diff --git a/ragengine/__init__.py b/ragengine/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/ragengine/embedding/__init__.py b/ragengine/embedding/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/ragengine/embedding/base.py b/ragengine/embedding/base.py
new file mode 100644
index 000000000..a1c371937
--- /dev/null
+++ b/ragengine/embedding/base.py
@@ -0,0 +1,13 @@
+from abc import ABC, abstractmethod
+
+
+class BaseEmbeddingModel(ABC):
+    @abstractmethod
+    def get_text_embedding(self, text: str):
+        """Returns the text embedding for a given input string."""
+        pass
+    
+    @abstractmethod
+    def get_embedding_dimension(self) -> int:
+        """Returns the embedding dimension for the model."""
+        pass
\ No newline at end of file
diff --git a/ragengine/embedding/huggingface_local.py b/ragengine/embedding/huggingface_local.py
new file mode 100644
index 000000000..3dab51e9a
--- /dev/null
+++ b/ragengine/embedding/huggingface_local.py
@@ -0,0 +1,19 @@
+from llama_index.embeddings.huggingface import HuggingFaceEmbedding
+
+from .base import BaseEmbeddingModel
+
+
+class LocalHuggingFaceEmbedding(BaseEmbeddingModel):
+    def __init__(self, model_name: str):
+        self.model = HuggingFaceEmbedding(model_name=model_name) # TODO: Ensure/test loads on GPU (when available)
+
+    def get_text_embedding(self, text: str):
+        """Returns the text embedding for a given input string."""
+        return self.model.get_text_embedding(text)
+
+    def get_embedding_dimension(self) -> int:
+        """Infers the embedding dimension by making a local call to get the embedding of a dummy text."""
+        dummy_input = "This is a dummy sentence."
+        embedding = self.get_text_embedding(dummy_input)
+        
+        return len(embedding)
\ No newline at end of file
diff --git a/ragengine/embedding/huggingface_remote.py b/ragengine/embedding/huggingface_remote.py
new file mode 100644
index 000000000..0f8e79181
--- /dev/null
+++ b/ragengine/embedding/huggingface_remote.py
@@ -0,0 +1,20 @@
+from llama_index.embeddings.huggingface_api import \
+    HuggingFaceInferenceAPIEmbedding
+
+from .base import BaseEmbeddingModel
+
+
+class RemoteHuggingFaceEmbedding(BaseEmbeddingModel):
+    def __init__(self, model_name: str, api_key: str):
+        self.model = HuggingFaceInferenceAPIEmbedding(model_name=model_name, token=api_key)
+
+    def get_text_embedding(self, text: str):
+        """Returns the text embedding for a given input string."""
+        return self.model.get_text_embedding(text)
+    
+    def get_embedding_dimension(self) -> int:
+        """Infers the embedding dimension by making a remote call to get the embedding of a dummy text."""
+        dummy_input = "This is a dummy sentence."
+        embedding = self.get_text_embedding(dummy_input)
+        
+        return len(embedding)
diff --git a/ragengine/requirements.txt b/ragengine/requirements.txt
new file mode 100644
index 000000000..18ca062fc
--- /dev/null
+++ b/ragengine/requirements.txt
@@ -0,0 +1,7 @@
+# RAG Library Requirements
+llama-index
+llama-index-embeddings-huggingface
+fastapi
+faiss-cpu
+llama-index-vector-stores-faiss
+uvicorn