fastembed integration new parameters

integrations/fastembed/src/haystack_integrations/components/embedders/fastembed/embedding_backend/fastembed_backend.py

@@ -1,4 +1,4 @@
-from typing import ClassVar, Dict, List
+from typing import ClassVar, Dict, List, Optional
 
 from fastembed import TextEmbedding
 
@@ -13,15 +13,15 @@ class _FastembedEmbeddingBackendFactory:
     @staticmethod
     def get_embedding_backend(
         model_name: str,
+        cache_dir: Optional[str] = None,
+        threads: Optional[int] = None,
     ):
-        embedding_backend_id = f"{model_name}"
+        embedding_backend_id = f"{model_name}{cache_dir}{threads}"
 
         if embedding_backend_id in _FastembedEmbeddingBackendFactory._instances:
             return _FastembedEmbeddingBackendFactory._instances[embedding_backend_id]
 
-        embedding_backend = _FastembedEmbeddingBackend(
-            model_name=model_name,
-        )
+        embedding_backend = _FastembedEmbeddingBackend(model_name=model_name, cache_dir=cache_dir, threads=threads)
         _FastembedEmbeddingBackendFactory._instances[embedding_backend_id] = embedding_backend
         return embedding_backend
 
@@ -34,8 +34,10 @@ class _FastembedEmbeddingBackend:
     def __init__(
         self,
         model_name: str,
+        cache_dir: Optional[str] = None,
+        threads: Optional[int] = None,
     ):
-        self.model = TextEmbedding(model_name=model_name)
+        self.model = TextEmbedding(model_name=model_name, cache_dir=cache_dir, threads=threads)
 
     def embed(self, data: List[List[str]], **kwargs) -> List[List[float]]:
         # the embed method returns a Iterable[np.ndarray], so we convert it to a list of lists

integrations/fastembed/src/haystack_integrations/components/embedders/fastembed/fastembed_document_embedder.py

@@ -53,6 +53,8 @@ class FastembedDocumentEmbedder:
     def __init__(
         self,
         model: str = "BAAI/bge-small-en-v1.5",
+        cache_dir: Optional[str] = None,
+        threads: Optional[int] = None,
         prefix: str = "",
         suffix: str = "",
         batch_size: int = 256,
@@ -66,6 +68,10 @@ def __init__(
 
         :param model: Local path or name of the model in Hugging Face's model hub,
             such as ``'BAAI/bge-small-en-v1.5'``.
+        :param cache_dir (str, optional): The path to the cache directory.
+                Can be set using the `FASTEMBED_CACHE_PATH` env variable.
+                Defaults to `fastembed_cache` in the system's temp directory.
+        :param threads (int, optional): The number of threads single onnxruntime session can use. Defaults to None.
         :param prefix: A string to add to the beginning of each text.
         :param suffix: A string to add to the end of each text.
         :param batch_size: Number of strings to encode at once.
@@ -79,6 +85,8 @@ def __init__(
         """
 
         self.model_name = model
+        self.cache_dir = cache_dir
+        self.threads = threads
         self.prefix = prefix
         self.suffix = suffix
         self.batch_size = batch_size
@@ -94,6 +102,8 @@ def to_dict(self) -> Dict[str, Any]:
         return default_to_dict(
             self,
             model=self.model_name,
+            cache_dir=self.cache_dir,
+            threads=self.threads,
             prefix=self.prefix,
             suffix=self.suffix,
             batch_size=self.batch_size,
@@ -108,7 +118,9 @@ def warm_up(self):
         Load the embedding backend.
         """
         if not hasattr(self, "embedding_backend"):
-            self.embedding_backend = _FastembedEmbeddingBackendFactory.get_embedding_backend(model_name=self.model_name)
+            self.embedding_backend = _FastembedEmbeddingBackendFactory.get_embedding_backend(
+                model_name=self.model_name, cache_dir=self.cache_dir, threads=self.threads
+            )
 
     def _prepare_texts_to_embed(self, documents: List[Document]) -> List[str]:
         texts_to_embed = []

integrations/fastembed/src/haystack_integrations/components/embedders/fastembed/fastembed_text_embedder.py

@@ -31,6 +31,8 @@ class FastembedTextEmbedder:
     def __init__(
         self,
         model: str = "BAAI/bge-small-en-v1.5",
+        cache_dir: Optional[str] = None,
+        threads: Optional[int] = None,
         prefix: str = "",
         suffix: str = "",
         batch_size: int = 256,
@@ -42,6 +44,10 @@ def __init__(
 
         :param model: Local path or name of the model in Fastembed's model hub,
             such as ``'BAAI/bge-small-en-v1.5'``.
+        :param cache_dir (str, optional): The path to the cache directory.
+                Can be set using the `FASTEMBED_CACHE_PATH` env variable.
+                Defaults to `fastembed_cache` in the system's temp directory.
+        :param threads (int, optional): The number of threads single onnxruntime session can use. Defaults to None.
         :param batch_size: Number of strings to encode at once.
         :param prefix: A string to add to the beginning of each text.
         :param suffix: A string to add to the end of each text.
@@ -52,9 +58,9 @@ def __init__(
                 If None, don't use data-parallel processing, use default onnxruntime threading instead.
         """
 
-        # TODO add parallel
-
         self.model_name = model
+        self.cache_dir = cache_dir
+        self.threads = threads
         self.prefix = prefix
         self.suffix = suffix
         self.batch_size = batch_size
@@ -68,6 +74,8 @@ def to_dict(self) -> Dict[str, Any]:
         return default_to_dict(
             self,
             model=self.model_name,
+            cache_dir=self.cache_dir,
+            threads=self.threads,
             prefix=self.prefix,
             suffix=self.suffix,
             batch_size=self.batch_size,
@@ -80,7 +88,9 @@ def warm_up(self):
         Load the embedding backend.
         """
         if not hasattr(self, "embedding_backend"):
-            self.embedding_backend = _FastembedEmbeddingBackendFactory.get_embedding_backend(model_name=self.model_name)
+            self.embedding_backend = _FastembedEmbeddingBackendFactory.get_embedding_backend(
+                model_name=self.model_name, cache_dir=self.cache_dir, threads=self.threads
+            )
 
     @component.output_types(embedding=List[float])
     def run(self, text: str):

integrations/fastembed/tests/test_fastembed_backend.py

@@ -8,7 +8,9 @@
 @patch("haystack_integrations.components.embedders.fastembed.embedding_backend.fastembed_backend.TextEmbedding")
 def test_factory_behavior(mock_instructor):  # noqa: ARG001
     embedding_backend = _FastembedEmbeddingBackendFactory.get_embedding_backend(model_name="BAAI/bge-small-en-v1.5")
-    same_embedding_backend = _FastembedEmbeddingBackendFactory.get_embedding_backend("BAAI/bge-small-en-v1.5")
+    same_embedding_backend = _FastembedEmbeddingBackendFactory.get_embedding_backend(
+        model_name="BAAI/bge-small-en-v1.5", cache_dir=None, threads=None
+    )
     another_embedding_backend = _FastembedEmbeddingBackendFactory.get_embedding_backend(
         model_name="BAAI/bge-base-en-v1.5"
     )
@@ -25,9 +27,7 @@ def test_model_initialization(mock_instructor):
     _FastembedEmbeddingBackendFactory.get_embedding_backend(
         model_name="BAAI/bge-small-en-v1.5",
     )
-    mock_instructor.assert_called_once_with(
-        model_name="BAAI/bge-small-en-v1.5",
-    )
+    mock_instructor.assert_called_once_with(model_name="BAAI/bge-small-en-v1.5", cache_dir=None, threads=None)
     # restore the factory state
     _FastembedEmbeddingBackendFactory._instances = {}
 

integrations/fastembed/tests/test_fastembed_document_embedder.py

@@ -15,6 +15,8 @@ def test_init_default(self):
         """
         embedder = FastembedDocumentEmbedder(model="BAAI/bge-small-en-v1.5")
         assert embedder.model_name == "BAAI/bge-small-en-v1.5"
+        assert embedder.cache_dir is None
+        assert embedder.threads is None
         assert embedder.prefix == ""
         assert embedder.suffix == ""
         assert embedder.batch_size == 256
@@ -29,6 +31,8 @@ def test_init_with_parameters(self):
         """
         embedder = FastembedDocumentEmbedder(
             model="BAAI/bge-small-en-v1.5",
+            cache_dir="fake_dir",
+            threads=2,
             prefix="prefix",
             suffix="suffix",
             batch_size=64,
@@ -38,6 +42,8 @@ def test_init_with_parameters(self):
             embedding_separator=" | ",
         )
         assert embedder.model_name == "BAAI/bge-small-en-v1.5"
+        assert embedder.cache_dir == "fake_dir"
+        assert embedder.threads == 2
         assert embedder.prefix == "prefix"
         assert embedder.suffix == "suffix"
         assert embedder.batch_size == 64
@@ -56,6 +62,8 @@ def test_to_dict(self):
             "type": "haystack_integrations.components.embedders.fastembed.fastembed_document_embedder.FastembedDocumentEmbedder",  #  noqa
             "init_parameters": {
                 "model": "BAAI/bge-small-en-v1.5",
+                "cache_dir": None,
+                "threads": None,
                 "prefix": "",
                 "suffix": "",
                 "batch_size": 256,
@@ -72,6 +80,8 @@ def test_to_dict_with_custom_init_parameters(self):
         """
         embedder = FastembedDocumentEmbedder(
             model="BAAI/bge-small-en-v1.5",
+            cache_dir="fake_dir",
+            threads=2,
             prefix="prefix",
             suffix="suffix",
             batch_size=64,
@@ -85,6 +95,8 @@ def test_to_dict_with_custom_init_parameters(self):
             "type": "haystack_integrations.components.embedders.fastembed.fastembed_document_embedder.FastembedDocumentEmbedder",  #  noqa
             "init_parameters": {
                 "model": "BAAI/bge-small-en-v1.5",
+                "cache_dir": "fake_dir",
+                "threads": 2,
                 "prefix": "prefix",
                 "suffix": "suffix",
                 "batch_size": 64,
@@ -103,6 +115,8 @@ def test_from_dict(self):
             "type": "haystack_integrations.components.embedders.fastembed.fastembed_document_embedder.FastembedDocumentEmbedder",  #  noqa
             "init_parameters": {
                 "model": "BAAI/bge-small-en-v1.5",
+                "cache_dir": None,
+                "threads": None,
                 "prefix": "",
                 "suffix": "",
                 "batch_size": 256,
@@ -114,6 +128,8 @@ def test_from_dict(self):
         }
         embedder = default_from_dict(FastembedDocumentEmbedder, embedder_dict)
         assert embedder.model_name == "BAAI/bge-small-en-v1.5"
+        assert embedder.cache_dir is None
+        assert embedder.threads is None
         assert embedder.prefix == ""
         assert embedder.suffix == ""
         assert embedder.batch_size == 256
@@ -130,6 +146,8 @@ def test_from_dict_with_custom_init_parameters(self):
             "type": "haystack_integrations.components.embedders.fastembed.fastembed_document_embedder.FastembedDocumentEmbedder",  #  noqa
             "init_parameters": {
                 "model": "BAAI/bge-small-en-v1.5",
+                "cache_dir": "fake_dir",
+                "threads": 2,
                 "prefix": "prefix",
                 "suffix": "suffix",
                 "batch_size": 64,
@@ -141,6 +159,8 @@ def test_from_dict_with_custom_init_parameters(self):
         }
         embedder = default_from_dict(FastembedDocumentEmbedder, embedder_dict)
         assert embedder.model_name == "BAAI/bge-small-en-v1.5"
+        assert embedder.cache_dir == "fake_dir"
+        assert embedder.threads == 2
         assert embedder.prefix == "prefix"
         assert embedder.suffix == "suffix"
         assert embedder.batch_size == 64
@@ -160,7 +180,7 @@ def test_warmup(self, mocked_factory):
         mocked_factory.get_embedding_backend.assert_not_called()
         embedder.warm_up()
         mocked_factory.get_embedding_backend.assert_called_once_with(
-            model_name="BAAI/bge-small-en-v1.5",
+            model_name="BAAI/bge-small-en-v1.5", cache_dir=None, threads=None
         )
 
     @patch(

integrations/fastembed/tests/test_fastembed_text_embedder.py

@@ -15,6 +15,8 @@ def test_init_default(self):
         """
         embedder = FastembedTextEmbedder(model="BAAI/bge-small-en-v1.5")
         assert embedder.model_name == "BAAI/bge-small-en-v1.5"
+        assert embedder.cache_dir is None
+        assert embedder.threads is None
         assert embedder.prefix == ""
         assert embedder.suffix == ""
         assert embedder.batch_size == 256
@@ -27,13 +29,17 @@ def test_init_with_parameters(self):
         """
         embedder = FastembedTextEmbedder(
             model="BAAI/bge-small-en-v1.5",
+            cache_dir="fake_dir",
+            threads=2,
             prefix="prefix",
             suffix="suffix",
             batch_size=64,
             progress_bar=False,
             parallel=1,
         )
         assert embedder.model_name == "BAAI/bge-small-en-v1.5"
+        assert embedder.cache_dir == "fake_dir"
+        assert embedder.threads == 2
         assert embedder.prefix == "prefix"
         assert embedder.suffix == "suffix"
         assert embedder.batch_size == 64
@@ -50,6 +56,8 @@ def test_to_dict(self):
             "type": "haystack_integrations.components.embedders.fastembed.fastembed_text_embedder.FastembedTextEmbedder",  # noqa
             "init_parameters": {
                 "model": "BAAI/bge-small-en-v1.5",
+                "cache_dir": None,
+                "threads": None,
                 "prefix": "",
                 "suffix": "",
                 "batch_size": 256,
@@ -64,6 +72,8 @@ def test_to_dict_with_custom_init_parameters(self):
         """
         embedder = FastembedTextEmbedder(
             model="BAAI/bge-small-en-v1.5",
+            cache_dir="fake_dir",
+            threads=2,
             prefix="prefix",
             suffix="suffix",
             batch_size=64,
@@ -75,6 +85,8 @@ def test_to_dict_with_custom_init_parameters(self):
             "type": "haystack_integrations.components.embedders.fastembed.fastembed_text_embedder.FastembedTextEmbedder",  # noqa
             "init_parameters": {
                 "model": "BAAI/bge-small-en-v1.5",
+                "cache_dir": "fake_dir",
+                "threads": 2,
                 "prefix": "prefix",
                 "suffix": "suffix",
                 "batch_size": 64,
@@ -91,6 +103,8 @@ def test_from_dict(self):
             "type": "haystack_integrations.components.embedders.fastembed.fastembed_text_embedder.FastembedTextEmbedder",  # noqa
             "init_parameters": {
                 "model": "BAAI/bge-small-en-v1.5",
+                "cache_dir": None,
+                "threads": None,
                 "prefix": "",
                 "suffix": "",
                 "batch_size": 256,
@@ -100,6 +114,8 @@ def test_from_dict(self):
         }
         embedder = default_from_dict(FastembedTextEmbedder, embedder_dict)
         assert embedder.model_name == "BAAI/bge-small-en-v1.5"
+        assert embedder.cache_dir is None
+        assert embedder.threads is None
         assert embedder.prefix == ""
         assert embedder.suffix == ""
         assert embedder.batch_size == 256
@@ -114,6 +130,8 @@ def test_from_dict_with_custom_init_parameters(self):
             "type": "haystack_integrations.components.embedders.fastembed.fastembed_text_embedder.FastembedTextEmbedder",  # noqa
             "init_parameters": {
                 "model": "BAAI/bge-small-en-v1.5",
+                "cache_dir": "fake_dir",
+                "threads": 2,
                 "prefix": "prefix",
                 "suffix": "suffix",
                 "batch_size": 64,
@@ -123,6 +141,8 @@ def test_from_dict_with_custom_init_parameters(self):
         }
         embedder = default_from_dict(FastembedTextEmbedder, embedder_dict)
         assert embedder.model_name == "BAAI/bge-small-en-v1.5"
+        assert embedder.cache_dir == "fake_dir"
+        assert embedder.threads == 2
         assert embedder.prefix == "prefix"
         assert embedder.suffix == "suffix"
         assert embedder.batch_size == 64
@@ -139,7 +159,9 @@ def test_warmup(self, mocked_factory):
         embedder = FastembedTextEmbedder(model="BAAI/bge-small-en-v1.5")
         mocked_factory.get_embedding_backend.assert_not_called()
         embedder.warm_up()
-        mocked_factory.get_embedding_backend.assert_called_once_with(model_name="BAAI/bge-small-en-v1.5")
+        mocked_factory.get_embedding_backend.assert_called_once_with(
+            model_name="BAAI/bge-small-en-v1.5", cache_dir=None, threads=None
+        )
 
     @patch(
         "haystack_integrations.components.embedders.fastembed.fastembed_text_embedder._FastembedEmbeddingBackendFactory"