(engine: "Engine")
| 5 | import gradio as gr |
| 6 | |
| 7 | def create_basic(engine: "Engine") -> Dict[str, "Component"]: |
| 8 | with gr.Row(): |
| 9 | lang = gr.Dropdown( |
| 10 | choices = ["zh", "en"], |
| 11 | ) |
| 12 | |
| 13 | method_name = gr.Dropdown( |
| 14 | choices = METHODS, |
| 15 | value = METHODS[0], |
| 16 | interactive = True |
| 17 | ) |
| 18 | |
| 19 | config_file = gr.Dropdown( |
| 20 | choices = engine.runner.get_config_files(), |
| 21 | value = None, |
| 22 | interactive = True |
| 23 | ) |
| 24 | |
| 25 | with gr.Accordion(open = True) as base_tab: |
| 26 | with gr.Row(): |
| 27 | gpu_id = gr.Textbox(interactive = True, placeholder = "0,1,2,3,4,5,6,7,8") |
| 28 | framework = gr.Dropdown( |
| 29 | choices = ["hf", "vllm", 'fschat', 'openai'], |
| 30 | value = 'hf', |
| 31 | interactive = True |
| 32 | ) |
| 33 | |
| 34 | generator_name = gr.Textbox(interactive = True, placeholder = 'llama3.1-8b-instruct') |
| 35 | generator_model_path = gr.Textbox(interactive = True, placeholder = 'meta-llama/Llama-3.1-8B-Instruct') |
| 36 | |
| 37 | with gr.Row(): |
| 38 | retrieval_method = gr.Textbox(interactive = True, placeholder = 'e5') |
| 39 | retrieval_model_path = gr.Textbox(interactive = True, placeholder = 'intfloat/e5-base-v2') |
| 40 | |
| 41 | with gr.Row(): |
| 42 | corpus_path = gr.Textbox(interactive = True) |
| 43 | index_path = gr.Textbox(interactive = True) |
| 44 | |
| 45 | return dict( |
| 46 | lang = lang, |
| 47 | method_name = method_name, |
| 48 | gpu_id = gpu_id, |
| 49 | base_tab = base_tab, |
| 50 | framework = framework, |
| 51 | generator_name = generator_name, |
| 52 | generator_model_path = generator_model_path, |
| 53 | retrieval_method = retrieval_method, |
| 54 | retrieval_model_path = retrieval_model_path, |
| 55 | corpus_path = corpus_path, |
| 56 | index_path = index_path, |
| 57 | config_file = config_file |
| 58 | ) |
| 59 | |
| 60 |
no test coverage detected