Merge pull request #9 from greenmagenta/client-handling

Update Client handling

autosculptor/operators.py

@@ -6,6 +6,16 @@
 from bpy.types import Operator
 from .utils import ensure_gradio_installed, install_gradio
 
+# Clients API config
+client_config = {
+    "shap_e": "hysts/Shap-E",
+    "sdxl": "hysts/SDXL",
+    "one_2_3_45": "https://one-2-3-45-one-2-3-45.hf.space/",
+    "dreamgaussian": "https://jiawei011-dreamgaussian.hf.space/",
+    "instantmesh": "TencentARC/InstantMesh",
+    "triposr": "stabilityai/TripoSR"
+}
+
 class InstallDependenciesOperator(Operator):
     bl_idname = "wm.install_dependencies"
     bl_label = "Install Dependencies"
@@ -67,6 +77,9 @@ def run_pipeline(self, autosculptor_props):
         image_height = autosculptor_props.image_height
         api_key = autosculptor_props.api_key
 
+        if api_key == "":
+            api_key = None
+
         for _ in range(batch_count):
             # Get seed for generation
             seed = autosculptor_props.seed
@@ -140,7 +153,8 @@ def generate_model(self, prompt, seed, guidance_scale, num_inference_steps, mode
 
     def generate_shape_e_model(self, api_key, prompt, seed, guidance_scale, num_inference_steps):
         from gradio_client import Client
-        client = Client("hysts/Shap-E", hf_token=api_key)
+
+        client = Client(client_config["shap_e"], hf_token=api_key) if api_key else Client(client_config["shap_e"])
         result = client.predict(
             prompt=prompt,
             seed=seed,
@@ -152,7 +166,7 @@ def generate_shape_e_model(self, api_key, prompt, seed, guidance_scale, num_infe
 
     def generate_sdxl_shape_e_model(self, api_key, prompt, seed, guidance_scale, num_inference_steps, image_width, image_height):
         from gradio_client import Client, handle_file
-        client1 = Client("hysts/SDXL", hf_token=api_key)
+        client1 = Client(client_config["sdxl"], hf_token=api_key) if api_key else Client(client_config["sdxl"])
         image = client1.predict(
             prompt=prompt,
             negative_prompt="",
@@ -167,13 +181,13 @@ def generate_sdxl_shape_e_model(self, api_key, prompt, seed, guidance_scale, num
         )
         image_path = image
 
-        client2 = Client("https://one-2-3-45-one-2-3-45.hf.space/", hf_token=api_key)
+        client2 = Client(client_config["one_2_3_45"], hf_token=api_key) if api_key else Client(client_config["one_2_3_45"])
         segmented_img_filepath = client2.predict(
             image_path,
             api_name="/preprocess"
-            )
+        )
 
-        client3 = Client("hysts/Shap-E", hf_token=api_key)
+        client3 = Client(client_config["shap_e"], hf_token=api_key) if api_key else Client(client_config["shap_e"])
         result = client3.predict(
             image=handle_file(segmented_img_filepath),
             seed=seed,
@@ -185,7 +199,7 @@ def generate_sdxl_shape_e_model(self, api_key, prompt, seed, guidance_scale, num
 
     def generate_sdxl_dreamgaussian_model(self, api_key, prompt, seed, guidance_scale, num_inference_steps, image_width, image_height):
         from gradio_client import Client, handle_file
-        client1 = Client("hysts/SDXL", hf_token=api_key)
+        client1 = Client(client_config["sdxl"], hf_token=api_key) if api_key else Client(client_config["sdxl"])
         image = client1.predict(
             prompt=prompt,
             negative_prompt="",
@@ -200,17 +214,17 @@ def generate_sdxl_dreamgaussian_model(self, api_key, prompt, seed, guidance_scal
         )
         image_path = image
 
-        client2 = Client("https://one-2-3-45-one-2-3-45.hf.space/", hf_token=api_key)
+        client2 = Client(client_config["one_2_3_45"], hf_token=api_key) if api_key else Client(client_config["one_2_3_45"])
         elevation_angle_deg = client2.predict(
             image_path,
             True,
             api_name="/estimate_elevation"
-            )
+        )
 
         if elevation_angle_deg < -90 or elevation_angle_deg > 90:
             elevation_angle_deg = 0
 
-        client3 = Client("https://jiawei011-dreamgaussian.hf.space/", hf_token=api_key)
+        client3 = Client(client_config["dreamgaussian"], hf_token=api_key) if api_key else Client(client_config["dreamgaussian"])
         result = client3.predict(
             image_path,
             True, 
@@ -221,7 +235,7 @@ def generate_sdxl_dreamgaussian_model(self, api_key, prompt, seed, guidance_scal
 
     def generate_sdxl_instantmesh_model(self, api_key, prompt, seed, guidance_scale, num_inference_steps, image_width, image_height):
         from gradio_client import Client, handle_file
-        client1 = Client("hysts/SDXL", hf_token=api_key)
+        client1 = Client(client_config["sdxl"], hf_token=api_key) if api_key else Client(client_config["sdxl"])
         image = client1.predict(
             prompt=prompt,
             negative_prompt="",
@@ -236,7 +250,7 @@ def generate_sdxl_instantmesh_model(self, api_key, prompt, seed, guidance_scale,
         )
         image_path = image
 
-        client2 = Client("TencentARC/InstantMesh", hf_token=api_key)
+        client2 = Client(client_config["instantmesh"], hf_token=api_key) if api_key else Client(client_config["instantmesh"])
         processed_image = client2.predict(
             input_image=handle_file(image_path),
             do_remove_background=True,
@@ -257,7 +271,7 @@ def generate_sdxl_instantmesh_model(self, api_key, prompt, seed, guidance_scale,
 
     def generate_sdxl_triposr_model(self, api_key, prompt, seed, guidance_scale, num_inference_steps, image_width, image_height):
         from gradio_client import Client, handle_file
-        client1 = Client("hysts/SDXL", hf_token=api_key)
+        client1 = Client(client_config["sdxl"], hf_token=api_key) if api_key else Client(client_config["sdxl"])
         image = client1.predict(
             prompt=prompt,
             negative_prompt="",
@@ -272,7 +286,7 @@ def generate_sdxl_triposr_model(self, api_key, prompt, seed, guidance_scale, num
         )
         image_path = image
 
-        client2 = Client("stabilityai/TripoSR", hf_token=api_key)
+        client2 = Client(client_config["triposr"], hf_token=api_key) if api_key else Client(client_config["triposr"])
         processed_image = client2.predict(
             handle_file(image_path),
             True,