perf(memory): keep embed model warm across turns (keep_alive 0 -> 5m)

Empirical A/B/C measurement against the live RTX 5050 Ollama stack
(qwen2.5:3b + nomic-embed-text) showed keep_alive=0 unloads the embed
model ~2s after every call, so each turn after a brief idle gap pays a
cold reload. VRAM is not the constraint (~4.4-4.7 GB free with both
models resident) and keep_alive=0 never evicted the chat model, so CPU
embedding (num_gpu=0) gave no benefit. A short positive keep_alive is
the fastest of the three: it keeps the ~0.3 GB embed model resident
across consecutive turns at negligible VRAM cost.

Add tests/test_embeddings.py covering the warm-across-turns behaviour.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

src/jarvis/memory/embeddings.py

@@ -6,11 +6,14 @@ def get_embedding(text: str, base_url: str, model: str, timeout_sec: float = 15.
     try:
         resp = requests.post(
             f"{base_url.rstrip('/')}/api/embeddings",
-            # keep_alive=0 unloads the embedding model right after the call so
+            # Short positive keep_alive keeps the embed model warm across the
-            # it does not sit resident in VRAM alongside the chat model. The
+            # consecutive turns of an active conversation. With keep_alive=0
-            # chat model is pinned separately (llm.py keep_alive=30m); only the
+            # Ollama unloads it ~2s after every call, so each turn after a brief
-            # actively-used chat model should stay loaded.
+            # idle gap pays a cold reload of the embed model. The embed model is
-            json={"model": model, "prompt": text, "keep_alive": 0},
+            # tiny (~0.3 GB) and coexists in VRAM with the chat model (pinned at
+            # keep_alive=30m in llm.py) with ample headroom, so holding it for a
+            # few minutes is effectively free and removes the per-turn reload.
+            json={"model": model, "prompt": text, "keep_alive": "5m"},
             timeout=timeout_sec,
         )
         resp.raise_for_status()

tests/test_embeddings.py

@@ -0,0 +1,52 @@
+"""Tests for the Ollama embedding client.
+
+Behaviour under test: the embedding request keeps the embed model warm across
+consecutive conversation turns. With ``keep_alive=0`` Ollama unloads the embed
+model ~2s after every call, so each turn after a short idle gap pays a cold
+reload. A short positive ``keep_alive`` keeps it resident between turns at a
+negligible VRAM cost (nomic-embed-text is ~0.3 GB).
+"""
+from __future__ import annotations
+
+from unittest.mock import MagicMock, patch
+
+from jarvis.memory.embeddings import get_embedding
+
+
+def _mock_response(vec):
+    resp = MagicMock()
+    resp.raise_for_status.return_value = None
+    resp.json.return_value = {"embedding": vec}
+    return resp
+
+
+def test_get_embedding_posts_to_embeddings_endpoint():
+    with patch("jarvis.memory.embeddings.requests") as mock_requests:
+        mock_requests.post.return_value = _mock_response([0.1, 0.2, 0.3])
+        vec = get_embedding("hello", "http://localhost:11434", "nomic-embed-text")
+
+    assert vec == [0.1, 0.2, 0.3]
+    args, kwargs = mock_requests.post.call_args
+    assert args[0].endswith("/api/embeddings")
+    assert kwargs["json"]["model"] == "nomic-embed-text"
+    assert kwargs["json"]["prompt"] == "hello"
+
+
+def test_get_embedding_keeps_model_warm_between_turns():
+    """The request must not unload the model after each call (keep_alive > 0)."""
+    with patch("jarvis.memory.embeddings.requests") as mock_requests:
+        mock_requests.post.return_value = _mock_response([0.0])
+        get_embedding("warm me", "http://localhost:11434", "nomic-embed-text")
+
+    _, kwargs = mock_requests.post.call_args
+    keep_alive = kwargs["json"].get("keep_alive")
+    # A falsy/zero keep_alive evicts the model immediately, forcing a cold
+    # reload on the next turn. Anything truthy positive keeps it resident.
+    assert keep_alive, f"embedding keep_alive should be a positive duration, got {keep_alive!r}"
+    assert keep_alive != 0
+
+
+def test_get_embedding_returns_none_on_error():
+    with patch("jarvis.memory.embeddings.requests") as mock_requests:
+        mock_requests.post.side_effect = RuntimeError("boom")
+        assert get_embedding("x", "http://localhost:11434", "nomic-embed-text") is None