add download

app.py

@@ -1,7 +1,9 @@
 import os
+import tempfile
 
 import gradio as gr
 import numpy as np
+import requests
 from dotenv import load_dotenv
 from huggingface_hub import InferenceClient, login
 
@@ -12,6 +14,26 @@ MAX_IMAGE_SIZE = 2048
 TOKEN = None
 
 
+def download_image_locally(image_url: str, local_path: str = "downloaded_image.png") -> str:
+    """Download an image from a URL to a local path.
+
+    Args:
+        image_url (str): The URL of the image to download. Must be an http(s) URL.
+        local_path (str, optional): The path (including filename) where the file should be saved. Defaults to "downloaded_image.png".
+
+    Returns:
+        str: The filesystem path of the saved file – suitable for returning to a **gr.File** output, or as an MCP tool response.
+    """
+    response = requests.get(image_url, timeout=30)
+    response.raise_for_status()
+    # If the caller passed only a filename, save into a temporary directory to avoid permission issues
+    if os.path.dirname(local_path) == "":
+        tmp_dir = tempfile.gettempdir()
+        local_path = os.path.join(tmp_dir, local_path)
+    with open(local_path, "wb") as f:
+        f.write(response.content)
+    return local_path
+
 def get_token(oauth_token: gr.OAuthToken | None):
     global TOKEN
     if oauth_token and oauth_token.token:
@@ -64,82 +86,96 @@ css="""
 
 with gr.Blocks(css=css) as demo:
     demo.load(get_token, inputs=None, outputs=None)
+
     with gr.Sidebar():
         gr.Markdown("# Inference Provider")
-        gr.Markdown("This Space showcases the black-forest-labs/FLUX.1-dev model, served by the nebius API. Sign in with your Hugging Face account to use this API.")
+        gr.Markdown(
+            "This Space showcases the black-forest-labs/FLUX.1-dev model, served by the nebius API. Sign in with your Hugging Face account to use this API."
+        )
         button = gr.LoginButton("Sign in")
         button.click(fn=get_token, inputs=[], outputs=[])
-        
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown(f"""# FLUX.1 [schnell] with fal-ai through HF Inference Providers ⚡
-learn more about HF Inference Providers [here](https://huggingface.co/docs/inference-providers/index)""")
-        
-        with gr.Row():
-            
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
-            
-            run_button = gr.Button("Run", scale=0)
-        
-        result = gr.Image(label="Result", show_label=False, format="png")
-        
-        with gr.Accordion("Advanced Settings", open=False):
-            
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=42,
-            )
-                        
-            with gr.Row():
-                
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,
+
+    with gr.Tabs():
+        with gr.TabItem("Generate Image"):
+            with gr.Column(elem_id="col-container"):
+                gr.Markdown(
+                    """# FLUX.1 [schnell] with fal‑ai through HF Inference Providers ⚡\nLearn more about HF Inference Providers [here](https://huggingface.co/docs/inference-providers/index)"""
                 )
-                
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,
+
+                with gr.Row():
+                    prompt = gr.Text(
+                        label="Prompt",
+                        show_label=False,
+                        max_lines=1,
+                        placeholder="Enter your prompt",
+                        container=False,
+                    )
+                    run_button = gr.Button("Run", scale=0)
+
+                result = gr.Image(label="Result", show_label=False, format="png")
+
+                with gr.Accordion("Advanced Settings", open=False):
+                    seed = gr.Slider(
+                        label="Seed",
+                        minimum=0,
+                        maximum=MAX_SEED,
+                        step=1,
+                        value=42,
+                    )
+                    with gr.Row():
+                        width = gr.Slider(
+                            label="Width",
+                            minimum=256,
+                            maximum=MAX_IMAGE_SIZE,
+                            step=32,
+                            value=1024,
+                        )
+                        height = gr.Slider(
+                            label="Height",
+                            minimum=256,
+                            maximum=MAX_IMAGE_SIZE,
+                            step=32,
+                            value=1024,
+                        )
+                    num_inference_steps = gr.Slider(
+                        label="Number of inference steps",
+                        minimum=1,
+                        maximum=50,
+                        step=1,
+                        value=25,
+                    )
+
+                gr.Examples(
+                    examples=examples,
+                    fn=generate,
+                    inputs=[prompt],
+                    outputs=[result, seed],
+                    cache_examples="lazy",
                 )
-            
-            with gr.Row():
-                
-  
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=25,
+
+                gr.on(
+                    triggers=[run_button.click, prompt.submit],
+                    fn=generate,
+                    inputs=[prompt, seed, width, height, num_inference_steps],
+                    outputs=[result, seed],
+                    show_api=True,
                 )
-        
-        gr.Examples(
-            examples = examples,
-            fn = generate,
-            inputs = [prompt],
-            outputs = [result, seed],
-            cache_examples="lazy"
-        )
 
-    gr.on(
-        triggers=[run_button.click, prompt.submit],
-        fn = generate,
-        inputs = [prompt, seed, width, height, num_inference_steps],
-        outputs = [result, seed]
-    )
+        with gr.TabItem("Download Image"):
+            gr.Markdown("## Download an image from a URL and make it available as a file")
+            url_input = gr.Text(label="Image URL", placeholder="https://example.com/cool-image.png")
+            filename_input = gr.Text(
+                label="Save as (filename)", value="downloaded_image.png", placeholder="downloaded_image.png"
+            )
+            download_btn = gr.Button("Download")
+            file_output = gr.File(label="Downloaded file")
+
+            download_btn.click(
+                fn=download_image_locally,
+                inputs=[url_input, filename_input],
+                outputs=[file_output],
+                show_api=True,
+            )
 
-demo.launch(mcp_server=True)
+if __name__ == "__main__":
+    demo.launch(mcp_server=True)