* feat(embedding.py): add abstract base class Embedding and two concrete implementations SentenceTransformersEmbedding and OpenAIEmbedding

fastvector/embedding.py

@@ -0,0 +1,31 @@
+from abc import ABC, abstractmethod
+
+
+class Embedding(ABC):
+    @abstractmethod
+    def encode(self, texts):
+        pass
+
+
+class SentenceTransformersEmbedding(Embedding):
+    def __init__(self, model_name="sentence-transformers/all-MiniLM-L6-v2"):
+        try:
+            from sentence_transformers import SentenceTransformer
+        except ImportError:
+            raise ImportError("Please install the sentence-transformers package to use this method.")
+        self.model = SentenceTransformer(model_name)
+
+    def encode(self, texts):
+        return self.model.encode(texts)
+
+
+class OpenAIEmbedding(Embedding):
+    def __init__(self):
+        # Initialize your OpenAI model here
+        # self.model = ...
+        ...
+
+    def encode(self, texts):
+        # Use your OpenAI model to encode the texts
+        # return self.model.encode(texts)
+        raise NotImplementedError