rename

Author: ulfaslak

README.md

@@ -19,15 +19,15 @@ pip install -e .
 ### From GitHub Repository
 To install this package into your own project from GitHub, run:
 ```bash
-pip install git+https://github.com/pymc-labs/embeddings-similarity-rating.git
+pip install git+https://github.com/pymc-labs/semantic-similarity-rating.git
 ```
 
 ## Quick Start
 
 ```python
 import polars as po
 import numpy as np
-from embeddings_similarity_rating import ResponseRater
+from semantic_similarity_rating import ResponseRater
 
 # Create example reference sentences dataframe
 reference_set_1 = [

pixi.lock

@@ -8,7 +8,7 @@ dependencies = [
     "sentence-transformers>=2.2.0",
 ]
 description = "A Python package implementing the Embeddings-Similarity Rating methodology for converting LLM textual responses to Likert scale probability distributions using semantic similarity against reference statements."
-name = "embeddings_similarity_rating"
+name = "semantic_similarity_rating"
 requires-python = ">= 3.10"
 version = "1.0.0"
 readme = "README.md"
@@ -37,7 +37,7 @@ channels = ["conda-forge"]
 platforms = ["osx-arm64", "linux-64", "osx-64"]
 
 [tool.pixi.pypi-dependencies]
-embeddings_similarity_rating = { path = ".", editable = true }
+semantic_similarity_rating = { path = ".", editable = true }
 
 [tool.pixi.dependencies]
 ipykernel = "*"

pyproject.toml

@@ -76,7 +76,7 @@ class ResponseRater:
     **Text mode (automatic embedding computation):**
 
     >>> import polars as po
-    >>> from embeddings_similarity_rating import ResponseRater
+    >>> from semantic_similarity_rating import ResponseRater
     >>>
     >>> # Create reference sentences dataframe (no embedding column)
     >>> df = po.DataFrame({

embeddings_similarity_rating/__init__.py renamed to semantic_similarity_rating/__init__.py

@@ -4,7 +4,7 @@
 
 import numpy as np
 import pytest
-from embeddings_similarity_rating.compute import (
+from semantic_similarity_rating.compute import (
     scale_pmf,
     response_embeddings_to_pmf,
 )

embeddings_similarity_rating/compute.py renamed to semantic_similarity_rating/compute.py

@@ -5,7 +5,7 @@
 import numpy as np
 import polars as po
 import pytest
-from embeddings_similarity_rating import ResponseRater
+from semantic_similarity_rating import ResponseRater
 
 # Test constants
 EMBEDDING_DIM = 128