| import os | |
| import gradio as gr | |
| def build_command(mode, model, dataset): | |
| mode = (mode or "basic").strip().lower() | |
| model = (model or "TinyLlama/TinyLlama-1.1B").strip() | |
| dataset = (dataset or "").strip() | |
| cmd = f'humigence train --mode {mode} --model "{model}"' | |
| if dataset: | |
| cmd += f' --dataset "{dataset}"' | |
| return f"### Copy & run locally\n```\n{cmd}\n```" | |
| with gr.Blocks(title="Humigence") as demo: | |
| gr.Markdown("# 🚀 Humigence Fine‑tuning Toolkit (Space Preview)") | |
| with gr.Row(): | |
| mode = gr.Radio(["basic", "advanced"], value="basic", label="Setup Mode") | |
| model = gr.Textbox(label="Base Model", value="TinyLlama/TinyLlama-1.1B") | |
| dataset = gr.Textbox(label="Dataset (path/URL)", placeholder="e.g., data/alpaca.jsonl") | |
| out = gr.Markdown() | |
| gr.Button("Generate CLI Command").click(build_command, [mode, model, dataset], out) | |
| demo.launch(server_name="0.0.0.0", server_port=int(os.getenv("PORT", "7860"))) | |