rename package

src/llamafactory/webui/components/top.py

@@ -0,0 +1,66 @@
+from typing import TYPE_CHECKING, Dict
+
+from ...data import templates
+from ...extras.constants import METHODS, SUPPORTED_MODELS
+from ...extras.packages import is_gradio_available
+from ..common import get_model_path, get_template, get_visual, list_adapters, save_config
+from ..utils import can_quantize
+
+
+if is_gradio_available():
+    import gradio as gr
+
+
+if TYPE_CHECKING:
+    from gradio.components import Component
+
+
+def create_top() -> Dict[str, "Component"]:
+    available_models = list(SUPPORTED_MODELS.keys()) + ["Custom"]
+
+    with gr.Row():
+        lang = gr.Dropdown(choices=["en", "ru", "zh"], scale=1)
+        model_name = gr.Dropdown(choices=available_models, scale=3)
+        model_path = gr.Textbox(scale=3)
+
+    with gr.Row():
+        finetuning_type = gr.Dropdown(choices=METHODS, value="lora", scale=1)
+        adapter_path = gr.Dropdown(multiselect=True, allow_custom_value=True, scale=5)
+        refresh_btn = gr.Button(scale=1)
+
+    with gr.Accordion(open=False) as advanced_tab:
+        with gr.Row():
+            quantization_bit = gr.Dropdown(choices=["none", "8", "4"], value="none", scale=2)
+            template = gr.Dropdown(choices=list(templates.keys()), value="default", scale=2)
+            rope_scaling = gr.Radio(choices=["none", "linear", "dynamic"], value="none", scale=3)
+            booster = gr.Radio(choices=["none", "flashattn2", "unsloth"], value="none", scale=3)
+            visual_inputs = gr.Checkbox(scale=1)
+
+    model_name.change(list_adapters, [model_name, finetuning_type], [adapter_path], queue=False).then(
+        get_model_path, [model_name], [model_path], queue=False
+    ).then(get_template, [model_name], [template], queue=False).then(
+        get_visual, [model_name], [visual_inputs], queue=False
+    )  # do not save config since the below line will save
+
+    model_path.change(save_config, inputs=[lang, model_name, model_path], queue=False)
+
+    finetuning_type.change(list_adapters, [model_name, finetuning_type], [adapter_path], queue=False).then(
+        can_quantize, [finetuning_type], [quantization_bit], queue=False
+    )
+
+    refresh_btn.click(list_adapters, [model_name, finetuning_type], [adapter_path], queue=False)
+
+    return dict(
+        lang=lang,
+        model_name=model_name,
+        model_path=model_path,
+        finetuning_type=finetuning_type,
+        adapter_path=adapter_path,
+        refresh_btn=refresh_btn,
+        advanced_tab=advanced_tab,
+        quantization_bit=quantization_bit,
+        template=template,
+        rope_scaling=rope_scaling,
+        booster=booster,
+        visual_inputs=visual_inputs,
+    )