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| import gradio as gr | |
| from utils.upload_file import UploadFile | |
| from utils.chatbot import ChatBot | |
| from utils.ui_settings import UISettings | |
| from utils.load_config import LoadConfig | |
| APPCFG = LoadConfig() | |
| # # Prepare the LLm and Tokenizer | |
| # tokenizer = AutoTokenizer.from_pretrained( | |
| # APPCFG.llm_engine, token=APPCFG.gemma_token, device=APPCFG.device) | |
| # model = model = AutoModelForCausalLM.from_pretrained(pretrained_model_name_or_path="google/gemma-7b-it", | |
| # token=APPCFG.gemma_token, | |
| # torch_dtype=torch.float16, | |
| # device_map=APPCFG.device | |
| # ) | |
| # app_pipeline = pipeline( | |
| # "text-generation", | |
| # model=model, | |
| # tokenizer=tokenizer | |
| # ) | |
| with gr.Blocks() as demo: | |
| with gr.Tabs(): | |
| with gr.TabItem("Med-App"): | |
| ############## | |
| # First ROW: | |
| ############## | |
| with gr.Row() as row_one: | |
| with gr.Column(visible=False) as reference_bar: | |
| ref_output = gr.Markdown() | |
| with gr.Column() as chatbot_output: | |
| chatbot = gr.Chatbot( | |
| [], | |
| elem_id="chatbot", | |
| bubble_full_width=False, | |
| height=500, | |
| avatar_images=( | |
| ("images/test.png"), "images/Gemma-logo.png"), | |
| # render=False | |
| ) | |
| # **Adding like/dislike icons | |
| chatbot.like(UISettings.feedback, None, None) | |
| ############## | |
| # SECOND ROW: | |
| ############## | |
| with gr.Row(): | |
| input_txt = gr.Textbox( | |
| lines=4, | |
| scale=8, | |
| placeholder="Enter text and press enter, or upload PDF files", | |
| container=False, | |
| ) | |
| ############## | |
| # Third ROW: | |
| ############## | |
| with gr.Row() as row_two: | |
| text_submit_btn = gr.Button(value="Submit text") | |
| sidebar_state = gr.State(False) | |
| btn_toggle_sidebar = gr.Button( | |
| value="References") | |
| btn_toggle_sidebar.click(UISettings.toggle_sidebar, [sidebar_state], [ | |
| reference_bar, sidebar_state]) | |
| upload_btn = gr.UploadButton( | |
| "📁 Upload PDF or doc files", file_types=[ | |
| '.pdf', | |
| '.doc' | |
| ], | |
| file_count="multiple") | |
| clear_button = gr.ClearButton([input_txt, chatbot]) | |
| rag_with_dropdown = gr.Dropdown( | |
| label="RAG with", choices=["Preprocessed doc", "Upload doc: Process for RAG"], value="Preprocessed doc") | |
| ############## | |
| # Fourth ROW: | |
| ############## | |
| with gr.Row() as row_four: | |
| temperature_bar = gr.Slider(minimum=0.1, maximum=1, value=0.1, step=0.1, | |
| label="Temperature", info="Increasing the temperature will make the model answer more creatively.") | |
| top_k = gr.Slider(minimum=0.0, | |
| maximum=100.0, | |
| step=1, | |
| label="top_k", | |
| value=50, | |
| info="A lower value (e.g. 10) will result in more conservative answers.") | |
| top_p = gr.Slider(minimum=0.0, | |
| maximum=1.0, | |
| step=0.01, | |
| label="top_p", | |
| value=0.95, | |
| info=" Works together with top-k. lower value (e.g., 0.5) will generate more focused and conservative text. (Default: 0.0)") | |
| ############## | |
| # Process: | |
| ############## | |
| file_msg = upload_btn.upload(fn=UploadFile.process_uploaded_files, inputs=[ | |
| upload_btn, chatbot, rag_with_dropdown], outputs=[input_txt, chatbot], queue=False) | |
| txt_msg = input_txt.submit(fn=ChatBot.respond, | |
| inputs=[chatbot, input_txt, | |
| rag_with_dropdown, temperature_bar, top_k, top_p], | |
| outputs=[input_txt, | |
| chatbot, ref_output], | |
| queue=False).then(lambda: gr.Textbox(interactive=True), | |
| None, [input_txt], queue=False) | |
| txt_msg = text_submit_btn.click(fn=ChatBot.respond, | |
| inputs=[chatbot, input_txt, | |
| rag_with_dropdown, temperature_bar, top_k, top_p], | |
| outputs=[input_txt, | |
| chatbot, ref_output], | |
| queue=False).then(lambda: gr.Textbox(interactive=True), | |
| None, [input_txt], queue=False) | |
| if __name__ == "__main__": | |
| demo.launch() | |