Merge branch 'aurelio-labs:main' into main

README.md

-[![Aurelio AI](https://pbs.twimg.com/profile_banners/1671498317455581184/1696285195/1500x500)](https://aurelio.ai)
-
-# Semantic Router
+[![Semantic Router](https://i.ibb.co.com/g423grt/semantic-router-banner.png)](https://aurelio.ai)
 
 <p>
 <img alt="PyPI - Python Version" src="https://img.shields.io/pypi/pyversions/semantic-router?logo=python&logoColor=gold" />
@@ -144,6 +142,8 @@ Our utterance vector space also integrates with [Pinecone](https://github.com/au
 
 ### Community
 
+Dimitrios Manias, Ali Chouman, Abdallah Shami, [Semantic Routing for Enhanced Performance of LLM-Assisted Intent-Based 5G Core Network Management and Orchestration](https://arxiv.org/abs/2404.15869), IEEE GlobeCom 2024
+
 Julian Horsey, [Semantic Router superfast decision layer for LLMs and AI agents](https://www.geeky-gadgets.com/semantic-router-superfast-decision-layer-for-llms-and-ai-agents/), Geeky Gadgets
 
 azhar, [Beyond Basic Chatbots: How Semantic Router is Changing the Game](https://medium.com/ai-insights-cobet/beyond-basic-chatbots-how-semantic-router-is-changing-the-game-783dd959a32d), AI Insights @ Medium

pyproject.toml

 [tool.poetry]
 name = "semantic-router"
-version = "0.0.44"
+version = "0.0.45"
 description = "Super fast semantic router for AI decision making"
 authors = [
     "James Briggs <james@aurelio.ai>",
@@ -25,9 +25,9 @@ numpy = "^1.25.2"
 colorlog = "^6.8.0"
 pyyaml = "^6.0.1"
 pinecone-text = {version = ">=0.7.1,<0.8.0", optional = true}
-fastembed = {version = "^0.2.4", optional = true, python = "<3.12"}
 torch = {version = ">=2.1.0,<2.6.0", optional = true}
-transformers = {version = "^4.36.2", optional = true}
+transformers = {version = ">=4.36.2", optional = true}
+tokenizers = {version = ">=0.19", optional = true}
 llama-cpp-python = {version = "^0.2.28", optional = true}
 colorama = "^0.4.6"
 pinecone-client = {version=">=3.0.0,<4.0.0", optional = true}
@@ -43,8 +43,7 @@ boto3 = { version = "^1.34.98", optional = true }
 
 [tool.poetry.extras]
 hybrid = ["pinecone-text"]
-fastembed = ["fastembed"]
-local = ["torch", "transformers", "llama-cpp-python"]
+local = ["torch", "transformers", "tokenizers", "huggingface-hub", "llama-cpp-python"]
 pinecone = ["pinecone-client"]
 vision = ["torch", "torchvision", "transformers", "pillow"]
 processing = ["matplotlib"]

semantic_router/__init__.py

@@ -4,4 +4,4 @@ from semantic_router.route import Route
 
 __all__ = ["RouteLayer", "HybridRouteLayer", "Route", "LayerConfig"]
 
-__version__ = "0.0.44"
+__version__ = "0.0.45"

semantic_router/encoders/zure.py

@@ -94,7 +94,9 @@ class AzureOpenAIEncoder(BaseEncoder):
         for j in range(3):
             try:
                 embeds = self.client.embeddings.create(
-                    input=docs, model=str(self.model), dimensions=self.dimensions,
+                    input=docs,
+                    model=str(self.model),
+                    dimensions=self.dimensions,
                 )
                 if embeds.data:
                     break

tests/unit/encoders/test_clip.py

@@ -5,7 +5,7 @@ from PIL import Image
 
 from semantic_router.encoders import CLIPEncoder
 
-test_model_name = "hf-internal-testing/tiny-random-CLIPModel"
+test_model_name = "aurelio-ai/sr-test-clip"
 clip_encoder = CLIPEncoder(name=test_model_name)
 embed_dim = 64
 

tests/unit/encoders/test_fastembed.py

@@ -3,8 +3,10 @@ from semantic_router.encoders import FastEmbedEncoder
 
 class TestFastEmbedEncoder:
     def test_fastembed_encoder(self):
-        encode = FastEmbedEncoder()
-        test_docs = ["This is a test", "This is another test"]
+        if False:
+            # temporarily disabled until fastembed added back as dep
+            encode = FastEmbedEncoder()
+            test_docs = ["This is a test", "This is another test"]
 
-        embeddings = encode(test_docs)
-        assert isinstance(embeddings, list)
+            embeddings = encode(test_docs)
+            assert isinstance(embeddings, list)

tests/unit/encoders/test_huggingface.py

@@ -5,7 +5,7 @@ import pytest
 
 from semantic_router.encoders.huggingface import HuggingFaceEncoder
 
-test_model_name = "hf-internal-testing/tiny-bert"
+test_model_name = "aurelio-ai/sr-test-huggingface"
 encoder = HuggingFaceEncoder(name=test_model_name)
 
 

tests/unit/encoders/test_vit.py

@@ -5,7 +5,7 @@ from PIL import Image
 
 from semantic_router.encoders import VitEncoder
 
-test_model_name = "hf-internal-testing/tiny-random-vit"
+test_model_name = "aurelio-ai/sr-test-vit"
 vit_encoder = VitEncoder(name=test_model_name)
 embed_dim = 32