Fixup bert python bindings.

gpt4all-bindings/python/gpt4all/__init__.py

@@ -1,2 +1,2 @@
-from .gpt4all import GPT4All, embed  # noqa
+from .gpt4all import GPT4All, Embedder  # noqa
 from .pyllmodel import LLModel  # noqa

gpt4all-bindings/python/gpt4all/gpt4all.py

@@ -15,20 +15,26 @@ from . import pyllmodel
 # TODO: move to config
 DEFAULT_MODEL_DIRECTORY = os.path.join(str(Path.home()), ".cache", "gpt4all").replace("\\", "\\\\")
 
-def embed(
-    text: str
-) -> list[float]:
-    """
-    Generate an embedding for all GPT4All.
+class Embedder:
+    def __init__(
+        self
+    ):
+        self.gpt4all = GPT4All(model_name='ggml-all-MiniLM-L6-v2-f16.bin', n_threads=8)
 
-    Args:
-        text: The text document to generate an embedding for.
+    def embed(
+        self,
+        text: str
+    ) -> list[float]:
+        """
+        Generate an embedding for all GPT4All.
 
-    Returns:
-        An embedding of your document of text.
-    """
-    model = GPT4All(model_name='ggml-all-MiniLM-L6-v2-f16.bin')
-    return model.model.generate_embedding(text)
+        Args:
+            text: The text document to generate an embedding for.
+
+        Returns:
+            An embedding of your document of text.
+        """
+        return self.gpt4all.model.generate_embedding(text)
 
 class GPT4All:
     """

gpt4all-bindings/python/gpt4all/pyllmodel.py

@@ -253,7 +253,7 @@ class LLModel:
         embedding_size = ctypes.c_size_t()
         c_text = ctypes.c_char_p(text.encode('utf-8'))
         embedding_ptr = llmodel.llmodel_embedding(self.model, c_text, ctypes.byref(embedding_size))
-        embedding_array = ctypes.cast(embedding_ptr, ctypes.POINTER(ctypes.c_float * embedding_size.value)).contents
+        embedding_array = [embedding_ptr[i] for i in range(embedding_size.value)]
         llmodel.llmodel_free_embedding(embedding_ptr)
         return list(embedding_array)