[Mem0] Update dependencies and make the package lighter (#1708)

Co-authored-by: Dev-Khant <devkhant24@gmail.com>

mem0/embeddings/azure_openai.py

@@ -6,17 +6,18 @@ from openai import AzureOpenAI
 from mem0.configs.embeddings.base import BaseEmbedderConfig
 from mem0.embeddings.base import EmbeddingBase
 
+
 class AzureOpenAIEmbedding(EmbeddingBase):
     def __init__(self, config: Optional[BaseEmbedderConfig] = None):
         super().__init__(config)
-        
+
         if self.config.model is None:
             self.config.model = "text-embedding-3-small"
         if self.config.embedding_dims is None:
             self.config.embedding_dims = 1536
-        
+
         api_key = os.getenv("AZURE_OPENAI_API_KEY") or self.config.api_key
-        self.client = AzureOpenAI(api_key=api_key) 
+        self.client = AzureOpenAI(api_key=api_key)
 
     def embed(self, text):
         """
@@ -30,10 +31,7 @@ class AzureOpenAIEmbedding(EmbeddingBase):
         """
         text = text.replace("\n", " ")
         return (
-            self.client.embeddings.create(
-                input=[text], 
-                model=self.config.model
-            )
+            self.client.embeddings.create(input=[text], model=self.config.model)
             .data[0]
             .embedding
         )

mem0/embeddings/base.py

@@ -3,18 +3,20 @@ from abc import ABC, abstractmethod
 
 from mem0.configs.embeddings.base import BaseEmbedderConfig
 
+
 class EmbeddingBase(ABC):
     """Initialized a base embedding class
 
     :param config: Embedding configuration option class, defaults to None
     :type config: Optional[BaseEmbedderConfig], optional
     """
+
     def __init__(self, config: Optional[BaseEmbedderConfig] = None):
         if config is None:
             self.config = BaseEmbedderConfig()
         else:
             self.config = config
-            
+
     @abstractmethod
     def embed(self, text):
         """

mem0/embeddings/configs.py

@@ -9,8 +9,7 @@ class EmbedderConfig(BaseModel):
         default="openai",
     )
     config: Optional[dict] = Field(
-        description="Configuration for the specific embedding model", 
-        default={}
+        description="Configuration for the specific embedding model", default={}
     )
 
     @field_validator("config")
@@ -20,4 +19,3 @@ class EmbedderConfig(BaseModel):
             return v
         else:
             raise ValueError(f"Unsupported embedding provider: {provider}")
-        

mem0/embeddings/huggingface.py

@@ -9,19 +9,15 @@ from mem0.embeddings.base import EmbeddingBase
 class HuggingFaceEmbedding(EmbeddingBase):
     def __init__(self, config: Optional[BaseEmbedderConfig] = None):
         super().__init__(config)
-        
+
         if self.config.model is None:
             self.config.model = "multi-qa-MiniLM-L6-cos-v1"
-  
-        self.model = SentenceTransformer(
-            self.config.model, 
-            **self.config.model_kwargs
-        )
+
+        self.model = SentenceTransformer(self.config.model, **self.config.model_kwargs)
 
         if self.config.embedding_dims is None:
             self.config.embedding_dims = self.model.get_sentence_embedding_dimension()
 
-    
     def embed(self, text):
         """
         Get the embedding for the given text using Hugging Face.

mem0/embeddings/ollama.py

@@ -6,18 +6,20 @@ from mem0.embeddings.base import EmbeddingBase
 try:
     from ollama import Client
 except ImportError:
-    raise ImportError("Ollama requires extra dependencies. Install with `pip install ollama`") from None
+    raise ImportError(
+        "Ollama requires extra dependencies. Install with `pip install ollama`"
+    ) from None
 
 
 class OllamaEmbedding(EmbeddingBase):
     def __init__(self, config: Optional[BaseEmbedderConfig] = None):
         super().__init__(config)
-    
+
         if not self.config.model:
-            self.config.model="nomic-embed-text"
+            self.config.model = "nomic-embed-text"
         if not self.config.embedding_dims:
-            self.config.embedding_dims=512
-            
+            self.config.embedding_dims = 512
+
         self.client = Client(host=self.config.ollama_base_url)
         self._ensure_model_exists()
 

mem0/embeddings/openai.py

@@ -6,10 +6,11 @@ from openai import OpenAI
 from mem0.configs.embeddings.base import BaseEmbedderConfig
 from mem0.embeddings.base import EmbeddingBase
 
+
 class OpenAIEmbedding(EmbeddingBase):
     def __init__(self, config: Optional[BaseEmbedderConfig] = None):
         super().__init__(config)
-    
+
         self.config.model = self.config.model or "text-embedding-3-small"
         self.config.embedding_dims = self.config.embedding_dims or 1536
 
@@ -28,10 +29,7 @@ class OpenAIEmbedding(EmbeddingBase):
         """
         text = text.replace("\n", " ")
         return (
-            self.client.embeddings.create(
-                input=[text], 
-                model=self.config.model
-            )
+            self.client.embeddings.create(input=[text], model=self.config.model)
             .data[0]
             .embedding
         )