update sd-webui api parameters to v1.9.3 (#4798)

Co-authored-by: Your Name <chen@krasus.red>

api/core/tools/provider/builtin/stablediffusion/tools/stable_diffusion.py

@@ -13,49 +13,76 @@ from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter,
 from core.tools.errors import ToolProviderCredentialValidationError
 from core.tools.tool.builtin_tool import BuiltinTool
 
+# All commented out parameters default to null
 DRAW_TEXT_OPTIONS = {
+    # Prompts
     "prompt": "",
     "negative_prompt": "",
+    # "styles": [],                
+    # Seeds 
     "seed": -1,
     "subseed": -1,
     "subseed_strength": 0,
     "seed_resize_from_h": -1,
-    'sampler_index': 'DPM++ SDE Karras',
     "seed_resize_from_w": -1,
+
+    # Samplers
+    # "sampler_name": "DPM++ 2M",
+    # "scheduler": "",
+    # "sampler_index": "Automatic",
+
+    # Latent Space Options
     "batch_size": 1,
     "n_iter": 1,
     "steps": 10,
     "cfg_scale": 7,
-    "width": 1024,
-    "height": 1024,
-    "restore_faces": False,
+    "width": 512,
+    "height": 512,
+    # "restore_faces": True,
+    # "tiling": True,
     "do_not_save_samples": False,
     "do_not_save_grid": False,
-    "eta": 0,
-    "denoising_strength": 0,
-    "s_min_uncond": 0,
-    "s_churn": 0,
-    "s_tmax": 0,
-    "s_tmin": 0,
-    "s_noise": 0,
+    # "eta": 0,                      
+    # "denoising_strength": 0.75,   
+    # "s_min_uncond": 0,             
+    # "s_churn": 0,
+    # "s_tmax": 0,
+    # "s_tmin": 0,
+    # "s_noise": 0,
     "override_settings": {},
     "override_settings_restore_afterwards": True,
+    # Refinement Options
+    "refiner_checkpoint": "",
     "refiner_switch_at": 0,
     "disable_extra_networks": False,
-    "comments": {},
+    # "firstpass_image": "",
+    # "comments": "",
+    # High-Resolution Options
     "enable_hr": False,
     "firstphase_width": 0,
     "firstphase_height": 0,
     "hr_scale": 2,
+    # "hr_upscaler": "",
     "hr_second_pass_steps": 0,
     "hr_resize_x": 0,
     "hr_resize_y": 0,
+    # "hr_checkpoint_name": "",
+    # "hr_sampler_name": "",
+    # "hr_scheduler": "",
     "hr_prompt": "",
     "hr_negative_prompt": "",
+    # Task Options
+    # "force_task_id": "",
+
+    # Script Options
+    # "script_name": "",
     "script_args": [],
+    # Output Options
     "send_images": True,
     "save_images": False,
-    "alwayson_scripts": {}
+    "alwayson_scripts": {},
+    # "infotext": "",
+    
 }
 
 
@@ -88,60 +115,15 @@ class StableDiffusionTool(BuiltinTool):
         except Exception as e:
             raise ToolProviderCredentialValidationError('Failed to set model, please tell user to set model')
 
-        
-        # prompt
-        prompt = tool_parameters.get('prompt', '')
-        if not prompt:
-            return self.create_text_message('Please input prompt')
-        
-        # get negative prompt
-        negative_prompt = tool_parameters.get('negative_prompt', '')
-        
-        # get size
-        width = tool_parameters.get('width', 1024)
-        height = tool_parameters.get('height', 1024)
-
-        # get steps
-        steps = tool_parameters.get('steps', 1)
-
-        # get lora
-        lora = tool_parameters.get('lora', '')
-
-        # get image id
+        # get image id and image variable
         image_id = tool_parameters.get('image_id', '')
-        if image_id.strip():
-            image_variable = self.get_default_image_variable()
-            if image_variable:
-                image_binary = self.get_variable_file(image_variable.name)
-                if not image_binary:
-                    return self.create_text_message('Image not found, please request user to generate image firstly.')
-                
-                # convert image to RGB
-                image = Image.open(io.BytesIO(image_binary))
-                image = image.convert("RGB")
-                buffer = io.BytesIO()
-                image.save(buffer, format="PNG")
-                image_binary = buffer.getvalue()
-                image.close()
+        image_variable = self.get_default_image_variable()
+        # Return text2img if there's no image ID or no image variable
+        if not image_id or not image_variable:
+            return self.text2img(base_url=base_url,tool_parameters=tool_parameters)
 
-                return self.img2img(base_url=base_url,
-                                    lora=lora,
-                                    image_binary=image_binary,
-                                    prompt=prompt,
-                                    negative_prompt=negative_prompt,
-                                    width=width,
-                                    height=height,
-                                    steps=steps,
-                                    model=model)
-            
-        return self.text2img(base_url=base_url,
-                             lora=lora,
-                             prompt=prompt,
-                             negative_prompt=negative_prompt,
-                             width=width,
-                             height=height,
-                             steps=steps,
-                             model=model)
+        # Proceed with image-to-image generation
+        return self.img2img(base_url=base_url,tool_parameters=tool_parameters)
 
     def validate_models(self) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]:
         """
@@ -197,35 +179,67 @@ class StableDiffusionTool(BuiltinTool):
         except Exception as e:
             return []
 
-    def img2img(self, base_url: str, lora: str, image_binary: bytes, 
-                prompt: str, negative_prompt: str,
-                width: int, height: int, steps: int, model: str) \
+    def img2img(self, base_url: str, tool_parameters: dict[str, Any]) \
         -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]:
         """
             generate image
         """
-        draw_options = {
+
+        # Fetch the binary data of the image
+        image_variable = self.get_default_image_variable()
+        image_binary = self.get_variable_file(image_variable.name)
+        if not image_binary:
+            return self.create_text_message('Image not found, please request user to generate image firstly.')
+
+        # Convert image to RGB and save as PNG
+        try:
+            with Image.open(io.BytesIO(image_binary)) as image:
+                with io.BytesIO() as buffer:
+                    image.convert("RGB").save(buffer, format="PNG")
+                    image_binary = buffer.getvalue()
+        except Exception as e:
+            return self.create_text_message(f"Failed to process the image: {str(e)}")
+
+        # copy draw options
+        draw_options = deepcopy(DRAW_TEXT_OPTIONS)
+        # set image options
+        model = tool_parameters.get('model', '')
+        draw_options_image = {
             "init_images": [b64encode(image_binary).decode('utf-8')],
-            "prompt": "",
-            "negative_prompt": negative_prompt,
             "denoising_strength": 0.9,
-            "width": width,
-            "height": height,
-            "cfg_scale": 7,
-            "sampler_name": "Euler a",
             "restore_faces": False,
-            "steps": steps,
-            "script_args": ["outpainting mk2"],
-            "override_settings": {"sd_model_checkpoint": model}
+            "script_args": [],
+            "override_settings": {"sd_model_checkpoint": model},
+            "resize_mode":0,
+            "image_cfg_scale": 0,
+            # "mask": None,
+            "mask_blur_x": 4,
+            "mask_blur_y": 4,
+            "mask_blur": 0,
+            "mask_round": True,
+            "inpainting_fill": 0,
+            "inpaint_full_res": True,
+            "inpaint_full_res_padding": 0,
+            "inpainting_mask_invert": 0,
+            "initial_noise_multiplier": 0,
+            # "latent_mask": None,
+            "include_init_images": True,
         }
+        # update key and values
+        draw_options.update(draw_options_image)
+        draw_options.update(tool_parameters)
 
+        # get prompt lora model
+        prompt = tool_parameters.get('prompt', '')
+        lora = tool_parameters.get('lora', '')
+        model = tool_parameters.get('model', '')
         if lora:
             draw_options['prompt'] = f'{lora},{prompt}'
         else:
             draw_options['prompt'] = prompt
 
         try:
-            url = str(URL(base_url) / 'sdapi' / 'v1' / 'img2img')
+            url = str(URL(base_url) / 'sdapi' / 'v1' / 'img2img') 
             response = post(url, data=json.dumps(draw_options), timeout=120)
             if response.status_code != 200:
                 return self.create_text_message('Failed to generate image')
@@ -239,24 +253,24 @@ class StableDiffusionTool(BuiltinTool):
         except Exception as e:
             return self.create_text_message('Failed to generate image')
 
-    def text2img(self, base_url: str, lora: str, prompt: str, negative_prompt: str, width: int, height: int, steps: int, model: str) \
+    def text2img(self, base_url: str, tool_parameters: dict[str, Any]) \
         -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]:
         """
             generate image
         """
         # copy draw options
         draw_options = deepcopy(DRAW_TEXT_OPTIONS)
-
+        draw_options.update(tool_parameters)
+        # get prompt lora model
+        prompt = tool_parameters.get('prompt', '')
+        lora = tool_parameters.get('lora', '')
+        model = tool_parameters.get('model', '')
         if lora:
             draw_options['prompt'] = f'{lora},{prompt}'
         else:
             draw_options['prompt'] = prompt
-
-        draw_options['width'] = width
-        draw_options['height'] = height
-        draw_options['steps'] = steps
-        draw_options['negative_prompt'] = negative_prompt
         draw_options['override_settings']['sd_model_checkpoint'] = model
+
         
         try:
             url = str(URL(base_url) / 'sdapi' / 'v1' / 'txt2img')