Merge pull request #93 from Haidra-Org/main

feat: use latest comfyui (as of Nov 10, 2023)

hordelib/consts.py

@@ -6,7 +6,7 @@
 
 from hordelib.config_path import get_hordelib_path
 
-COMFYUI_VERSION = "dd116abfc48e8023bb425c2dd5bd954ee99d7a9c"
+COMFYUI_VERSION = "3e0033ef30a111076af54a7a4e6b470cdc570886"
 """The exact version of ComfyUI version to load."""
 
 REMOTE_PROXY = ""

hordelib/model_manager/lora.py

@@ -334,7 +334,9 @@ def _download_thread(self, thread_number):
                     response = requests.get(lora["url"], timeout=self.REQUEST_DOWNLOAD_TIMEOUT)
                     response.raise_for_status()
                     if "reason=download-auth" in response.url:
-                        logger.error(f"Error downloading {lora['filename']}. CivitAI appears to be redirecting us to a login page. Aborting")
+                        logger.error(
+                            f"Error downloading {lora['filename']}. CivitAI appears to be redirecting us to a login page. Aborting"
+                        )
                         break
                     # Check the data hash
                     hash_object = hashlib.sha256()
@@ -567,7 +569,7 @@ def find_lora_trigger(self, model_name: str, trigger_search: str):
 
     def save_cached_reference_to_disk(self):
         with open(self.models_db_path, "w", encoding="utf-8", errors="ignore") as outfile:
-            outfile.write(json.dumps(self.model_reference, indent=4))
+            outfile.write(json.dumps(self.model_reference.copy(), indent=4))
 
     def calculate_downloaded_loras(self, mode=DOWNLOAD_SIZE_CHECK.everything):
         total_size = 0

tests/test_horde_lora.py

@@ -242,6 +242,10 @@ def test_text_to_image_lora_blue_low_strength(
 
         img_filename = "lora_blue_low_model_strength.png"
         pil_image.save(f"images/{img_filename}", quality=100)
+        assert check_single_lora_image_similarity(
+            f"images_expected/{img_filename}",
+            pil_image,
+        )
 
         data["loras"] = [{"name": lora_name, "model": 1.0, "clip": 0.1}]
         pil_image = hordelib_instance.basic_inference_single_image(data)
@@ -250,6 +254,10 @@ def test_text_to_image_lora_blue_low_strength(
 
         img_filename = "lora_blue_low_clip_strength.png"
         pil_image.save(f"images/{img_filename}", quality=100)
+        assert check_single_lora_image_similarity(
+            f"images_expected/{img_filename}",
+            pil_image,
+        )
 
         data["loras"] = [{"name": lora_name, "model": 0.1, "clip": 0.1}]
         pil_image = hordelib_instance.basic_inference_single_image(data)
@@ -258,6 +266,10 @@ def test_text_to_image_lora_blue_low_strength(
 
         img_filename = "lora_blue_low_model_and_clip_strength.png"
         pil_image.save(f"images/{img_filename}", quality=100)
+        assert check_single_lora_image_similarity(
+            f"images_expected/{img_filename}",
+            pil_image,
+        )
 
     def test_text_to_image_lora_blue_negative_strength(
         self,
@@ -295,22 +307,37 @@ def test_text_to_image_lora_blue_negative_strength(
         pil_image = hordelib_instance.basic_inference_single_image(data)
         assert pil_image is not None
         assert isinstance(pil_image, Image.Image)
+
         img_filename = "lora_blue_negative_model_strength.png"
         pil_image.save(f"images/{img_filename}", quality=100)
+        assert check_single_lora_image_similarity(
+            f"images_expected/{img_filename}",
+            pil_image,
+        )
 
         data["loras"] = [{"name": lora_name, "model": 1.0, "clip": -1.0}]
         pil_image = hordelib_instance.basic_inference_single_image(data)
         assert pil_image is not None
         assert isinstance(pil_image, Image.Image)
+
         img_filename = "lora_blue_negative_clip_strength.png"
         pil_image.save(f"images/{img_filename}", quality=100)
+        assert check_single_lora_image_similarity(
+            f"images_expected/{img_filename}",
+            pil_image,
+        )
 
         data["loras"] = [{"name": lora_name, "model": -1.0, "clip": -1.0}]
         pil_image = hordelib_instance.basic_inference_single_image(data)
         assert pil_image is not None
         assert isinstance(pil_image, Image.Image)
+
         img_filename = "lora_blue_negative_model_and_clip_strength.png"
         pil_image.save(f"images/{img_filename}", quality=100)
+        assert check_single_lora_image_similarity(
+            f"images_expected/{img_filename}",
+            pil_image,
+        )
 
     def test_text_to_image_lora_blue_hires_fix(
         self,
@@ -815,6 +842,11 @@ def test_negative_model_power(
         img_filename = "lora_negative_strength.png"
         pil_image.save(f"images/{img_filename}", quality=100)
 
+        assert check_single_lora_image_similarity(
+            f"images_expected/{img_filename}",
+            pil_image,
+        )
+
         data = {
             "sampler_name": "k_euler",
             "cfg_scale": 8.0,

tests/test_horde_samplers.py

@@ -1,6 +1,7 @@
 # test_horde.py
 
 from PIL import Image
+from loguru import logger
 
 from hordelib.horde import HordeLib
 
@@ -81,6 +82,7 @@ def test_samplers(
             images_to_compare.append((f"images_expected/{img_filename}", pil_image))
 
         for img_filename, pil_image in images_to_compare:
+            logger.debug(f"Checking image {img_filename}")
             assert check_single_inference_image_similarity(
                 img_filename,
                 pil_image,