comfy manager naming

pyproject.toml

@@ -3,9 +3,9 @@ requires = ["setuptools>=70.0"]
 build-backend = "setuptools.build_meta"
 
 [project]
-name = "inferencescale"
+name = "ComfyUI-InferenceTimeScaling"
 version = "0.0.1"
-description = "inference diffusion scaling"
+description = "Inference-time diffusion scaling"
 authors = [
   {name = "Max Clouser", email = "maximclouser@gmail.com"}
 ]
@@ -27,13 +27,13 @@ dev = [
 ]
 
 [project.urls]
-bugs = "https://github.com/MaximClouser/inferencescale/issues"
-homepage = "https://github.com/MaximClouser/inferencescale"
+bugs = "https://github.com/MaximClouser/ComfyUI-InferenceTimeScaling/issues"
+homepage = "https://github.com/MaximClouser/ComfyUI-InferenceTimeScaling"
 
 
 [tool.comfy]
 PublisherId = "maximclouser"
-DisplayName = "InferenceScale"
+DisplayName = "ComfyUI-InferenceTimeScaling"
 Icon = ""
 
 [tool.setuptools.package-data]

src/inferencescale/nodes.py

@@ -78,9 +78,9 @@ def common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive,
 def rank_candidates(results_by_verifier, num_candidates):
     """
     results_by_verifier: {
-       'clip': [score0, score1, ...],
-       'image_reward': [...],
-       'qwen_vlm_verifier': [...],
+       'clip': [score0, score1, ...], # Scores for each image from CLIP
+       'image_reward': [...], # Scores from ImageReward
+       'qwen_vlm_verifier': [...], # Scores from Qwen
        ...
     }
     Convert each verifier's raw scores into ranks (best=rank 1), then compute
@@ -175,8 +175,7 @@ def score_candidates(candidate_tensors: List[torch.Tensor], text_prompt: str, ve
 
 def rank_from_raw_scores(raw_scores_list):
     """
-    Converts a list of raw score dictionaries into a ranked list
-    using the existing ranking mechanism.
+    Converts a list of raw score dictionaries into a ranked list.
     """
     # Build a verifier-to-scores dictionary from the raw_scores_list
     results_by_verifier = {}