feat(gradio): generate extraction templates from images

Add an independent ZeroGPU template-generation pipeline using NuExtract3's grounded document mode. Wire a new input-column button to populate the existing editable template while preserving presets and structured extraction.

README.md

@@ -17,7 +17,7 @@ short_description: Extract structured JSON from documents with NuExtract3.
 
 NuMark is a Gradio app for extracting structured JSON from document images with [NuExtract3](https://huggingface.co/numind/NuExtract3).
 
-Upload a receipt, invoice, or other document image, optionally add accompanying text, and choose a JSON template for schema-guided structured extraction.
+Upload a receipt, invoice, or other document image, optionally add accompanying text, and choose a JSON template for schema-guided structured extraction. You can also generate a grounded template from the uploaded image before running extraction.
 
 The inference function uses Hugging Face ZeroGPU dynamic GPU allocation. Select ZeroGPU in the Space hardware settings before launching the app.
 

app/gradio.py

@@ -236,7 +236,6 @@ model = (
 )
 
 
-@spaces.GPU
 def run_nuextract(messages, **chat_template_kwargs):
     inputs = processor.apply_chat_template(
         messages,
@@ -262,6 +261,7 @@ def run_nuextract(messages, **chat_template_kwargs):
     )[0].strip()
 
 
+@spaces.GPU
 def extract(image, text, template, enable_thinking):
     result = run_nuextract(
         [
@@ -281,6 +281,32 @@ def extract(image, text, template, enable_thinking):
     return json.loads(result)
 
 
+@spaces.GPU
+def generate_template(image):
+    result = run_nuextract(
+        [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "image", "image": image},
+                    {
+                        "type": "text",
+                        "text": (
+                            "Create a reusable structured extraction template grounded only "
+                            "in the visible document. Include fields supported by the document, "
+                            "represent repeated records as arrays, use NuExtract template leaf "
+                            "types, and return only the JSON template."
+                        ),
+                    },
+                ],
+            }
+        ],
+        mode="template-generation",
+    )
+
+    return json.dumps(json.loads(result), indent=2)
+
+
 with gr.Blocks(title="NuMarkApp") as demo:
     gr.Markdown(
         "# NuMarkApp\n"
@@ -302,6 +328,7 @@ with gr.Blocks(title="NuMarkApp") as demo:
                 label="JSON template preset",
                 info="Choose a starting structure, then edit it below.",
             )
+            generate_template_button = gr.Button("Generate template from Image")
             with gr.Accordion("Structured JSON template", open=False):
                 template = gr.Textbox(
                     label="Structured JSON template",
@@ -389,6 +416,13 @@ with gr.Blocks(title="NuMarkApp") as demo:
         outputs=template,
     )
 
+    generate_template_button.click(
+        generate_template,
+        inputs=image,
+        outputs=template,
+        api_name="generate_template",
+    )
+
     run.click(
         extract,
         inputs=[image, text, template, enable_thinking],