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| import gradio as gr | |
| from executor import KernelRequest, LocalCLIExecutor | |
| SKILL_MD_DEFAULT = "skill_example/SKILL.md" | |
| executor = LocalCLIExecutor() | |
| theme = gr.themes.Default() | |
| css = """ | |
| .orange-btn { | |
| background: #ea580c !important; | |
| color: white !important; | |
| border: none !important; | |
| } | |
| .orange-btn:hover { | |
| background: #c2410c !important; | |
| } | |
| .sidebar { | |
| border-right: 1px solid #e5e7eb !important; | |
| min-width: 200px !important; | |
| align-self: flex-start !important; | |
| position: sticky !important; | |
| top: 0 !important; | |
| } | |
| """ | |
| # Holds the files dict from the latest run so callbacks can read them | |
| _latest_files: dict[str, str] = {} | |
| def generate_kernel(skills_path, prompt): | |
| global _latest_files | |
| _latest_files = {} | |
| request = KernelRequest(skill_path=skills_path, prompt=prompt) | |
| for response in executor.stream(request): | |
| if response.files: | |
| _latest_files = response.files | |
| choices = list(_latest_files.keys()) if _latest_files else [] | |
| error_prefix = f"Error: {response.error}\n\n" if response.error else "" | |
| first_content = _latest_files.get(choices[0], "") if choices else "" | |
| yield ( | |
| error_prefix + response.streaming_output, | |
| response.final_output, | |
| first_content, | |
| response.log, | |
| "Benchmark skipped", | |
| gr.update(choices=choices, value=choices[0] if choices else None), | |
| ) | |
| def on_file_select(filename): | |
| if filename and filename in _latest_files: | |
| return _latest_files[filename], gr.Tabs(selected="files") | |
| return "", gr.Tabs(selected="files") | |
| with gr.Blocks(css=css) as demo: | |
| gr.Markdown( | |
| "# ⚡ Kernel Skills Sandbox\n" | |
| "Generate GPU kernels from natural language prompts. " | |
| "Point to your SKILL.md, describe what you need, and hit **Run**." | |
| ) | |
| with gr.Group(): | |
| skills_path = gr.Textbox( | |
| label="Path to SKILL.md", | |
| value=SKILL_MD_DEFAULT, | |
| placeholder="e.g. SKILL.md or /path/to/SKILL.md", | |
| ) | |
| prompt = gr.Textbox( | |
| label="Prompt for Kernel Generation", | |
| lines=3, | |
| placeholder="Describe the kernel you want to generate...", | |
| ) | |
| run_btn = gr.Button("Run", elem_classes=["orange-btn"]) | |
| gr.Markdown("---") | |
| with gr.Row(equal_height=False): | |
| # LHS sidebar: file list | |
| with gr.Column(scale=1, min_width=200, elem_classes=["sidebar"]): | |
| gr.Markdown("**Generated Files**") | |
| file_dropdown = gr.Radio( | |
| label="Files", | |
| choices=[], | |
| interactive=True, | |
| ) | |
| # RHS: tabbed content | |
| with gr.Column(scale=4): | |
| with gr.Tabs() as tabs: | |
| with gr.Tab("Output", id="output"): | |
| streaming_output = gr.Textbox( | |
| lines=20, | |
| show_label=False, | |
| interactive=False, | |
| ) | |
| with gr.Tab("Response", id="response"): | |
| final_response = gr.Textbox( | |
| lines=20, | |
| show_label=False, | |
| interactive=False, | |
| ) | |
| with gr.Tab("File Viewer", id="files"): | |
| file_content = gr.Code( | |
| label="File Content", | |
| language=None, | |
| lines=20, | |
| ) | |
| with gr.Tab("Live Log", id="log"): | |
| live_log = gr.Textbox( | |
| lines=20, | |
| show_label=False, | |
| interactive=False, | |
| ) | |
| with gr.Tab("Benchmark", id="benchmark"): | |
| benchmark_results = gr.Textbox( | |
| lines=20, | |
| show_label=False, | |
| interactive=False, | |
| ) | |
| run_btn.click( | |
| fn=generate_kernel, | |
| inputs=[skills_path, prompt], | |
| outputs=[streaming_output, final_response, file_content, live_log, benchmark_results, file_dropdown], | |
| ) | |
| file_dropdown.change( | |
| fn=on_file_select, | |
| inputs=[file_dropdown], | |
| outputs=[file_content, tabs], | |
| ) | |
| demo.launch(theme=theme) | |