Add minimal Gradio app so HF Space runs

app.py

@@ -0,0 +1,34 @@
+import os
+import gradio as gr
+
+INTRO = """
+# Humigence (Space Preview)
+
+This Space provides a **lightweight preview UI**.  
+The full fine‑tuning & evaluation pipeline runs via the **Humigence CLI** locally.
+
+Use this UI to form the CLI command you'll run on your machine.
+"""
+
+def make_command(mode, model, dataset):
+    mode_flag = "--mode basic" if mode == "Basic" else "--mode advanced"
+    model_flag = f'--model "{model.strip()}"' if model.strip() else ""
+    dataset_flag = f'--dataset "{dataset.strip()}"' if dataset.strip() else ""
+    cmd = f"humigence {mode_flag} {model_flag} {dataset_flag}".strip()
+    return f"### Preview Command\n```\n{cmd}\n```\n\n> Copy/paste and run this locally to execute the real pipeline."
+
+with gr.Blocks(title="Humigence") as demo:
+    gr.Markdown(INTRO)
+
+    with gr.Row():
+        mode = gr.Radio(["Basic", "Advanced"], value="Basic", label="Mode")
+        model = gr.Textbox(label="Base Model", value="TinyLlama/TinyLlama-1.1B", placeholder="e.g., TinyLlama/TinyLlama-1.1B or microsoft/phi-2")
+    dataset = gr.Textbox(label="Dataset Source (path or URL)", placeholder="e.g., data/processed/my_dataset.jsonl")
+
+    run = gr.Button("Generate CLI Command")
+    out = gr.Markdown()
+
+    run.click(make_command, inputs=[mode, model, dataset], outputs=out)
+
+# HF Spaces expose PORT; default to 7860 locally
+demo.launch(server_name="0.0.0.0", server_port=int(os.getenv("PORT", "7860")))

requirements.txt

@@ -1,17 +1 @@
-torch>=2.0.0
-transformers>=4.40,<4.47
-accelerate>=0.28.0
-peft>=0.12.0
-bitsandbytes==0.45.5
-datasets>=2.18.0
-evaluate>=0.4.0
-huggingface_hub>=0.24.0
-numpy>=1.24.0
-pydantic>=2.0.0
-typer>=0.12.3
-InquirerPy>=0.3.4
-rich>=13.7.1
-scikit-learn>=1.3.0
-tqdm>=4.65.0
-tokenizers>=0.15.0
-safetensors>=0.4.0
+gradio==4.43.0