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| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| import torch | |
| import gradio as gr | |
| import os | |
| import time | |
| model_id = "alibidaran/Gemma2_Virtual_doctor" | |
| tokenizer = AutoTokenizer.from_pretrained(model_id) | |
| model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto") | |
| def print_like_dislike(x: gr.LikeData): | |
| print(x.index, x.value, x.liked) | |
| def add_text(history, text): | |
| history = history + [(text,None)] | |
| return history, gr.Textbox(value="", interactive=False) | |
| def add_file(history, file): | |
| global image_file | |
| image_file=file.name | |
| history = history + [((file.name,),None)] | |
| return history | |
| def bot(history): | |
| prompt=history[-1][0] | |
| text=f"<s> ###Human: {prompt} ###Asistant: " | |
| inputs=tokenizer(text,return_tensors='pt').to('cpu') | |
| with torch.no_grad(): | |
| outputs=model.generate(**inputs,max_new_tokens=120,do_sample=True,top_p=0.92,top_k=10,temperature=0.7) | |
| output_text=outputs[:, inputs.input_ids.shape[1]:] | |
| response=tokenizer.decode(output_text[0], skip_special_tokens=True) | |
| print(response) | |
| history[-1][1] = "" | |
| for character in response[1:-1]: | |
| history[-1][1] += character | |
| time.sleep(0.01) | |
| yield history | |
| with gr.Blocks() as demo: | |
| chatbot = gr.Chatbot( | |
| [], | |
| elem_id="chatbot", | |
| bubble_full_width=False, | |
| #avatar_images=(None, (os.path.join(os.path.dirname(__file__), "avatar.png"))), | |
| ) | |
| with gr.Row(): | |
| txt = gr.Textbox( | |
| scale=4, | |
| show_label=False, | |
| placeholder="Ask the virtual doctor about your symptoms!", | |
| container=False, | |
| ) | |
| btn = gr.UploadButton("📁", file_types=["image", "video", "audio"]) | |
| txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then( | |
| bot, chatbot, chatbot, api_name="bot_response" | |
| ) | |
| txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False) | |
| file_msg = btn.upload(add_file, [chatbot, btn], [chatbot], queue=False).then( | |
| bot, chatbot, chatbot | |
| ) | |
| chatbot.like(print_like_dislike, None, None) | |
| if __name__=="__main__": | |
| demo.launch(share=True,debug=True) |