Merge pull request #5 from aurelio-labs/tolga/semantic-router-compati…

…bility

fix: update the semantic-router version field

docs/01-video-chunking.ipynb

@@ -31,7 +31,7 @@
    "outputs": [],
    "source": [
     "!pip install -qU \\\n",
-    "    \"semantic-chunkers[stats]==0.0.3\" \\\n",
+    "    \"semantic-chunkers[stats]\" \\\n",
     "    \"semantic-router[vision]==0.0.39\" \\\n",
     "    opencv-python"
    ]
@@ -128,8 +128,11 @@
     "import torch\n",
     "from semantic_router.encoders import VitEncoder\n",
     "\n",
-    "device = \"mps\" if torch.backends.mps.is_available() else \"cuda\" \\\n",
-    "    if torch.cuda.is_available() else \"cpu\"\n",
+    "device = (\n",
+    "    \"mps\"\n",
+    "    if torch.backends.mps.is_available()\n",
+    "    else \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
+    ")\n",
     "print(f\"Using '{device}'\")\n",
     "\n",
     "encoder = VitEncoder(device=device)"

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "semantic-chunkers"
-version = "0.0.3"
+version = "0.0.4"
 description = "Super advanced chunking methods for AI"
 authors = ["Aurelio AI <[email protected]>"]
 readme = "README.md"
@@ -16,7 +16,7 @@ regex = "^2023.12.25"
 tiktoken = "^0.6.0"
 matplotlib = { version = "^3.8.3", optional = true}
 requests-mock = "^1.12.1"
-semantic-router = "^0.0.39"
+semantic-router = ">=0.0.20,<0.1.0"
 
 [tool.poetry.extras]
 stats = ["matplotlib"]
@@ -31,7 +31,7 @@ pytest-xdist = "^3.5.0"
 mypy = "^1.7.1"
 types-pyyaml = "^6.0.12.12"
 types-requests = "^2.31.0"
-black = "^24.0.0"
+black = "^23.12.1"
 
 [build-system]
 requires = ["poetry-core"]

semantic_chunkers/__init__.py

@@ -10,4 +10,4 @@
     "StatisticalChunker",
 ]
 
-__version__ = "0.0.3"
+__version__ = "0.0.4"

tests/unit/test_splitters.py

@@ -18,7 +18,6 @@ def test_consecutive_sim_splitter():
     cohere_encoder = CohereEncoder(
         name="",
         cohere_api_key="a",
-        input_type="",
     )
     # Instantiate the ConsecutiveSimSplitter with the mock encoder
     splitter = ConsecutiveChunker(encoder=cohere_encoder, score_threshold=0.9)
@@ -55,7 +54,6 @@ def test_cumulative_sim_splitter():
     cohere_encoder = CohereEncoder(
         name="",
         cohere_api_key="a",
-        input_type="",
     )
     splitter = CumulativeChunker(encoder=cohere_encoder, score_threshold=0.9)
     splitter.encoder = mock_encoder