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| # # Mount Google Drive | |
| # from google.colab import drive | |
| # drive.mount('/content/drive') | |
| import gradio as gr | |
| from transformers import AutoModel, TFAutoModel | |
| # Modèle Hugging Face à partir de l'identifiant du modèle | |
| model_name = "gpt2" | |
| huggingface_model = AutoModel.from_pretrained(model_name) | |
| # Spécifiez l'identifiant de référentiel correct sans informations supplémentaires | |
| repo_name = "motofanacc/monModel" | |
| # Chemin vers les poids de votre modèle dans votre référentiel | |
| model_checkpoint = "main" | |
| # Charger le modèle à partir de Hugging Face Hub | |
| model = TFAutoModel.from_pretrained(repo_name, from_pt=True, model_checkpoint=model_checkpoint) | |
| #a | |
| # # Charger les poids TensorFlow | |
| # tensorflow_weights_path = "motofanacc/GradioChatBot/tree/main/Checkpoints" | |
| # tensorflow_model = TFAutoModel.from_pretrained(tensorflow_weights_path) | |
| def generate_text(model, input_text, max_length=50): | |
| return model.generate(input_text, max_length=max_length) | |
| # preprocessor = keras_nlp.models.GPT2CausalLMPreprocessor.from_preset( | |
| # "gpt2_base_en", | |
| # sequence_length=128, | |
| # ) | |
| # gpt2_lm = keras_nlp.models.GPT2CausalLM.from_preset( | |
| # "gpt2_base_en", | |
| # preprocessor=preprocessor, | |
| # ) | |
| # gpt2_lm.load_weights('/content/drive/MyDrive/Checkpoints/weights') | |
| # Gradio app | |
| # <a href="https://www.freepik.com/icon/user_456212#fromView=search&term=avatar&track=ais&page=1&position=22&uuid=48125587-eeb5-4fe3-9eb2-f9fe7330f4fe">Icon by Freepik</a> | |
| # <a href="https://www.freepik.com/icon/ai_2814666#fromView=search&term=robot&track=ais&page=1&position=20&uuid=58780fb9-dab6-4fb1-9928-479b2926a242">Icon by Freepik</a> | |
| theme = gr.themes.Soft().set( | |
| background_fill_primary='white', | |
| background_fill_primary_dark='white', | |
| ) | |
| with gr.Blocks(theme=theme,css=""" | |
| .gradio-container { | |
| background-color: white; | |
| width: 70vw; | |
| } | |
| #chatbot{ | |
| background-image: url("https://png.pngtree.com/thumb_back/fh260/background/20201014/pngtree-breast-cancer-awareness-pink-ribbons-background-design-image_417234.jpg"); | |
| } | |
| #chatbot .bubble-wrap::-webkit-scrollbar { | |
| width: 20px; | |
| } | |
| #chatbot .bubble-wrap::-webkit-scrollbar-thumb { | |
| background-color: whitesmoke; | |
| border-radius: 20px; | |
| border: 6px solid transparent; | |
| background-clip: content-box; | |
| } | |
| #chatbot .bubble-wrap::-webkit-scrollbar-thumb:hover { | |
| background-color: grey; | |
| } | |
| #chatbot .bubble-wrap::-webkit-scrollbar-track { | |
| background-color: transparent; | |
| } | |
| #chatbot .message p{ | |
| text-align: start; | |
| color: white; | |
| } | |
| h1, p { | |
| text-align: center; | |
| color: black; | |
| } | |
| body #footer_note { | |
| text-align: center; | |
| font-size: x-small; | |
| font-weight:bold; | |
| } | |
| .label { | |
| display:none; | |
| } | |
| textarea, .gallery-item, .gallery-item:hover { | |
| color: black; | |
| border: 1px black solid; | |
| background-color: white; | |
| } | |
| .user { | |
| background-color: #374151; | |
| } | |
| .user { | |
| background-color: #111827; | |
| } | |
| .gallery-item:hover { | |
| color: white; | |
| border: 1px black solid; | |
| background-color: black; | |
| } | |
| body gradio-app { | |
| background-color: white; | |
| } | |
| """) as demo: | |
| gr.HTML(f""" | |
| <html> | |
| <body> | |
| <h1>Welcome, I'm CancerBot 🤖</h1> | |
| <p>Here you can ask all questions about cancer</p> | |
| </body> | |
| </html> | |
| """) | |
| def return_message(message, history, model=huggingface_model, max_length=128): | |
| if len(message) <= 1: | |
| gr.Warning('Please enter a message with more than one character.') | |
| elif len(message) > max_length: | |
| gr.Warning(f"Input should not exceed {max_length} characters.") | |
| else: | |
| cancer_answer = generate_text(model, message) | |
| message = "**You**\n" + message | |
| history.append([message, f"**CancerBot**\n{cancer_answer}"]) | |
| return "", history | |
| chatbot = gr.Chatbot( | |
| height="60vh", | |
| bubble_full_width=True, | |
| avatar_images=(["/content/drive/MyDrive/Data/avatar.png", "/content/drive/MyDrive/Data/robot.png"]), | |
| show_copy_button=True, | |
| likeable=True, | |
| layout='bubble', | |
| elem_id='chatbot', | |
| show_label=False, | |
| ) | |
| with gr.Row(): | |
| input_box = gr.Textbox(placeholder="Message CancerBot...", container=False, scale=9) | |
| submit_btn = gr.Button(value="⬆", scale=1) | |
| submit_btn.click(return_message, [input_box, chatbot],[input_box, chatbot]) | |
| examples = gr.Examples(examples=["What is a thyroid cancer ?", "How can I know that I have a lung cancer ?", | |
| "How many types of cancer ?"], inputs=[input_box], label="") | |
| input_box.submit(return_message, [input_box, chatbot],[input_box, chatbot]) | |
| gr.HTML(f""" | |
| <html> | |
| <body> | |
| <p id="footer_note">CancerBot is based on cancer documents. Consider checking important information.</p> | |
| </body> | |
| </html> | |
| """) | |
| demo.queue(default_concurrency_limit=34) # 32 students, 2 teachers | |
| demo.launch(share=True) |