Upload app.py

app.py

@@ -1874,9 +1874,44 @@ with gr.Blocks(theme=args.theme, elem_id="main", fill_width=True, fill_height=Fa
         copy_prompt_btn.click(gradio_copy_prompt, inputs=[output_text], outputs=[prompt_gui])
         copy_prompt_btn_pony.click(gradio_copy_prompt, inputs=[output_text_pony], outputs=[prompt_gui])
 
+    # Stable programmatic endpoint
+    from typing import Any, Dict, List, Union, Generator
+    Payload = Union[List[Any], Dict[str, Any]]
+
+    def generate_minimal(payload: Payload) -> Generator[Any, None, None]:
+        # One-call wrapper: optionally preload a model, then delegate to the original generator.
+        # Accepts EITHER:
+        #  - dict: {"args":[...full positional array...], "model_name":..., "vae_model":..., "task":..., "controlnet_model":...}
+        #  - list: [...full positional array...] (legacy, forwarded as-is)
+        # Normalize input
+        if isinstance(payload, dict):
+            args = payload.get("args") or payload.get("data") or []
+            m = payload.get("model_name")
+            v = payload.get("vae_model")
+            t = payload.get("task")
+            c = payload.get("controlnet_model")
+            # Optional preload if all four fields are present
+            if all(x is not None for x in (m, v, t, c)):
+                for _ in sd_gen.load_new_model(m, v, t, c):
+                    # If you want to stream loader status, you could `yield {"status": _}`
+                    pass
+        else:
+            # Legacy: payload is the full positional array already
+            args = payload
+        # Delegate to the existing streaming generator; preserves SSE behavior
+        yield from sd_gen_generate_pipeline(*args)
+
+    gr.api(
+        generate_minimal,
+        api_name="generate",
+        api_description="Accepts a list (positional) or a dict with {'args': [...]} + optional loader fields.",
+        queue=True,
+    )
+
     gr.LoginButton()
     gr.DuplicateButton(value="Duplicate Space for private use (This demo does not work on CPU. Requires GPU Space)")
 
+
 if __name__ == "__main__":
     app.queue()
     app.launch(