feat: multi-entity state-update coordinator

chat/services/multi_state_update.py

@@ -0,0 +1,62 @@
+"""Multi-entity state-update coordinator (T40).
+
+Wraps single-pair compute_state_update to run state updates for ALL
+directed pairs of present entities. With 3 present entities (you, host,
+guest) that's 6 directed pairs. With 2 present (you, host) it's 2 pairs.
+
+Calls run sequentially to respect Featherless's 2-connection cap (the
+client-level semaphore would serialize them anyway, but doing it here
+keeps the failure surface clean — a hung pair doesn't queue behind
+itself).
+"""
+
+from __future__ import annotations
+
+from chat.llm.client import LLMClient
+from chat.services.state_update import StateUpdate, compute_state_update
+
+
+async def compute_state_updates_for_present(
+    client: LLMClient,
+    *,
+    classifier_model: str,
+    present_ids: list[str],
+    present_names: dict[str, str],
+    personas: dict[str, str],
+    prior_edges: dict[tuple[str, str], dict],
+    recent_dialogue: list[dict],
+    timeout_s: float = 30.0,
+) -> list[tuple[str, str, StateUpdate]]:
+    """Run compute_state_update for every directed pair (src != tgt) over
+    ``present_ids``. Returns list of ``(source_id, target_id, update)``
+    tuples in the natural iteration order over ``present_ids x present_ids``.
+
+    A single failing pair falls back to the schema-default StateUpdate
+    (zero deltas, empty facts) inside ``compute_state_update``; the batch
+    keeps going.
+    """
+    out: list[tuple[str, str, StateUpdate]] = []
+    for src in present_ids:
+        for tgt in present_ids:
+            if src == tgt:
+                continue
+            edge = prior_edges.get((src, tgt), {})
+            update = await compute_state_update(
+                client,
+                model=classifier_model,
+                source_id=src,
+                target_id=tgt,
+                source_name=present_names.get(src, src),
+                source_persona=personas.get(src, "") or "",
+                target_name=present_names.get(tgt, tgt),
+                prior_affinity=int(edge.get("affinity", 50)),
+                prior_trust=int(edge.get("trust", 50)),
+                prior_summary=edge.get("summary", "") or "",
+                recent_dialogue=recent_dialogue,
+                timeout_s=timeout_s,
+            )
+            out.append((src, tgt, update))
+    return out
+
+
+__all__ = ["compute_state_updates_for_present"]

tests/test_multi_state_update.py

@@ -0,0 +1,147 @@
+"""Multi-entity state-update coordinator (T40).
+
+Wraps the single-pair :func:`compute_state_update` to run state updates
+for ALL directed pairs of present entities. With 3 present entities
+(you, host, guest) that's 6 directed pairs; with 2 (you, host) it's 2.
+
+Calls run sequentially to respect Featherless's 2-connection cap.
+"""
+
+from __future__ import annotations
+
+import json
+
+import pytest
+
+from chat.llm.mock import MockLLMClient
+from chat.services.multi_state_update import compute_state_updates_for_present
+from chat.services.state_update import StateUpdate
+
+
+def _canned_update(affinity: int, trust: int, facts: list[str] | None = None) -> str:
+    return json.dumps(
+        {
+            "affinity_delta": affinity,
+            "trust_delta": trust,
+            "knowledge_facts": facts or [],
+        }
+    )
+
+
+@pytest.mark.asyncio
+async def test_two_entities_returns_two_updates():
+    """you + bot_a -> 2 directed pairs (you->bot_a, bot_a->you)."""
+    canned = [
+        _canned_update(2, 1, ["likes coffee"]),  # you -> bot_a
+        _canned_update(1, 0, ["greets warmly"]),  # bot_a -> you
+    ]
+    mock = MockLLMClient(canned=canned)
+
+    results = await compute_state_updates_for_present(
+        mock,
+        classifier_model="x",
+        present_ids=["you", "bot_a"],
+        present_names={"you": "Me", "bot_a": "BotA"},
+        personas={"you": "", "bot_a": "thoughtful"},
+        prior_edges={
+            ("you", "bot_a"): {"affinity": 50, "trust": 50, "summary": ""},
+            ("bot_a", "you"): {"affinity": 50, "trust": 50, "summary": ""},
+        },
+        recent_dialogue=[
+            {"speaker": "you", "text": "hi"},
+            {"speaker": "BotA", "text": "Hello!"},
+        ],
+    )
+
+    assert len(results) == 2
+    assert results[0][0] == "you"
+    assert results[0][1] == "bot_a"
+    assert isinstance(results[0][2], StateUpdate)
+    assert results[0][2].affinity_delta == 2
+    assert results[0][2].trust_delta == 1
+    assert results[0][2].knowledge_facts == ["likes coffee"]
+
+    assert results[1][0] == "bot_a"
+    assert results[1][1] == "you"
+    assert isinstance(results[1][2], StateUpdate)
+    assert results[1][2].affinity_delta == 1
+    assert results[1][2].trust_delta == 0
+    assert results[1][2].knowledge_facts == ["greets warmly"]
+
+
+@pytest.mark.asyncio
+async def test_three_entities_returns_six_updates():
+    """you + bot_a + bot_b -> 6 directed pairs (no self-pairs)."""
+    canned = [_canned_update(i, 0) for i in range(6)]
+    mock = MockLLMClient(canned=canned)
+
+    results = await compute_state_updates_for_present(
+        mock,
+        classifier_model="x",
+        present_ids=["you", "bot_a", "bot_b"],
+        present_names={"you": "Me", "bot_a": "BotA", "bot_b": "BotB"},
+        personas={"you": "", "bot_a": "thoughtful", "bot_b": "cheerful"},
+        prior_edges={},  # all default to 50/50/""
+        recent_dialogue=[{"speaker": "you", "text": "hello all"}],
+    )
+
+    assert len(results) == 6
+
+    pairs = [(src, tgt) for src, tgt, _ in results]
+    # No self-pairs.
+    assert all(src != tgt for src, tgt in pairs)
+    # All 6 directed combinations present.
+    expected = {
+        ("you", "bot_a"),
+        ("you", "bot_b"),
+        ("bot_a", "you"),
+        ("bot_a", "bot_b"),
+        ("bot_b", "you"),
+        ("bot_b", "bot_a"),
+    }
+    assert set(pairs) == expected
+    # Every entry is a StateUpdate.
+    assert all(isinstance(u, StateUpdate) for _, _, u in results)
+
+
+@pytest.mark.asyncio
+async def test_failure_in_one_pair_does_not_kill_batch():
+    """First pair fails all 3 classify retries -> default; second parses OK."""
+    canned = [
+        # Pair 1 (you -> bot_a): 3 malformed responses -> default StateUpdate.
+        "bad",
+        "still bad",
+        "nope",
+        # Pair 2 (bot_a -> you): valid JSON.
+        _canned_update(3, 2, ["was warm"]),
+    ]
+    mock = MockLLMClient(canned=canned)
+
+    results = await compute_state_updates_for_present(
+        mock,
+        classifier_model="x",
+        present_ids=["you", "bot_a"],
+        present_names={"you": "Me", "bot_a": "BotA"},
+        personas={"you": "", "bot_a": "thoughtful"},
+        prior_edges={
+            ("you", "bot_a"): {"affinity": 60, "trust": 40, "summary": "some prior"},
+            ("bot_a", "you"): {"affinity": 50, "trust": 50, "summary": ""},
+        },
+        recent_dialogue=[{"speaker": "you", "text": "hi"}],
+    )
+
+    assert len(results) == 2
+
+    # First pair: default (zero-delta) StateUpdate.
+    src1, tgt1, update1 = results[0]
+    assert (src1, tgt1) == ("you", "bot_a")
+    assert update1.affinity_delta == 0
+    assert update1.trust_delta == 0
+    assert update1.knowledge_facts == []
+
+    # Second pair: parsed valid JSON.
+    src2, tgt2, update2 = results[1]
+    assert (src2, tgt2) == ("bot_a", "you")
+    assert update2.affinity_delta == 3
+    assert update2.trust_delta == 2
+    assert update2.knowledge_facts == ["was warm"]