Spaces:
Sleeping
Sleeping
| """ | |
| title: Manus | |
| emoji: 🚀 | |
| colorFrom: red | |
| colorTo: blue | |
| sdk: gradio | |
| sdk_version: 5.20.1 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| """ | |
| import gradio as gr | |
| import secrets | |
| # In-memory store for valid API keys. | |
| valid_api_keys = set() | |
| def generate_api_key(): | |
| """ | |
| Generate a secure 32-character hexadecimal API key, | |
| store it in the valid_api_keys set, and return it. | |
| """ | |
| key = secrets.token_hex(16) | |
| valid_api_keys.add(key) | |
| return key | |
| def llama_vision_inference(api_key, image): | |
| """ | |
| Dummy inference function for Llama Vision model. | |
| Replace the simulated processing below with actual model loading and inference. | |
| Ensure that your model is explicitly loaded on CPU. | |
| """ | |
| if not api_key.strip(): | |
| return "Error: API key is required." | |
| if api_key not in valid_api_keys: | |
| return "Error: Invalid API key. Please generate a valid key first." | |
| # Example: Force CPU usage when loading the model. | |
| # from llama_vision import LlamaVisionModel | |
| # model = LlamaVisionModel.from_pretrained("llama-vision-latest", device="cpu") | |
| # result = model.infer(image) | |
| # Simulated output for demonstration: | |
| result = ( | |
| "Simulated Model Output:\n" | |
| "- Detected GUI elements: [button, menu, text field]\n" | |
| "- Recognized text: 'Sample Linux GUI Screenshot'\n" | |
| "- Layout Analysis: Structured layout with header and sidebar" | |
| ) | |
| return result | |
| with gr.Blocks(title="Manus 🚀") as demo: | |
| gr.Markdown("# Manus 🚀") | |
| gr.Markdown( | |
| "This Gradio Space lets you generate an API key and perform vision inference using the Llama Vision model (running in CPU mode)." | |
| ) | |
| with gr.Tabs(): | |
| with gr.TabItem("API Key Generator"): | |
| gr.Markdown("Generate an API key to be used with the vision model API.") | |
| key_output = gr.Textbox(label="Your Generated API Key", interactive=False) | |
| generate_button = gr.Button("Generate API Key") | |
| generate_button.click(fn=generate_api_key, outputs=key_output) | |
| with gr.TabItem("Vision Model Inference"): | |
| gr.Markdown( | |
| "Enter your API key and upload an image (e.g., a Linux GUI screenshot) to run inference using the Llama Vision model." | |
| ) | |
| api_key_input = gr.Textbox(label="API Key", placeholder="Enter your API key here") | |
| image_input = gr.Image(type="pil", label="Upload Image") | |
| output_text = gr.Textbox(label="Model Output", interactive=False) | |
| run_button = gr.Button("Run Vision Model") | |
| run_button.click(fn=llama_vision_inference, inputs=[api_key_input, image_input], outputs=output_text) | |
| if __name__ == "__main__": | |
| demo.launch() |