fix: B6 — memory injection moves to live-zone user-tail
PR-A2 locked the system prompt and routed Anthropic memory injection to the
latest non-frozen user turn. PR-B6 finishes the job: every provider handler
that auto-injects memory context now does so via the live-zone tail, and a
new MemoryMode enum makes the routing explicit and configurable.
What changed
------------
* New `MemoryMode` enum in `headroom/proxy/memory_handler.py` with two
values:
- `AUTO_TAIL` (default) — retrieval results auto-append to the latest
user message. The cache hot zone (system / instructions / frozen
prefix) is never mutated.
- `TOOL` — auto-injection is disabled entirely. The model must call
`memory_search` to retrieve. Memory is opt-in and visible.
* `MemoryConfig.mode: MemoryMode = MemoryMode.AUTO_TAIL` propagates into
`search_and_format_context`, which now short-circuits to `None` in `TOOL`
mode. This is the single chokepoint that gates every provider — Anthropic
/v1/messages, OpenAI /v1/chat/completions, OpenAI /v1/responses, and
Gemini all funnel through it, so flipping a deployment to tool mode does
not require auditing every handler.
* New `MemoryHandler._append_to_latest_user_tail(messages, context_text,
provider=..., frozen_message_count=...)` static helper provides the unified
tail-append entry point and dispatches to the existing provider-specific
helpers (`AnthropicHandlerMixin._append_context_to_latest_non_frozen_user_turn`
for Anthropic, `append_text_to_latest_user_chat_message` for OpenAI).
* Gemini handler swapped from auto-prepending memory as a system message
(the old P2-24 cache-hot-zone mutation pattern) to using
`_append_to_latest_user_tail(provider="openai")`.
* `ProxyConfig.memory_mode: Literal["auto_tail", "tool"] = "auto_tail"`
surfaces the mode for deployment configuration. Server constructs the
enum via `MemoryMode(config.memory_mode)` and raises loudly on unknown
values (no silent fallback).
* OpenAI Chat Completions, OpenAI Responses, and Anthropic handlers were
already routing to the live-zone tail via PR-A2/A3 — no code change
needed beyond inheriting the `TOOL`-mode skip from the chokepoint.
Tests
-----
* `tests/test_memory_auto_tail.py` (6 tests):
- `test_memory_appears_in_latest_user_message_tail` — Anthropic shape.
- `test_memory_appears_in_latest_user_message_tail_openai_shape` —
OpenAI string + list-content shapes.
- `test_memory_does_not_modify_system_or_tools` — system prompt and
tools list are never touched; frozen-prefix tail is a no-op.
- `test_same_query_byte_identical_across_runs` — two independent runs
with identical inputs produce byte-identical mutated message lists
(determinism gate).
- `test_default_mode_is_auto_tail` — fresh `MemoryConfig` defaults to
`AUTO_TAIL`.
- `test_unknown_provider_raises` — invalid provider strings raise
loudly per the no-silent-fallback policy.
* `tests/test_memory_tool_mode.py` (4 tests):
- `test_tool_mode_skips_auto_injection` — `search_and_format_context`
returns `None` and the backend is never queried.
- `test_tool_mode_skip_emits_structured_log` — skip emits the
`event=memory_mode_skip` log line for routing-decision auditability.
- `test_auto_tail_mode_does_query_backend` — inverse contrast pinning
down that AUTO_TAIL still works end-to-end while TOOL skips.
- `test_tool_mode_enum_value_is_stable` — string round-trip is pinned
so deployment configs do not drift on rename.
Determinism
-----------
Tests stub the backend with a fixed, ordered result set so the byte-identical
assertion isolates the tail-injection layer from upstream search non-
determinism. The vector-search layer itself (LocalBackend / HNSW) is
deterministic per-process for the same inputs but has thread-scheduling
variability across processes; per the realignment plan, request-time
determinism is guaranteed by the formatter and the tail-append helpers
(this PR's responsibility), and the backend layer's determinism stays
out-of-scope for B6.
Per-PR-B6 plan: REALIGNMENT/04-phase-B-live-zone.md.
2026-05-02 16:37:54 -07:00
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"""PR-B6: tests that MemoryMode.TOOL fully disables auto-injection.
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In Tool mode, the memory subsystem must be invisible to the prompt-construction
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path. The model can still call ``memory_search`` explicitly (the tool is
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registered through the existing tool-injection plumbing), but
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``search_and_format_context`` — the auto-injection chokepoint that returns
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text for the proxy to splice into the latest user turn — must return
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``None`` unconditionally.
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This is the load-bearing guarantee that lets us flip a deployment from
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``auto_tail`` to ``tool`` without auditing every handler.
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"""
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from __future__ import annotations
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import asyncio
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import logging
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from dataclasses import dataclass
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from typing import Any
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from headroom.proxy.memory_handler import MemoryConfig, MemoryHandler, MemoryMode
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@dataclass
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class _StubMemory:
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id: str
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content: str
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metadata: dict[str, Any]
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@dataclass
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class _StubResult:
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memory: _StubMemory
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score: float
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related_entities: list[str]
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class _LoudBackend:
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"""Backend that fails the test if it is queried.
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Tool mode must short-circuit *before* the backend is touched. If
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``search_memories`` runs, the chokepoint is broken.
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"""
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def __init__(self) -> None:
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self.calls = 0
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async def search_memories(self, **_: Any) -> list[_StubResult]:
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self.calls += 1
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# Return data that would be appended in AutoTail mode — if Tool
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# mode incorrectly auto-injects we can detect via the text content.
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return [
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_StubResult(
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memory=_StubMemory(
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id="leaked_001",
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content="LEAK: this content must not appear in TOOL mode",
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metadata={},
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),
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score=0.99,
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related_entities=[],
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)
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]
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def _build_tool_mode_handler() -> tuple[MemoryHandler, _LoudBackend]:
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config = MemoryConfig(
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enabled=True,
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backend="local",
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inject_context=True,
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inject_tools=True,
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top_k=5,
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min_similarity=0.3,
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mode=MemoryMode.TOOL,
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)
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handler = MemoryHandler(config)
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backend = _LoudBackend()
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handler._backend = backend
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handler._initialized = True
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return handler, backend
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def test_tool_mode_skips_auto_injection() -> None:
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"""``search_and_format_context`` must return ``None`` in TOOL mode.
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This is the single chokepoint enforcement: every provider handler
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(Anthropic /v1/messages, OpenAI /v1/chat/completions and /v1/responses,
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Gemini) calls this method. If it returns ``None``, no tail-injection
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happens anywhere — without per-handler audit.
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"""
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handler, backend = _build_tool_mode_handler()
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messages = [
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{"role": "user", "content": "What do you remember about me?"},
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]
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result = asyncio.run(handler.search_and_format_context("alpha", messages))
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assert result is None, "TOOL mode must skip auto-injection (return None)"
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# Defense-in-depth: the backend must NOT have been queried. If it had
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# been, we would have wasted compute and burned cache lines reading
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# data that would never be used.
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assert backend.calls == 0, (
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f"TOOL mode must not even query the backend; saw {backend.calls} calls"
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)
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def test_tool_mode_skip_emits_structured_log(caplog: Any) -> None:
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"""The skip must emit a structured ``event=memory_mode_skip`` log line.
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Realignment build constraint: every cache-affecting decision is logged
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in the ``event=foo key=val`` style so operators can audit routing.
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2026-05-02 17:05:58 -07:00
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NOTE: caplog captures at the root logger via propagation. When other
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tests in the suite trigger proxy startup, ``_setup_file_logging`` sets
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``headroom.propagate=False`` and attaches a file handler. The conftest
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autouse reset is fragile against fixture ordering, so we attach
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``caplog.handler`` directly to the target logger here. That way the
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capture works regardless of propagation state.
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fix: B6 — memory injection moves to live-zone user-tail
PR-A2 locked the system prompt and routed Anthropic memory injection to the
latest non-frozen user turn. PR-B6 finishes the job: every provider handler
that auto-injects memory context now does so via the live-zone tail, and a
new MemoryMode enum makes the routing explicit and configurable.
What changed
------------
* New `MemoryMode` enum in `headroom/proxy/memory_handler.py` with two
values:
- `AUTO_TAIL` (default) — retrieval results auto-append to the latest
user message. The cache hot zone (system / instructions / frozen
prefix) is never mutated.
- `TOOL` — auto-injection is disabled entirely. The model must call
`memory_search` to retrieve. Memory is opt-in and visible.
* `MemoryConfig.mode: MemoryMode = MemoryMode.AUTO_TAIL` propagates into
`search_and_format_context`, which now short-circuits to `None` in `TOOL`
mode. This is the single chokepoint that gates every provider — Anthropic
/v1/messages, OpenAI /v1/chat/completions, OpenAI /v1/responses, and
Gemini all funnel through it, so flipping a deployment to tool mode does
not require auditing every handler.
* New `MemoryHandler._append_to_latest_user_tail(messages, context_text,
provider=..., frozen_message_count=...)` static helper provides the unified
tail-append entry point and dispatches to the existing provider-specific
helpers (`AnthropicHandlerMixin._append_context_to_latest_non_frozen_user_turn`
for Anthropic, `append_text_to_latest_user_chat_message` for OpenAI).
* Gemini handler swapped from auto-prepending memory as a system message
(the old P2-24 cache-hot-zone mutation pattern) to using
`_append_to_latest_user_tail(provider="openai")`.
* `ProxyConfig.memory_mode: Literal["auto_tail", "tool"] = "auto_tail"`
surfaces the mode for deployment configuration. Server constructs the
enum via `MemoryMode(config.memory_mode)` and raises loudly on unknown
values (no silent fallback).
* OpenAI Chat Completions, OpenAI Responses, and Anthropic handlers were
already routing to the live-zone tail via PR-A2/A3 — no code change
needed beyond inheriting the `TOOL`-mode skip from the chokepoint.
Tests
-----
* `tests/test_memory_auto_tail.py` (6 tests):
- `test_memory_appears_in_latest_user_message_tail` — Anthropic shape.
- `test_memory_appears_in_latest_user_message_tail_openai_shape` —
OpenAI string + list-content shapes.
- `test_memory_does_not_modify_system_or_tools` — system prompt and
tools list are never touched; frozen-prefix tail is a no-op.
- `test_same_query_byte_identical_across_runs` — two independent runs
with identical inputs produce byte-identical mutated message lists
(determinism gate).
- `test_default_mode_is_auto_tail` — fresh `MemoryConfig` defaults to
`AUTO_TAIL`.
- `test_unknown_provider_raises` — invalid provider strings raise
loudly per the no-silent-fallback policy.
* `tests/test_memory_tool_mode.py` (4 tests):
- `test_tool_mode_skips_auto_injection` — `search_and_format_context`
returns `None` and the backend is never queried.
- `test_tool_mode_skip_emits_structured_log` — skip emits the
`event=memory_mode_skip` log line for routing-decision auditability.
- `test_auto_tail_mode_does_query_backend` — inverse contrast pinning
down that AUTO_TAIL still works end-to-end while TOOL skips.
- `test_tool_mode_enum_value_is_stable` — string round-trip is pinned
so deployment configs do not drift on rename.
Determinism
-----------
Tests stub the backend with a fixed, ordered result set so the byte-identical
assertion isolates the tail-injection layer from upstream search non-
determinism. The vector-search layer itself (LocalBackend / HNSW) is
deterministic per-process for the same inputs but has thread-scheduling
variability across processes; per the realignment plan, request-time
determinism is guaranteed by the formatter and the tail-append helpers
(this PR's responsibility), and the backend layer's determinism stays
out-of-scope for B6.
Per-PR-B6 plan: REALIGNMENT/04-phase-B-live-zone.md.
2026-05-02 16:37:54 -07:00
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"""
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handler, _backend = _build_tool_mode_handler()
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2026-05-02 17:05:58 -07:00
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target_logger = logging.getLogger("headroom.proxy.memory_handler")
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previous_level = target_logger.level
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target_logger.setLevel(logging.INFO)
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target_logger.addHandler(caplog.handler)
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try:
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fix: B6 — memory injection moves to live-zone user-tail
PR-A2 locked the system prompt and routed Anthropic memory injection to the
latest non-frozen user turn. PR-B6 finishes the job: every provider handler
that auto-injects memory context now does so via the live-zone tail, and a
new MemoryMode enum makes the routing explicit and configurable.
What changed
------------
* New `MemoryMode` enum in `headroom/proxy/memory_handler.py` with two
values:
- `AUTO_TAIL` (default) — retrieval results auto-append to the latest
user message. The cache hot zone (system / instructions / frozen
prefix) is never mutated.
- `TOOL` — auto-injection is disabled entirely. The model must call
`memory_search` to retrieve. Memory is opt-in and visible.
* `MemoryConfig.mode: MemoryMode = MemoryMode.AUTO_TAIL` propagates into
`search_and_format_context`, which now short-circuits to `None` in `TOOL`
mode. This is the single chokepoint that gates every provider — Anthropic
/v1/messages, OpenAI /v1/chat/completions, OpenAI /v1/responses, and
Gemini all funnel through it, so flipping a deployment to tool mode does
not require auditing every handler.
* New `MemoryHandler._append_to_latest_user_tail(messages, context_text,
provider=..., frozen_message_count=...)` static helper provides the unified
tail-append entry point and dispatches to the existing provider-specific
helpers (`AnthropicHandlerMixin._append_context_to_latest_non_frozen_user_turn`
for Anthropic, `append_text_to_latest_user_chat_message` for OpenAI).
* Gemini handler swapped from auto-prepending memory as a system message
(the old P2-24 cache-hot-zone mutation pattern) to using
`_append_to_latest_user_tail(provider="openai")`.
* `ProxyConfig.memory_mode: Literal["auto_tail", "tool"] = "auto_tail"`
surfaces the mode for deployment configuration. Server constructs the
enum via `MemoryMode(config.memory_mode)` and raises loudly on unknown
values (no silent fallback).
* OpenAI Chat Completions, OpenAI Responses, and Anthropic handlers were
already routing to the live-zone tail via PR-A2/A3 — no code change
needed beyond inheriting the `TOOL`-mode skip from the chokepoint.
Tests
-----
* `tests/test_memory_auto_tail.py` (6 tests):
- `test_memory_appears_in_latest_user_message_tail` — Anthropic shape.
- `test_memory_appears_in_latest_user_message_tail_openai_shape` —
OpenAI string + list-content shapes.
- `test_memory_does_not_modify_system_or_tools` — system prompt and
tools list are never touched; frozen-prefix tail is a no-op.
- `test_same_query_byte_identical_across_runs` — two independent runs
with identical inputs produce byte-identical mutated message lists
(determinism gate).
- `test_default_mode_is_auto_tail` — fresh `MemoryConfig` defaults to
`AUTO_TAIL`.
- `test_unknown_provider_raises` — invalid provider strings raise
loudly per the no-silent-fallback policy.
* `tests/test_memory_tool_mode.py` (4 tests):
- `test_tool_mode_skips_auto_injection` — `search_and_format_context`
returns `None` and the backend is never queried.
- `test_tool_mode_skip_emits_structured_log` — skip emits the
`event=memory_mode_skip` log line for routing-decision auditability.
- `test_auto_tail_mode_does_query_backend` — inverse contrast pinning
down that AUTO_TAIL still works end-to-end while TOOL skips.
- `test_tool_mode_enum_value_is_stable` — string round-trip is pinned
so deployment configs do not drift on rename.
Determinism
-----------
Tests stub the backend with a fixed, ordered result set so the byte-identical
assertion isolates the tail-injection layer from upstream search non-
determinism. The vector-search layer itself (LocalBackend / HNSW) is
deterministic per-process for the same inputs but has thread-scheduling
variability across processes; per the realignment plan, request-time
determinism is guaranteed by the formatter and the tail-append helpers
(this PR's responsibility), and the backend layer's determinism stays
out-of-scope for B6.
Per-PR-B6 plan: REALIGNMENT/04-phase-B-live-zone.md.
2026-05-02 16:37:54 -07:00
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result = asyncio.run(
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handler.search_and_format_context("alpha", [{"role": "user", "content": "hi"}])
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)
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2026-05-02 17:05:58 -07:00
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finally:
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target_logger.removeHandler(caplog.handler)
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target_logger.setLevel(previous_level)
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fix: B6 — memory injection moves to live-zone user-tail
PR-A2 locked the system prompt and routed Anthropic memory injection to the
latest non-frozen user turn. PR-B6 finishes the job: every provider handler
that auto-injects memory context now does so via the live-zone tail, and a
new MemoryMode enum makes the routing explicit and configurable.
What changed
------------
* New `MemoryMode` enum in `headroom/proxy/memory_handler.py` with two
values:
- `AUTO_TAIL` (default) — retrieval results auto-append to the latest
user message. The cache hot zone (system / instructions / frozen
prefix) is never mutated.
- `TOOL` — auto-injection is disabled entirely. The model must call
`memory_search` to retrieve. Memory is opt-in and visible.
* `MemoryConfig.mode: MemoryMode = MemoryMode.AUTO_TAIL` propagates into
`search_and_format_context`, which now short-circuits to `None` in `TOOL`
mode. This is the single chokepoint that gates every provider — Anthropic
/v1/messages, OpenAI /v1/chat/completions, OpenAI /v1/responses, and
Gemini all funnel through it, so flipping a deployment to tool mode does
not require auditing every handler.
* New `MemoryHandler._append_to_latest_user_tail(messages, context_text,
provider=..., frozen_message_count=...)` static helper provides the unified
tail-append entry point and dispatches to the existing provider-specific
helpers (`AnthropicHandlerMixin._append_context_to_latest_non_frozen_user_turn`
for Anthropic, `append_text_to_latest_user_chat_message` for OpenAI).
* Gemini handler swapped from auto-prepending memory as a system message
(the old P2-24 cache-hot-zone mutation pattern) to using
`_append_to_latest_user_tail(provider="openai")`.
* `ProxyConfig.memory_mode: Literal["auto_tail", "tool"] = "auto_tail"`
surfaces the mode for deployment configuration. Server constructs the
enum via `MemoryMode(config.memory_mode)` and raises loudly on unknown
values (no silent fallback).
* OpenAI Chat Completions, OpenAI Responses, and Anthropic handlers were
already routing to the live-zone tail via PR-A2/A3 — no code change
needed beyond inheriting the `TOOL`-mode skip from the chokepoint.
Tests
-----
* `tests/test_memory_auto_tail.py` (6 tests):
- `test_memory_appears_in_latest_user_message_tail` — Anthropic shape.
- `test_memory_appears_in_latest_user_message_tail_openai_shape` —
OpenAI string + list-content shapes.
- `test_memory_does_not_modify_system_or_tools` — system prompt and
tools list are never touched; frozen-prefix tail is a no-op.
- `test_same_query_byte_identical_across_runs` — two independent runs
with identical inputs produce byte-identical mutated message lists
(determinism gate).
- `test_default_mode_is_auto_tail` — fresh `MemoryConfig` defaults to
`AUTO_TAIL`.
- `test_unknown_provider_raises` — invalid provider strings raise
loudly per the no-silent-fallback policy.
* `tests/test_memory_tool_mode.py` (4 tests):
- `test_tool_mode_skips_auto_injection` — `search_and_format_context`
returns `None` and the backend is never queried.
- `test_tool_mode_skip_emits_structured_log` — skip emits the
`event=memory_mode_skip` log line for routing-decision auditability.
- `test_auto_tail_mode_does_query_backend` — inverse contrast pinning
down that AUTO_TAIL still works end-to-end while TOOL skips.
- `test_tool_mode_enum_value_is_stable` — string round-trip is pinned
so deployment configs do not drift on rename.
Determinism
-----------
Tests stub the backend with a fixed, ordered result set so the byte-identical
assertion isolates the tail-injection layer from upstream search non-
determinism. The vector-search layer itself (LocalBackend / HNSW) is
deterministic per-process for the same inputs but has thread-scheduling
variability across processes; per the realignment plan, request-time
determinism is guaranteed by the formatter and the tail-append helpers
(this PR's responsibility), and the backend layer's determinism stays
out-of-scope for B6.
Per-PR-B6 plan: REALIGNMENT/04-phase-B-live-zone.md.
2026-05-02 16:37:54 -07:00
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assert result is None
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skip_records = [r for r in caplog.records if "event=memory_mode_skip" in r.getMessage()]
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assert skip_records, "TOOL mode skip must emit event=memory_mode_skip log line"
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msg = skip_records[0].getMessage()
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assert "mode=tool" in msg
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assert "user_id=alpha" in msg
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def test_auto_tail_mode_does_query_backend() -> None:
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"""Sanity: AUTO_TAIL mode (the inverse) MUST query the backend.
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Without this contrast, ``test_tool_mode_skips_auto_injection`` could be
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passing because the wiring is broken in both modes. This pins down that
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AUTO_TAIL still works end-to-end while TOOL skips.
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"""
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config = MemoryConfig(
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enabled=True,
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backend="local",
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inject_context=True,
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inject_tools=True,
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top_k=5,
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min_similarity=0.3,
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mode=MemoryMode.AUTO_TAIL,
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)
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handler = MemoryHandler(config)
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backend = _LoudBackend()
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handler._backend = backend
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handler._initialized = True
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result = asyncio.run(
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handler.search_and_format_context("alpha", [{"role": "user", "content": "hi"}])
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)
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assert result is not None
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assert backend.calls == 1
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def test_tool_mode_enum_value_is_stable() -> None:
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"""The ``"tool"`` string is the persistent on-the-wire identifier.
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Pinned to catch accidental rename — the ProxyConfig.memory_mode field
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accepts the string and must be able to round-trip via
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``MemoryMode("tool")``.
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"""
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assert MemoryMode("tool") is MemoryMode.TOOL
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assert MemoryMode("auto_tail") is MemoryMode.AUTO_TAIL
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assert MemoryMode.TOOL.value == "tool"
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assert MemoryMode.AUTO_TAIL.value == "auto_tail"
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