comm - modules transfer

pkgs/community/pyproject.toml

@@ -32,7 +32,7 @@ pygithub = "*"
 python-dotenv = "*"
 qrcode = "*"
 redis = "^4.0"
-scikit-learn="^1.4.2"
+#scikit-learn="^1.4.2"
 swarmauri = "==0.5.2"
 textstat = "*"
 transformers = ">=4.45.0"

pkgs/swarmauri/swarmauri/vector_stores/concrete/Doc2VecVectorStore.py → pkgs/community/swarmauri_community/vector_stores/Doc2VecVectorStore.py

@@ -1,8 +1,7 @@
 from typing import List, Union, Literal
-from pydantic import PrivateAttr
 
 from swarmauri.documents.concrete.Document import Document
-from swarmauri.embeddings.concrete.Doc2VecEmbedding import Doc2VecEmbedding
+from swarmauri_community.embeddings.concrete.Doc2VecEmbedding import Doc2VecEmbedding
 from swarmauri.distances.concrete.CosineDistance import CosineDistance
 from swarmauri.vector_stores.base.VectorStoreBase import VectorStoreBase
 from swarmauri.vector_stores.base.VectorStoreRetrieveMixin import (

pkgs/swarmauri/swarmauri/vector_stores/concrete/MlmVectorStore.py → pkgs/community/swarmauri_community/vector_stores/MlmVectorStore.py

@@ -1,6 +1,6 @@
 from typing import List, Union, Literal
 from swarmauri.documents.concrete.Document import Document
-from swarmauri.embeddings.concrete.MlmEmbedding import MlmEmbedding
+from swarmauri_community.embeddings.concrete.MlmEmbedding import MlmEmbedding
 from swarmauri.distances.concrete.CosineDistance import CosineDistance
 
 from swarmauri.vector_stores.base.VectorStoreBase import VectorStoreBase

pkgs/swarmauri/tests/unit/embeddings/Doc2VecEmbedding_unit_test.py → pkgs/community/tests/unit/embeddings/Doc2VecEmbedding_unit_test.py

@@ -1,5 +1,5 @@
 import pytest
-from swarmauri.embeddings.concrete.Doc2VecEmbedding import Doc2VecEmbedding
+from swarmauri_community.embeddings.concrete.Doc2VecEmbedding import Doc2VecEmbedding
 
 @pytest.mark.unit
 def test_ubc_resource():

pkgs/swarmauri/tests/unit/embeddings/MlmEmbedding_unit_test.py → pkgs/community/tests/unit/embeddings/MlmEmbedding_unit_test.py

@@ -1,5 +1,5 @@
 import pytest
-from swarmauri.embeddings.concrete.MlmEmbedding import MlmEmbedding
+from swarmauri_community.embeddings.concrete.MlmEmbedding import MlmEmbedding
 
 @pytest.mark.unit
 def test_ubc_resource():

pkgs/swarmauri/tests/unit/parsers/TextBlobNounParser_unit_test.py → pkgs/community/tests/unit/parsers/TextBlobNounParser_unit_test.py

@@ -1,5 +1,5 @@
 import pytest
-from swarmauri.parsers.concrete.TextBlobNounParser import TextBlobNounParser as Parser
+from swarmauri_community.parsers.concrete.TextBlobNounParser import TextBlobNounParser as Parser
 
 
 def setup_module(module):

pkgs/swarmauri/tests/unit/parsers/TextBlobSentenceParser_unit_test.py → pkgs/community/tests/unit/parsers/TextBlobSentenceParser_unit_test.py

@@ -1,5 +1,5 @@
 import pytest
-from swarmauri.parsers.concrete.TextBlobSentenceParser import TextBlobSentenceParser as Parser
+from swarmauri_community.parsers.concrete.TextBlobSentenceParser import TextBlobSentenceParser as Parser
 
 @pytest.mark.unit
 def test_ubc_resource():

pkgs/swarmauri/tests/unit/tools/TextLength_unit_test.py → pkgs/community/tests/unit/tools/TextLength_unit_test.py

@@ -1,5 +1,5 @@
 import pytest
-from swarmauri.tools.concrete import TextLengthTool as Tool
+from swarmauri_community.tools.concrete import TextLengthTool as Tool
 
 @pytest.mark.unit
 def test_ubc_resource():

pkgs/swarmauri/tests/unit/vector_stores/Doc2VecVectorStore_unit_test.py → pkgs/community/tests/unit/vector_stores/Doc2VecVectorStore_unit_test.py

@@ -1,6 +1,6 @@
 import pytest
 from swarmauri.documents.concrete.Document import Document
-from swarmauri.vector_stores.concrete.Doc2VecVectorStore import Doc2VecVectorStore
+from swarmauri_community.vector_stores.Doc2VecVectorStore import Doc2VecVectorStore
 
 
 @pytest.mark.unit

pkgs/swarmauri/tests/unit/vector_stores/MlmVectorStore_unit_test.py → pkgs/community/tests/unit/vector_stores/MlmVectorStore_unit_test.py

@@ -1,6 +1,6 @@
 import pytest
 from swarmauri.documents.concrete.Document import Document
-from swarmauri.vector_stores.concrete.MlmVectorStore import MlmVectorStore
+from swarmauri_community.vector_stores.MlmVectorStore import MlmVectorStore
 
 
 @pytest.mark.unit

pkgs/swarmauri/pyproject.toml

@@ -34,18 +34,18 @@ aiohttp = { version = "^3.10.10", optional = true }
 #fal-client = { version = ">=0.5.0", optional = true }
 #google-generativeai = { version = "^0.8.3", optional = true }
 #openai = { version = "^1.52.0", optional = true }
-nltk = { version = "^3.9.1", optional = true }
-textblob = { version = "^0.18.0", optional = true }
+#nltk = { version = "^3.9.1", optional = true }
+#textblob = { version = "^0.18.0", optional = true }
 yake = { version = "==0.4.8", optional = true }
 beautifulsoup4 = { version = "04.12.3", optional = true }
-gensim = { version = "==4.3.3", optional = true }
+#gensim = { version = "==4.3.3", optional = true }
 scipy = { version = ">=1.7.0,<1.14.0", optional = true }
-scikit-learn = { version = "^1.4.2", optional = true }
-spacy = { version = ">=3.0.0,<=3.8.2", optional = true }
-transformers = { version = "^4.45.0", optional = true }
-torch = { version = "^2.5.0", optional = true }
-keras = { version = ">=3.2.0", optional = true }
-tf-keras = { version = ">=2.16.0", optional = true }
+#scikit-learn = { version = "^1.4.2", optional = true }
+#spacy = { version = ">=3.0.0,<=3.8.2", optional = true }
+#transformers = { version = "^4.45.0", optional = true }
+#torch = { version = "^2.5.0", optional = true }
+#keras = { version = ">=3.2.0", optional = true }
+#tf-keras = { version = ">=2.16.0", optional = true }
 matplotlib = { version = ">=3.9.2", optional = true }
 
 [tool.poetry.extras]
@@ -54,24 +54,25 @@ io = ["aiofiles", "aiohttp"]
 #llms = ["cohere", "mistralai", "fal-client", "google-generativeai", "openai"]
 nlp = ["nltk", "textblob", "yake"]
 nlp_tools = ["beautifulsoup4"]
-ml_toolkits = ["gensim", "scipy", "scikit-learn"]
-spacy = ["spacy"]
-transformers = ["transformers"]
-torch = ["torch"]
-tensorflow = ["keras", "tf-keras"]
+#ml_toolkits = ["gensim", "scipy", "scikit-learn"]
+#spacy = ["spacy"]
+#transformers = ["transformers"]
+#torch = ["torch"]
+#tensorflow = ["keras", "tf-keras"]
 visualization = ["matplotlib"]
 
 # Full option to install all extras
 full = [
     "aiofiles", "aiohttp",
     #"cohere", "mistralai", "fal-client", "google-generativeai", "openai",
-    "nltk", "textblob", "yake",
+    #"nltk", "textblob", 
+    "yake",
     "beautifulsoup4",
-    "gensim", "scipy", "scikit-learn",
-    "spacy",
-    "transformers",
-    "torch",
-    "keras", "tf-keras",
+    #"gensim", "scipy", "scikit-learn",
+    #"spacy",
+    #"transformers",
+    #"torch",
+    #"keras", "tf-keras",
     "matplotlib"
 ]
 

pkgs/swarmauri/swarmauri/embeddings/concrete/__init__.py

@@ -11,20 +11,20 @@ def _lazy_import(module_name, module_description=None):
         return None
 
 # Lazy loading of embeddings with descriptive names
-Doc2VecEmbedding = _lazy_import("swarmauri.embeddings.concrete.Doc2VecEmbedding", "Doc2VecEmbedding")
+# Doc2VecEmbedding = _lazy_import("swarmauri.embeddings.concrete.Doc2VecEmbedding", "Doc2VecEmbedding")
 GeminiEmbedding = _lazy_import("swarmauri.embeddings.concrete.GeminiEmbedding", "GeminiEmbedding")
 MistralEmbedding = _lazy_import("swarmauri.embeddings.concrete.MistralEmbedding", "MistralEmbedding")
-MlmEmbedding = _lazy_import("swarmauri.embeddings.concrete.MlmEmbedding", "MlmEmbedding")
+# MlmEmbedding = _lazy_import("swarmauri.embeddings.concrete.MlmEmbedding", "MlmEmbedding")
 NmfEmbedding = _lazy_import("swarmauri.embeddings.concrete.NmfEmbedding", "NmfEmbedding")
 OpenAIEmbedding = _lazy_import("swarmauri.embeddings.concrete.OpenAIEmbedding", "OpenAIEmbedding")
 TfidfEmbedding = _lazy_import("swarmauri.embeddings.concrete.TfidfEmbedding", "TfidfEmbedding")
 
 # Adding lazy-loaded modules to __all__
 __all__ = [
-    "Doc2VecEmbedding",
+    # "Doc2VecEmbedding",
     "GeminiEmbedding",
     "MistralEmbedding",
-    "MlmEmbedding",
+    # "MlmEmbedding",
     "NmfEmbedding",
     "OpenAIEmbedding",
     "TfidfEmbedding",

pkgs/swarmauri/swarmauri/parsers/concrete/__init__.py

@@ -13,7 +13,7 @@ def _lazy_import(module_name, module_description=None):
 # List of parser names (file names without the ".py" extension)
 parser_files = [
     "BeautifulSoupElementParser",
-    "BERTEmbeddingParser",
+    # "BERTEmbeddingParser",
     "CSVParser",
     "EntityRecognitionParser",
     "HTMLTagStripParser",
@@ -23,8 +23,8 @@ def _lazy_import(module_name, module_description=None):
     "PhoneNumberExtractorParser",
     "PythonParser",
     "RegExParser",
-    "TextBlobNounParser",
-    "TextBlobSentenceParser",
+    # "TextBlobNounParser",
+    # "TextBlobSentenceParser",
     "URLExtractorParser",
     "XMLParser",
 ]

pkgs/swarmauri/swarmauri/vector_stores/concrete/__init__.py

@@ -12,8 +12,8 @@ def _lazy_import(module_name, module_description=None):
 
 # List of vector store names (file names without the ".py" extension)
 vector_store_files = [
-    "Doc2VecVectorStore",
-    "MlmVectorStore",
+    # "Doc2VecVectorStore",
+    # "MlmVectorStore",
     "SqliteVectorStore",
     "TfidfVectorStore",
 ]