Updated test suite for explainability & provenance (#696)

* Provenance tests

* Embeddings tests

* Test librarian

* Test triples stream

* Test concurrency

* Entity centric graph writes

* Agent tool service tests

* Structured data tests

* RDF tests

* Addition LLM tests

* Reliability tests

tests/unit/test_embeddings/test_embeddings_client.py

@@ -0,0 +1,109 @@
+"""
+Tests for EmbeddingsClient — the client interface for batch embeddings.
+"""
+
+import pytest
+from unittest.mock import AsyncMock, MagicMock
+
+from trustgraph.base.embeddings_client import EmbeddingsClient
+from trustgraph.schema import EmbeddingsRequest, EmbeddingsResponse, Error
+
+
+class TestEmbeddingsClient:
+
+    @pytest.mark.asyncio
+    async def test_embed_sends_request_and_returns_vectors(self):
+        """embed() should send an EmbeddingsRequest and return vectors."""
+        client = EmbeddingsClient.__new__(EmbeddingsClient)
+        client.request = AsyncMock(return_value=EmbeddingsResponse(
+            error=None,
+            vectors=[[0.1, 0.2], [0.3, 0.4]],
+        ))
+
+        result = await client.embed(texts=["hello", "world"])
+
+        assert result == [[0.1, 0.2], [0.3, 0.4]]
+        client.request.assert_called_once()
+        req = client.request.call_args[0][0]
+        assert isinstance(req, EmbeddingsRequest)
+        assert req.texts == ["hello", "world"]
+
+    @pytest.mark.asyncio
+    async def test_embed_single_text(self):
+        """embed() should work with a single text."""
+        client = EmbeddingsClient.__new__(EmbeddingsClient)
+        client.request = AsyncMock(return_value=EmbeddingsResponse(
+            error=None,
+            vectors=[[1.0, 2.0, 3.0]],
+        ))
+
+        result = await client.embed(texts=["single"])
+
+        assert result == [[1.0, 2.0, 3.0]]
+
+    @pytest.mark.asyncio
+    async def test_embed_raises_on_error_response(self):
+        """embed() should raise RuntimeError when response contains an error."""
+        client = EmbeddingsClient.__new__(EmbeddingsClient)
+        client.request = AsyncMock(return_value=EmbeddingsResponse(
+            error=Error(type="embeddings-error", message="model not found"),
+            vectors=[],
+        ))
+
+        with pytest.raises(RuntimeError, match="model not found"):
+            await client.embed(texts=["test"])
+
+    @pytest.mark.asyncio
+    async def test_embed_passes_timeout(self):
+        """embed() should pass timeout to the underlying request."""
+        client = EmbeddingsClient.__new__(EmbeddingsClient)
+        client.request = AsyncMock(return_value=EmbeddingsResponse(
+            error=None, vectors=[[0.0]],
+        ))
+
+        await client.embed(texts=["test"], timeout=60)
+
+        _, kwargs = client.request.call_args
+        assert kwargs["timeout"] == 60
+
+    @pytest.mark.asyncio
+    async def test_embed_default_timeout(self):
+        """embed() should use 300s default timeout."""
+        client = EmbeddingsClient.__new__(EmbeddingsClient)
+        client.request = AsyncMock(return_value=EmbeddingsResponse(
+            error=None, vectors=[[0.0]],
+        ))
+
+        await client.embed(texts=["test"])
+
+        _, kwargs = client.request.call_args
+        assert kwargs["timeout"] == 300
+
+    @pytest.mark.asyncio
+    async def test_embed_empty_texts(self):
+        """embed() with empty list should still make the request."""
+        client = EmbeddingsClient.__new__(EmbeddingsClient)
+        client.request = AsyncMock(return_value=EmbeddingsResponse(
+            error=None, vectors=[],
+        ))
+
+        result = await client.embed(texts=[])
+
+        assert result == []
+
+    @pytest.mark.asyncio
+    async def test_embed_large_batch(self):
+        """embed() should handle large batches."""
+        client = EmbeddingsClient.__new__(EmbeddingsClient)
+        n = 100
+        vectors = [[float(i)] for i in range(n)]
+        client.request = AsyncMock(return_value=EmbeddingsResponse(
+            error=None, vectors=vectors,
+        ))
+
+        texts = [f"text {i}" for i in range(n)]
+        result = await client.embed(texts=texts)
+
+        assert len(result) == n
+        req = client.request.call_args[0][0]
+        assert len(req.texts) == n