Wire tier-2b Langfuse Generation fixtures

tests/conformance/test_observability.py

@@ -182,6 +182,11 @@ def _reset_otel_global_tracer_provider(restore_to: object) -> None:
         "035-caller-invocation-id-uuid",
         "036-caller-invocation-id-non-uuid",
         "059-implementation-attribution-langfuse",
+        # Tier 2b: Langfuse Generation observation (proposal 0031 §8.4.3/§8.4.4)
+        # -- model / modelParameters / usage / input-output payload (with
+        # truncation) and prompt-entity linkage.
+        "023-langfuse-generation-rendering",
+        "024-langfuse-prompt-linkage",
         # proposal 0052 attribution fixture (case 1) + proposal 0061
         # (case 2: the §5.1 attribution lands on the detached trace's own
         # openarmature.invocation span). Wired together now that 0061
@@ -298,14 +303,10 @@ def _reset_otel_global_tracer_provider(restore_to: object) -> None:
 _UNIT_TESTED_FIXTURES: dict[str, str] = {
     fixture_id: reason
     for fixture_ids, reason in (
-        # Fixture-harness catch-up tier 2a wired the trace-shape Langfuse
-        # fixtures (022/031/032), the invocation-id fixtures (035/036), and the
-        # attribution fixture (059). 023/024 (Langfuse Generation) are tier 2b;
-        # 033 (detached multi-trace) is tier 4.
-        (
-            ("023-langfuse-generation-rendering", "024-langfuse-prompt-linkage"),
-            "proposal 0031 Langfuse generation/prompt-linkage; covered by test_observability_langfuse.py",
-        ),
+        # Fixture-harness catch-up tier 2 wired the trace-shape Langfuse
+        # fixtures (022/031/032), invocation-id (035/036), attribution (059) in
+        # 2a, and the Langfuse Generation fixtures (023/024) in 2b. 033 (detached
+        # multi-trace) is tier 4.
         (
             ("033-langfuse-detached-trace-mode",),
             "proposal 0035/0061 Langfuse detached-trace mode; covered by test_observability_langfuse.py",
@@ -556,6 +557,11 @@ async def test_observability_fixture(fixture_path: Path) -> None:
         "036-caller-invocation-id-non-uuid",
     }:
         await _run_invocation_id_fixture(spec)
+    elif fixture_id in {
+        "023-langfuse-generation-rendering",
+        "024-langfuse-prompt-linkage",
+    }:
+        await _run_langfuse_generation_fixture(spec)
     elif fixture_id in {
         "012-otel-llm-payload-default-off",
         "013-otel-llm-payload-enabled",
@@ -2649,6 +2655,19 @@ def _langfuse_value_matches(
         and set(cast("Mapping[str, Any]", expected)).issubset(_LANGFUSE_MATCHER_SUBKEYS)
     ):
         return _langfuse_matcher_subkeys_match(actual, cast("Mapping[str, Any]", expected), params)
+    # A regular NON-empty nested mapping (e.g. 024 metadata.prompt): recurse per
+    # key so inner tokens (rendered_hash: <any-string>) still apply. Subset over
+    # keys -- every expected key must be present and match; actual MAY carry
+    # extras. An empty expected dict falls through to exact equality below
+    # (rather than vacuously matching any mapping).
+    if isinstance(expected, Mapping) and expected:
+        if not isinstance(actual, Mapping):
+            return False
+        actual_map = cast("Mapping[str, Any]", actual)
+        return all(
+            k in actual_map and _langfuse_value_matches(actual_map[k], v, bindings=bindings, params=params)
+            for k, v in cast("Mapping[str, Any]", expected).items()
+        )
     return bool(actual == expected)
 
 
@@ -2821,6 +2840,50 @@ async def _run_invocation_id_case(case: Mapping[str, Any]) -> None:
         assert actual == val, f"trace.metadata.{key} {actual!r} != {val!r}"
 
 
+async def _run_langfuse_generation_fixture(spec: Mapping[str, Any]) -> None:
+    """Driver for the Langfuse Generation fixtures (023 generation rendering +
+    truncation, 024 prompt linkage). Builds a calls_llm graph, records into an
+    InMemoryLangfuseClient under the fixture's observer config, and asserts the
+    Generation observation nested under the node span.
+    """
+    for case in cast("list[dict[str, Any]]", spec["cases"]):
+        case_name = cast("str", case["name"])
+        try:
+            await _run_langfuse_generation_case(case)
+        except AssertionError as e:
+            raise AssertionError(f"case {case_name!r}: {e}") from e
+
+
+async def _run_langfuse_generation_case(case: Mapping[str, Any]) -> None:
+    import openarmature
+    from openarmature.observability.langfuse import InMemoryLangfuseClient, LangfuseObserver
+
+    graph, state_cls, provider = _build_simple_llm_graph(case, populate_caller_metadata=False)
+    client = InMemoryLangfuseClient()
+    cfg = cast("dict[str, Any]", case.get("langfuse_observer") or {})
+    lf_kwargs: dict[str, Any] = {"client": client}
+    if "disable_provider_payload" in cfg:
+        lf_kwargs["disable_provider_payload"] = bool(cfg["disable_provider_payload"])
+    if "payload_byte_cap" in cfg:
+        lf_kwargs["payload_byte_cap"] = int(cfg["payload_byte_cap"])
+    observer = LangfuseObserver(**lf_kwargs)
+    graph.attach_observer(observer)
+    state = _make_state_instance(case, state_cls)
+    try:
+        await graph.invoke(state)
+        await graph.drain()
+    finally:
+        observer.shutdown()
+        await provider.aclose()
+
+    assert len(client.traces) == 1, f"expected 1 Langfuse trace; got {len(client.traces)}"
+    trace = next(iter(client.traces.values()))
+    bindings: dict[str, Any] = {}
+    params = {"implementation_name": openarmature.__implementation_name__}
+    expected = cast("dict[str, Any]", case["expected"]["langfuse_trace"])
+    _assert_langfuse_trace_shape(trace, expected, bindings=bindings, params=params)
+
+
 # ---------------------------------------------------------------------------
 # Fixture 010 — log correlation
 #
@@ -3755,6 +3818,55 @@ async def _update_body(_s: Any, _payload: dict[str, Any] = update_block) -> dict
     return builder.compile(), state_cls, providers
 
 
+def _assert_langfuse_generation_fields(
+    exp_name: str | None,
+    match: Any,
+    exp: Mapping[str, Any],
+    *,
+    bindings: dict[str, Any],
+    params: Mapping[str, Any],
+) -> None:
+    """Generation-observation fields beyond the base span shape (023/024):
+    model / modelParameters / usage, the input parse-or-truncation shapes, and
+    the prompt-entity link. Each is asserted only when present, so it is inert
+    for span / tool observations. The placeholder-capable fields go through the
+    value-matcher (consistent with metadata); usage is a typed integer record.
+    """
+    if "model" in exp:
+        assert _langfuse_value_matches(match.model, exp["model"], bindings=bindings, params=params), (
+            f"{exp_name!r}: model {match.model!r} did not match {exp['model']!r}"
+        )
+    if "modelParameters" in exp:
+        assert _langfuse_value_matches(
+            match.model_parameters, exp["modelParameters"], bindings=bindings, params=params
+        ), f"{exp_name!r}: modelParameters {match.model_parameters!r} != {exp['modelParameters']!r}"
+    if "usage" in exp:
+        u = cast("dict[str, Any]", exp["usage"])
+        got = None if match.usage is None else (match.usage.input, match.usage.output, match.usage.total)
+        assert got == (u["input"], u["output"], u["total"]), f"{exp_name!r}: usage {got!r} != {u!r}"
+    if "prompt_entity_link" in exp:
+        assert _langfuse_value_matches(
+            match.prompt_entity_link, exp["prompt_entity_link"], bindings=bindings, params=params
+        ), (
+            f"{exp_name!r}: prompt_entity_link {match.prompt_entity_link!r} "
+            f"did not match {exp['prompt_entity_link']!r}"
+        )
+    if exp.get("prompt_entity_link_absent") is True:
+        assert match.prompt_entity_link is None, (
+            f"{exp_name!r}: expected no prompt_entity_link; got {match.prompt_entity_link!r}"
+        )
+    if "input_parses_as_messages" in exp:
+        # Under-cap input is the native message list (§8.7); compare directly.
+        assert match.input == exp["input_parses_as_messages"], (
+            f"{exp_name!r}: input {match.input!r} did not parse as {exp['input_parses_as_messages']!r}"
+        )
+    if exp.get("input_is_raw_string_with_marker") is True:
+        # Over-cap input falls through to the raw truncated string + §5.5.5 marker.
+        assert isinstance(match.input, str) and "[truncated" in match.input, (
+            f"{exp_name!r}: expected a raw truncated string with marker; got {match.input!r}"
+        )
+
+
 def _assert_langfuse_observation_tree(
     trace: Any,
     expected: list[dict[str, Any]],
@@ -3802,6 +3914,7 @@ def _assert_langfuse_observation_tree(
                 assert match.metadata.get(key) == val, (
                     f"{exp_name!r}: metadata.{key} {match.metadata.get(key)!r} != {val!r}"
                 )
+        _assert_langfuse_generation_fields(exp_name, match, exp, bindings=bindings or {}, params=params or {})
         children = cast("list[dict[str, Any]] | None", exp.get("children"))
         if children:
             _assert_langfuse_observation_tree(
@@ -4146,6 +4259,13 @@ def _materialize_typed_messages(messages_spec: Sequence[Mapping[str, Any]]) -> l
     for m in messages_spec:
         role = m.get("role")
         content = m.get("content")
+        # content_repeat synthesis (023 case 2 / fixture 014, mirroring the OTel
+        # _materialize_messages helper): N repetitions of a single char to drive
+        # payload truncation. The fixtures use a single-byte ASCII char, so the
+        # char count equals the byte count.
+        cr = cast("Mapping[str, Any] | None", m.get("content_repeat"))
+        if cr is not None:
+            content = cast("str", cr["char"]) * int(cr["bytes"])
         if role == "system":
             out.append(SystemMessage(content=_require_text_content(role, content)))
         elif role == "user":
@@ -4179,6 +4299,13 @@ def _render_prompt_result(case: Mapping[str, Any], prompt_name: str) -> Any:
         rendered = rendered.replace("{{" + key + "}}", str(value)).replace("{{ " + key + " }}", str(value))
     messages: list[Message] = [UserMessage(content=rendered)]
     now = datetime.now(UTC)
+    # A backend that exposes a Langfuse Prompt reference (024 case 1,
+    # mock_with_langfuse_reference) surfaces it as the langfuse_prompt
+    # observability entity; the observer reads it to link the Generation.
+    observability_entities: dict[str, Any] | None = None
+    reference = entry.get("langfuse_prompt_reference")
+    if reference is not None:
+        observability_entities = {"langfuse_prompt": reference}
     return PromptResult(
         name=cast("str", entry["name"]),
         version=cast("str", entry["version"]),
@@ -4189,6 +4316,7 @@ def _render_prompt_result(case: Mapping[str, Any], prompt_name: str) -> Any:
         variables=variables,
         fetched_at=now,
         rendered_at=now,
+        observability_entities=observability_entities,
     )