feat(embeddings): add native embed_batch to OllamaEmbedding (#5415)

Co-authored-by: Kartik <kartik.labhshetwar@mem0.ai>

mem0/embeddings/ollama.py

@@ -63,3 +63,13 @@ class OllamaEmbedding(EmbeddingBase):
         if not embeddings:
             raise ValueError(f"Ollama embed() returned no embeddings for model '{self.config.model}'")
         return embeddings[0]
+
+    def embed_batch(self, texts, memory_action="add"):
+        """Embed multiple texts in a single Ollama API call."""
+        if not texts:
+            return []
+        response = self.client.embed(model=self.config.model, input=texts)
+        embeddings = response.get("embeddings") or []
+        if len(embeddings) != len(texts):
+            raise ValueError(f"Ollama embed() returned {len(embeddings)} embeddings for {len(texts)} texts using model '{self.config.model}'")
+        return embeddings

tests/embeddings/test_ollama_embeddings.py

@@ -60,3 +60,37 @@ def test_embed_empty_response_raises(mock_ollama_client):
 
     with pytest.raises(ValueError, match="returned no embeddings"):
         embedder.embed("some text")
+
+
+def test_embed_batch_single_call(mock_ollama_client):
+    config = BaseEmbedderConfig(model="nomic-embed-text", embedding_dims=512)
+    embedder = OllamaEmbedding(config)
+
+    mock_response = {"embeddings": [[0.1, 0.2, 0.3], [0.4, 0.5, 0.6], [0.7, 0.8, 0.9]]}
+    mock_ollama_client.embed.return_value = mock_response
+
+    texts = ["First text.", "Second text.", "Third text."]
+    embeddings = embedder.embed_batch(texts)
+
+    mock_ollama_client.embed.assert_called_once_with(model="nomic-embed-text", input=texts)
+    assert embeddings == [[0.1, 0.2, 0.3], [0.4, 0.5, 0.6], [0.7, 0.8, 0.9]]
+
+
+def test_embed_batch_empty_list(mock_ollama_client):
+    config = BaseEmbedderConfig(model="nomic-embed-text", embedding_dims=512)
+    embedder = OllamaEmbedding(config)
+
+    result = embedder.embed_batch([])
+
+    assert result == []
+    mock_ollama_client.embed.assert_not_called()
+
+
+def test_embed_batch_count_mismatch_raises(mock_ollama_client):
+    config = BaseEmbedderConfig(model="nomic-embed-text", embedding_dims=512)
+    embedder = OllamaEmbedding(config)
+
+    mock_ollama_client.embed.return_value = {"embeddings": [[0.1, 0.2, 0.3]]}
+
+    with pytest.raises(ValueError, match="returned 1 embeddings for 2 texts"):
+        embedder.embed_batch(["first text", "second text"])