change langgraph pattern

eval_protocol/pytest/default_langchain_rollout_processor.py

@@ -21,12 +21,15 @@ class LangGraphRolloutProcessor(RolloutProcessor):
     def __init__(
         self,
         *,
-        graph_factory: Callable[[Dict[str, Any]], Any],
+        # Factory must accept RolloutProcessorConfig (parity with Pydantic AI processor)
+        graph_factory: Callable[[RolloutProcessorConfig], Any],
         to_input: Optional[Callable[[EvaluationRow], Dict[str, Any]]] = None,
         apply_result: Optional[Callable[[EvaluationRow, Any], EvaluationRow]] = None,
         build_graph_kwargs: Optional[Callable[[CompletionParams], Dict[str, Any]]] = None,
         input_key: str = "messages",
         output_key: str = "messages",
+        # Optional: build per-invoke RunnableConfig dict from full RolloutProcessorConfig
+        build_invoke_config: Optional[Callable[[RolloutProcessorConfig], Dict[str, Any]]] = None,
     ) -> None:
         # Build the graph per-call using completion_params
         self._graph_factory = graph_factory
@@ -35,6 +38,7 @@ def __init__(
         self._build_graph_kwargs = build_graph_kwargs
         self._input_key = input_key
         self._output_key = output_key
+        self._build_invoke_config = build_invoke_config
 
     def _default_to_input(self, row: EvaluationRow) -> Dict[str, Any]:
         messages = row.messages or []
@@ -121,14 +125,21 @@ def __call__(self, rows: List[EvaluationRow], config: RolloutProcessorConfig) ->
         if config.completion_params:
             graph_config = build_kwargs(config.completion_params)
 
-        # (Re)build the graph for this call using the graph kwargs
-        graph_target = self._graph_factory(graph_config or {})
+        # (Re)build the graph for this call using the full typed config.
+        graph_target = self._graph_factory(config)
+
+        # Build per-invoke config if provided; otherwise reuse graph_config for backwards compat
+        invoke_config: Optional[Dict[str, Any]] = None
+        if self._build_invoke_config is not None:
+            invoke_config = self._build_invoke_config(config)
+        elif graph_config is not None:
+            invoke_config = graph_config
 
         async def _process_row(row: EvaluationRow) -> EvaluationRow:
             try:
                 payload = to_input(row)
-                if graph_config is not None:
-                    result = await graph_target.ainvoke(payload, config=graph_config)
+                if invoke_config is not None:
+                    result = await graph_target.ainvoke(payload, config=invoke_config)
                 else:
                     result = await graph_target.ainvoke(payload)
                 row = apply_result(row, result)

examples/langgraph/__init__.py

@@ -0,0 +1 @@
+# Package marker for examples.langgraph

examples/langgraph/test_langgraph_rollout.py

@@ -3,9 +3,9 @@
 from eval_protocol.models import EvaluationRow, EvaluateResult, Message
 from eval_protocol.pytest import evaluation_test
 from eval_protocol.pytest.default_langchain_rollout_processor import LangGraphRolloutProcessor
-from eval_protocol.pytest.types import RolloutProcessorConfig as _UnusedRolloutProcessorConfig  # noqa: F401
+from eval_protocol.pytest.types import RolloutProcessorConfig
 
-from examples.langgraph.simple_graph import build_simple_graph
+from .simple_graph import build_simple_graph
 import os
 import pytest
 
@@ -25,27 +25,15 @@ def adapter(raw_rows: List[Dict[str, Any]]) -> List[EvaluationRow]:
     return rows
 
 
-def build_graph_kwargs(cp: Dict[str, Any]) -> Dict[str, Any]:
-    return {
-        "config": {
-            "model": cp.get("model"),
-            "temperature": cp.get("temperature", 0.0),
-        }
-    }
-
-
-def graph_factory(graph_kwargs: Dict[str, Any]) -> Any:
-    cfg = graph_kwargs.get("config", {}) if isinstance(graph_kwargs, dict) else {}
-    model = cfg.get("model") or "accounts/fireworks/models/kimi-k2-instruct"
-    temperature = cfg.get("temperature", 0.0)
-    # Provider is fixed to fireworks for this example; can be extended via cfg if needed
+def graph_factory(config: RolloutProcessorConfig) -> Any:
+    cp = config.completion_params or {}
+    model = cp.get("model") or "accounts/fireworks/models/kimi-k2-instruct"
+    temperature = cp.get("temperature", 0.0)
+    # Provider is fixed to fireworks for this example; can be extended via cp if needed
     return build_simple_graph(model=model, model_provider="fireworks", temperature=temperature)
 
 
-processor = LangGraphRolloutProcessor(
-    graph_factory=graph_factory,
-    build_graph_kwargs=build_graph_kwargs,
-)
+processor = LangGraphRolloutProcessor(graph_factory=graph_factory)
 
 
 @pytest.mark.skipif(os.getenv("FIREWORKS_API_KEY") in (None, ""), reason="FIREWORKS_API_KEY not set")

examples/langgraph/test_reasoning_rollout.py

@@ -3,8 +3,9 @@
 from eval_protocol.models import EvaluationRow, EvaluateResult, Message
 from eval_protocol.pytest import evaluation_test
 from eval_protocol.pytest.default_langchain_rollout_processor import LangGraphRolloutProcessor
+from eval_protocol.pytest.types import RolloutProcessorConfig
 
-from examples.langgraph.reasoning_gpt_oss_120b_graph import build_reasoning_graph
+from .reasoning_gpt_oss_120b_graph import build_reasoning_graph
 import os
 import pytest
 
@@ -24,21 +25,11 @@ def adapter(raw_rows: List[Dict[str, Any]]) -> List[EvaluationRow]:
     return rows
 
 
-def build_graph_kwargs(cp: Dict[str, Any]) -> Dict[str, Any]:
-    return {
-        "config": {
-            "model": cp.get("model", "accounts/fireworks/models/gpt-oss-120b"),
-            "temperature": cp.get("temperature", 0.0),
-            "reasoning_effort": cp.get("reasoning_effort"),
-        }
-    }
-
-
-def graph_factory(graph_kwargs: Dict[str, Any]) -> Any:
-    cfg = graph_kwargs.get("config", {}) if isinstance(graph_kwargs, dict) else {}
-    model = cfg.get("model") or "accounts/fireworks/models/gpt-oss-120b"
-    temperature = cfg.get("temperature", 0.0)
-    reasoning_effort = cfg.get("reasoning_effort")
+def graph_factory(config: RolloutProcessorConfig) -> Any:
+    cp = config.completion_params or {}
+    model = cp.get("model") or "accounts/fireworks/models/gpt-oss-120b"
+    temperature = cp.get("temperature", 0.0)
+    reasoning_effort = cp.get("reasoning_effort")
     return build_reasoning_graph(
         model=model,
         model_provider="fireworks",
@@ -47,10 +38,7 @@ def graph_factory(graph_kwargs: Dict[str, Any]) -> Any:
     )
 
 
-processor = LangGraphRolloutProcessor(
-    graph_factory=graph_factory,
-    build_graph_kwargs=build_graph_kwargs,
-)
+processor = LangGraphRolloutProcessor(graph_factory=graph_factory)
 
 
 @pytest.mark.skipif(os.getenv("FIREWORKS_API_KEY") in (None, ""), reason="FIREWORKS_API_KEY not set")

tests/pytest/test_langgraph_processor.py

@@ -7,6 +7,7 @@
 
 from eval_protocol.models import EvaluationRow, Message
 from eval_protocol.pytest.default_langchain_rollout_processor import LangGraphRolloutProcessor
+from eval_protocol.pytest.types import RolloutProcessorConfig
 
 
 class DummyLCMessage:
@@ -25,7 +26,7 @@ async def ainvoke(self, payload: Dict[str, Any], **_: Any):
 
 
 def _make_processor_with_defaults(out_messages: List[Any]) -> LangGraphRolloutProcessor:
-    def graph_factory(_: Dict[str, Any]):
+    def graph_factory(_: RolloutProcessorConfig):
         return DummyGraph(out_messages)
 
     return LangGraphRolloutProcessor(graph_factory=graph_factory)
@@ -116,7 +117,7 @@ async def ainvoke(self, payload, **_):
             # Ensure our adapter-produced messages flow through
             return payload
 
-    processor = LangGraphRolloutProcessor(graph_factory=lambda _: EchoGraph())
+    processor = LangGraphRolloutProcessor(graph_factory=lambda _config: EchoGraph())
 
     # Act
     tasks = processor(