support model ProteusV0.2

Author: smalltong02

WebUI/configs/basicconfig.py

@@ -429,7 +429,7 @@ def generate_prompt_for_imagegen(model_name : str = "", prompt : str = "", image
     new_prompt = ""
     if len(model_name) == 0 or len(prompt) == 0:
         return prompt
-    if model_name == "OpenDalleV1.1":        
+    if model_name == "OpenDalleV1.1" or model_name == "ProteusV0.2":        
         new_prompt = """
                 You need to create prompts for an image generation model based on the user's question. The format of the prompts is the features of the image, separated by commas, with no any other information outputted, for example:
 

WebUI/configs/imagemodels.py

@@ -123,7 +123,7 @@ def init_image_generation_models(config):
     if not torch.cuda.is_available():
         return None
     if isinstance(config, dict):
-        if config["model_name"] == "OpenDalleV1.1":
+        if config["model_name"] == "OpenDalleV1.1" or config["model_name"] == "ProteusV0.2":
             from diffusers import AutoencoderKL, DiffusionPipeline
             model_id = config["model_path"]
             enable_torch_compile = config["torch_compile"]
@@ -180,7 +180,7 @@ def first_prompt(prompt):
 
     if len(text_data) and model is not None:
         if isinstance(config, dict):
-            if config["model_name"] == "OpenDalleV1.1":
+            if config["model_name"] == "OpenDalleV1.1" or config["model_name"] == "ProteusV0.2":
                 seed = config["seed"]
                 apply_refiner = False if refiner is None else True
                 if seed == -1:

WebUI/configs/webuiconfig.json

@@ -137,6 +137,19 @@
                     "cpu_offload": false,
                     "refiner": true
                 }
+            },
+            "ProteusV0.2": {
+                "type": "local",
+                "path": "models/imagegeneration/ProteusV0.2",
+                "device": "auto",
+                "loadbits": 16,
+                "Huggingface": "dataautogpt3/ProteusV0.2",
+                "config": {
+                    "seed": -1,
+                    "torch_compile": false,
+                    "cpu_offload": false,
+                    "refiner": true
+                }
             }
         },
         "VtoTModel": {

WebUI/webui_pages/tools_agent/toolsagent.py

@@ -924,7 +924,7 @@ def tools_agent_page(api: ApiRequest, is_lite: bool = False):
                         provider = imagegenmodels[imagegenmodel].get("provider", "")
                         pathstr = imagegenmodels[imagegenmodel].get("path")
                         if provider != "" or ImageModelExist(pathstr):
-                            if imagegenmodel == "OpenDalleV1.1" and ImageModelExist("models/imagegeneration/sdxl-vae-fp16-fix") == False:
+                            if (imagegenmodel == "OpenDalleV1.1" or imagegenmodel == "ProteusV0.2") and ImageModelExist("models/imagegeneration/sdxl-vae-fp16-fix") == False:
                                 st.error("Please first download the sdxl-vae-fp16-fix model from Hugginface.")
                             else:
                                 r = api.change_image_generation_model(current_imagegen_model, imagegenmodel)