Typhoon as default translator + Pose (ControlNet) for SDXL

app.py

@@ -202,7 +202,7 @@ with gr.Blocks(css=CSS, theme=gr.themes.Soft(primary_hue="blue"),
                 choices=[("ปิด / Off", "off"),
                          ("NLLB-200 (เร็ว)", "nllb"),
                          ("Typhoon 2 (ไทยแน่น)", "typhoon")],
-                value="nllb",
+                value="typhoon",
                 label="แปลไทย→อังกฤษ / Auto-translate (พิมพ์ไทยได้เลย)",
             )
 

pipeline_manager.py

@@ -39,7 +39,7 @@ DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 # Modes supported per base family. Used by the UI to gate options.
 SUPPORTED_MODES = {
     "sd15": ["txt2img", "img2img", "ip_adapter", "face_id", "pose"],
-    "sdxl": ["txt2img", "img2img", "ip_adapter", "face_id"],
+    "sdxl": ["txt2img", "img2img", "ip_adapter", "face_id", "pose"],
     "flux": ["txt2img", "img2img"],
 }
 
@@ -340,11 +340,13 @@ def _get_controlnet(base):
     if base in _CONTROLNET:
         return _CONTROLNET[base]
     from diffusers import ControlNetModel
-    if base == "sd15":
-        repo = "lllyasviel/control_v11p_sd15_openpose"
-    else:
-        raise ValueError("Pose (ControlNet) รองรับเฉพาะ SD1.5 ตอนนี้ / SD1.5 only for now.")
-    cn = ControlNetModel.from_pretrained(repo, torch_dtype=DTYPE_SD)
+    repos = {
+        "sd15": "lllyasviel/control_v11p_sd15_openpose",
+        "sdxl": "xinsir/controlnet-openpose-sdxl-1.0",
+    }
+    if base not in repos:
+        raise ValueError("Pose (ControlNet) รองรับ SD1.5 / SDXL เท่านั้น.")
+    cn = ControlNetModel.from_pretrained(repos[base], torch_dtype=DTYPE_SD)
     _CONTROLNET[base] = cn
     return cn
 
@@ -447,8 +449,12 @@ def run_generation(cfg, mode, prompt, negative_prompt, ref_image,
         detector = _get_openpose()
         pose_img = detector(ref_image.convert("RGB")).resize((int(width), int(height)))
         cn = _get_controlnet(base).to(DEVICE)
-        from diffusers import StableDiffusionControlNetPipeline
-        cn_pipe = StableDiffusionControlNetPipeline.from_pipe(pipe, controlnet=cn).to(DEVICE)
+        if base == "sdxl":
+            from diffusers import StableDiffusionXLControlNetPipeline
+            cn_pipe = StableDiffusionXLControlNetPipeline.from_pipe(pipe, controlnet=cn).to(DEVICE)
+        else:
+            from diffusers import StableDiffusionControlNetPipeline
+            cn_pipe = StableDiffusionControlNetPipeline.from_pipe(pipe, controlnet=cn).to(DEVICE)
         call["image"] = pose_img
         return _safe_call(cn_pipe, call)