fix(python): huggingface TEI auth, procedural-memory content handling, and proxy pip auto-install (#6947)

tests/embeddings/test_langchain_embeddings.py

@@ -0,0 +1,61 @@
+import pytest
+
+pytest.importorskip("langchain", reason="langchain is an optional extra")
+
+from langchain.embeddings.base import Embeddings  # noqa: E402
+
+from mem0.configs.embeddings.base import BaseEmbedderConfig  # noqa: E402
+from mem0.embeddings.langchain import LangchainEmbedding  # noqa: E402
+
+
+class DummyEmbeddings(Embeddings):
+    def __init__(self):
+        self.queries = []
+
+    def embed_documents(self, texts):
+        return [[0.1, 0.2, 0.3] for _ in texts]
+
+    def embed_query(self, text):
+        self.queries.append(text)
+        return [0.1, 0.2, 0.3]
+
+
+def test_missing_model_raises():
+    with pytest.raises(ValueError, match="`model` parameter is required"):
+        LangchainEmbedding(BaseEmbedderConfig())
+
+
+def test_model_that_is_not_an_embeddings_instance_raises():
+    with pytest.raises(ValueError, match="`model` must be an instance of Embeddings"):
+        LangchainEmbedding(BaseEmbedderConfig(model="text-embedding-3-small"))
+
+
+def test_configured_model_instance_is_kept():
+    model = DummyEmbeddings()
+
+    assert LangchainEmbedding(BaseEmbedderConfig(model=model)).langchain_model is model
+
+
+def test_embed_delegates_to_embed_query():
+    model = DummyEmbeddings()
+    embedder = LangchainEmbedding(BaseEmbedderConfig(model=model))
+
+    assert embedder.embed("hello", "add") == [0.1, 0.2, 0.3]
+    assert model.queries == ["hello"]
+
+
+def test_memory_action_never_reaches_the_model():
+    model = DummyEmbeddings()
+    embedder = LangchainEmbedding(BaseEmbedderConfig(model=model))
+
+    embedder.embed("hello", memory_action="add")
+
+    assert model.queries == ["hello"]
+
+
+def test_embed_batch_falls_back_to_sequential_embed():
+    model = DummyEmbeddings()
+    embedder = LangchainEmbedding(BaseEmbedderConfig(model=model))
+
+    assert embedder.embed_batch(["a", "b"]) == [[0.1, 0.2, 0.3], [0.1, 0.2, 0.3]]
+    assert model.queries == ["a", "b"]