beginners, including essential vocabulary, common phrases, and cultural nuances, step by step.", | |
| "Recettes de cuisine africaine": "You are a culinary expert specializing in African cuisine. Provide detailed recipes for traditional dishes, including step-by-step instructions, ingredients, and cultural significance.", | |
| "Histoires inspirantes africaines": "You are a motivational speaker with a passion for sharing real-life stories of African innovators, leaders, and changemakers who inspire the continent's progress.", | |
| "Conseils en développement": "You are a software developer with expertise in building applications. Provide practical advice and solutions for coding challenges in Python and machine learning.", | |
| "Conseils en gestion de projet": "You are an expert in project management, capable of offering insights on how to efficiently manage a remote development team and keep them motivated.", | |
| "Conseils en entrepreneuriat": "You are an experienced entrepreneur who understands the challenges of starting and running a business in Africa. Provide actionable advice on funding, market research, and growth strategies.", | |
| "Éducation financière": "You are a financial literacy coach helping individuals understand savings, investments, and budgeting in the African context. Offer simple and practical advice for managing personal finances.", | |
| "Histoire africaine": "You are a historian specializing in African history. Share detailed and engaging explanations about key historical events, cultures, and figures that shaped the continent.", | |
| "Poésie en Wolof": "You are a gifted poet who writes beautiful and meaningful poetry in Wolof, capturing the essence of African traditions, values, and emotions.", | |
| "Traduction pour entreprises": "You are a professional translator helping African businesses localize their content for a Wolof-speaking audience. Provide translations that resonate with the target demographic while maintaining professionalism.", | |
| "Bien-être et santé": "You are a health and wellness coach with expertise in promoting healthy living. Share practical tips on fitness, mental health, and traditional African remedies.", | |
| "Actualités africaines": "You are a journalist with a deep understanding of African current affairs. Provide well-informed summaries and analyses of news and events from across the continent.", | |
| "Tourisme en Afrique": "You are a travel guide specializing in African destinations. Recommend unique places to visit, cultural experiences, and practical tips for travelers exploring the continent." | |
| } | |
| # Fonction pour générer une réponse | |
| def generate_response(user_input, system_prompt, max_new_tokens=150, temperature=0.7): | |
| # Gérer le cas où le prompt système est vide | |
| if not system_prompt.strip(): | |
| messages = [ | |
| {"role": "user", "content": user_input} | |
| ] | |
| else: | |
| messages = [ | |
| {"role": "system", "content": system_prompt}, | |
| {"role": "user", "content": user_input} | |
| ] | |
| # Utiliser apply_chat_template | |
| text = tokenizer.apply_chat_template( | |
| messages, | |
| tokenize=False, | |
| add_generation_prompt=True | |
| ) | |
| # Préparer les entrées du modèle | |
| model_inputs = tokenizer([text], return_tensors="pt").to(device) | |
| # Générer la réponse | |
| generated_ids = model.generate( | |
| model_inputs.input_ids, | |
| max_new_tokens=int(max_new_tokens), | |
| temperature=temperature | |
| ) | |
| # Décoder la réponse | |
| generated_ids = [ | |
| output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids) | |
| ] | |
| response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0] | |
| return response | |
| # Fonction pour mettre à jour le message du prompt système en fonction du choix | |
| def update_system_prompt(selected_prompt): | |
| return system_prompts.get(selected_prompt, "") | |
| # Interface Gradio avec Blocks | |
| with gr.Blocks() as iface: | |
| with gr.Row(): # Structure divisée en deux colonnes | |
| with gr.Column(scale=1): # Partie gauche : Entrées | |
| gr.Markdown("# Oolel Chatbot") | |
| gr.Markdown("Génération de réponses basées sur des prompts système personnalisés.") | |
| # Textbox pour le message utilisateur | |
| user_input = gr.Textbox(label="Message utilisateur", placeholder="Entrez votre message ici...") | |
| # Dropdown pour choisir un prompt système | |
| dropdown = gr.Dropdown( | |
| label="Choisir un prompt système", | |
| choices=list(system_prompts.keys()), # Liste des options de prompts | |
| value=None, # Pas de sélection par défaut | |
| type="value", | |
| interactive=True | |
| ) | |
| # Textbox pour afficher et modifier le message du prompt système | |
| system_prompt_textbox = gr.Textbox( | |
| label="Message du prompt système", | |
| value="", # Valeur par défaut vide | |
| placeholder="Sélectionnez un prompt système pour afficher son contenu ici..." | |
| ) | |
| # Événement pour mettre à jour le prompt dans le Textbox | |
| dropdown.change(update_system_prompt, inputs=[dropdown], outputs=[system_prompt_textbox]) | |
| # Slider pour choisir le nombre maximal de tokens | |
| max_tokens_slider = gr.Slider(50, 500, value=150, label="Nombre max de tokens") | |
| # Slider pour ajuster la température | |
| temperature_slider = gr.Slider(0.1, 1.5, value=0.7, step=0.1, label="Température (créativité)") | |
| # Bouton pour générer la réponse | |
| generate_button = gr.Button("Générer une réponse") | |
| with gr.Column(scale=1): # Partie droite : Réponse générée | |
| gr.Markdown("## Réponse générée") | |
| output = gr.Textbox(label="", interactive=False) # Affichage de la réponse générée | |
| # Connecter le bouton à la fonction de génération | |
| generate_button.click( | |
| fn=generate_response, | |
| inputs=[user_input, system_prompt_textbox, max_tokens_slider, temperature_slider], | |
| outputs=output | |
| ) | |
| # Lancer l'interface | |
| iface.launch() | |