refactor: add support for Ollama embedding size definition

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

@@ -57,7 +57,7 @@ class OllamaEmbeddingEngine(EmbeddingEngine):
         model: Optional[str] = "avr/sfr-embedding-mistral:latest",
         dimensions: Optional[int] = 1024,
         max_completion_tokens: int = 512,
-        endpoint: Optional[str] = "http://localhost:11434/api/embeddings",
+        endpoint: Optional[str] = "http://localhost:11434/api/embed",
         huggingface_tokenizer: str = "Salesforce/SFR-Embedding-Mistral",
         batch_size: int = 100,
     ):
@@ -93,6 +93,10 @@ class OllamaEmbeddingEngine(EmbeddingEngine):
         if self.mock:
             return [[0.0] * self.dimensions for _ in text]
 
+        # Handle case when a single string is passed instead of a list
+        if not isinstance(text, list):
+            text = [text]
+
         embeddings = await asyncio.gather(*[self._get_embedding(prompt) for prompt in text])
         return embeddings
 
@@ -107,7 +111,12 @@ class OllamaEmbeddingEngine(EmbeddingEngine):
         """
         Internal method to call the Ollama embeddings endpoint for a single prompt.
         """
-        payload = {"model": self.model, "prompt": prompt, "input": prompt}
+        payload = {
+            "model": self.model,
+            "prompt": prompt,
+            "input": prompt,
+            "dimensions": self.dimensions,
+        }
 
         headers = {}
         api_key = os.getenv("LLM_API_KEY")