Refactor dimensions handling in LiteLLMEmbeddingEngine

Remove dimensions initialization from constructor and add validation for dimensions if provided.

cognee/infrastructure/databases/vector/embeddings/LiteLLMEmbeddingEngine.py

@@ -68,7 +68,6 @@ class LiteLLMEmbeddingEngine(EmbeddingEngine):
         self.api_version = api_version
         self.provider = provider
         self.model = model
-        self.dimensions = dimensions
         self.max_completion_tokens = max_completion_tokens
         self.tokenizer = self.get_tokenizer()
         self.retry_count = 0
@@ -78,6 +77,11 @@ class LiteLLMEmbeddingEngine(EmbeddingEngine):
         if isinstance(enable_mocking, bool):
             enable_mocking = str(enable_mocking).lower()
         self.mock = enable_mocking in ("true", "1", "yes")
+        
+        if dimensions is not None:
+            if not isinstance(dimensions, int) or dimensions <= 0:
+                raise ValueError("dimensions must be a positive integer")
+        self.dimensions = dimensions
 
     @retry(
         stop=stop_after_delay(128),
@@ -111,13 +115,16 @@ class LiteLLMEmbeddingEngine(EmbeddingEngine):
                 return [data["embedding"] for data in response["data"]]
             else:
                 async with embedding_rate_limiter_context_manager():
+                    kwargs = {}
+                    if self.dimensions is not None:
+                        kwargs['dimensions'] = self.dimensions
                     response = await litellm.aembedding(
                         model=self.model,
                         input=text,
                         api_key=self.api_key,
                         api_base=self.endpoint,
                         api_version=self.api_version,
-                        dimensions=self.dimensions,
+                        **kwargs,
                     )
 
                 return [data["embedding"] for data in response.data]