merge

README.md

@@ -65,7 +65,7 @@ encoder = OpenAIEncoder()
 With our `decisions` and `encoder` defined we now create a `DecisionLayer`. The decision layer handles our semantic decision making.
 
 ```python
-from semantic_router import DecisionLayer
+from semantic_router.layer import DecisionLayer
 
 dl = DecisionLayer(encoder=encoder, decisions=decisions)
 ```
@@ -106,4 +106,4 @@ In this case, no decision could be made as we had no matches — so our decision
 
 |     |     |
 | --- | --- |
-| 🏃 [Walkthrough](https://colab.research.google.com/github/aurelio-labs/semantic-router/blob/main/walkthrough.ipynb) | Quickstart Python notebook |
\ No newline at end of file
+| 🏃 [Walkthrough](https://colab.research.google.com/github/aurelio-labs/semantic-router/blob/main/walkthrough.ipynb) | Quickstart Python notebook |

pyproject.toml

@@ -11,8 +11,8 @@ authors = [
 readme = "README.md"
 
 [tool.poetry.dependencies]
-python = "^3.11"
-pydantic = "^2.4.2"
+python = "^3.10"
+pydantic = "^1.8.2"
 openai = "^0.28.1"
 cohere = "^4.32"
 

semantic_router/retrievers/cohere.py

@@ -20,9 +20,5 @@ class CohereRetriever(BaseRetriever):
     def __call__(self, docs: list[str]) -> list[list[float]]:
         if self.client is None:
             raise ValueError("Cohere client is not initialized.")
-        if len(docs) == 1:
-            input_type = "search_query"
-        else:
-            input_type = "search_document"
-        embeds = self.client.embed(docs, input_type=input_type, model=self.name)
+        embeds = self.client.embed(docs, input_type="search_query", model=self.name)
         return embeds.embeddings

semantic_router/schema.py

@@ -6,7 +6,6 @@ from pydantic.dataclasses import dataclass
 from semantic_router.retrievers import (
     BaseRetriever,
     CohereRetriever,
-    HuggingFaceRetriever,
     OpenAIRetriever,
 )
 
@@ -33,7 +32,7 @@ class Retriever:
         self.type = RetrieverType(type)
         self.name = name
         if self.type == RetrieverType.HUGGINGFACE:
-            self.model = HuggingFaceRetriever(name)
+            raise NotImplementedError
         elif self.type == RetrieverType.OPENAI:
             self.model = OpenAIRetriever(name)
         elif self.type == RetrieverType.COHERE: