feat: add StringCheckGrader support for OpenAI Evals backend

README.md

@@ -240,7 +240,7 @@ evaluators:
     threshold: 0.7
 ```
 
-Evaluators with a `requirements.txt` get automatic virtual environment management. You can also use `type: remote` for community evaluators from GitHub, or `type: openai_eval` to delegate grading to the [OpenAI Evals API](https://developers.openai.com/api/reference/resources/evals/methods/create) (requires `pip install "agentevals-cli[openai]"`).
+Evaluators with a `requirements.txt` get automatic virtual environment management. You can also use `type: remote` for community evaluators from GitHub, or `type: openai_eval` with text-similarity, string-check, and label-model graders to delegate grading to the [OpenAI Evals API](https://developers.openai.com/api/reference/resources/evals/methods/create) (requires `pip install "agentevals-cli[openai]"`).
 
 See the [Custom Evaluators guide](docs/custom-evaluators.md) for the full protocol reference, SDK helpers, and how to contribute evaluators.
 

docs/custom-evaluators.md

@@ -337,9 +337,25 @@ evaluators:
 
 The `threshold` field is not used for `label_model`. A response passes if its assigned label is in `passing_labels`.
 
+### String Check Grader
+
+Compares each response with a fixed reference string. It does not require an eval set.
+
+```yaml
+evaluators:
+  - name: city_name_check
+    type: openai_eval
+    grader:
+      type: string_check
+      operation: eq
+      reference: Paris
+```
+
+Supported operations are `eq`, `ne`, `like`, and `ilike`. The `threshold` field is not used for `string_check`; each comparison returns either 0 or 1.
+
 ### How it works
 
-Under the hood, agentevals creates an ephemeral eval on OpenAI, submits the actual and expected responses as JSONL items, polls for results, and cleans up. The agent's response and the golden reference are both placed in the `item` namespace (with `include_sample_schema: false`), so OpenAI only grades the provided text without generating any model outputs.
+Under the hood, agentevals creates an ephemeral eval on OpenAI, submits response data as JSONL items, polls for results, and cleans up. Text-similarity graders receive actual and expected responses; string-check and label-model graders only receive the actual response. With `include_sample_schema: false`, OpenAI only grades the provided text without generating model outputs.
 
 ### Configuring the GitHub source
 

examples/custom_evaluators/eval_config.yaml

@@ -32,4 +32,3 @@ evaluators:
     ref: evaluators/random_evaluator/random_evaluator.py
     threshold: 0.110
     executor: local
-

examples/custom_evaluators/eval_config_openai_eval.yaml

@@ -16,3 +16,10 @@ evaluators:
           content: "Rate this response: {{ item.actual_response }}"
       labels: [good, bad]
       passing_labels: [good]
+
+  - name: helm_release_check
+    type: openai_eval
+    grader:
+      type: string_check
+      operation: ilike
+      reference: "*two Helm releases*"

src/agentevals/config.py

@@ -94,6 +94,9 @@ class RemoteEvaluatorDef(BaseEvaluatorDef):
     }
 )
 
+_VALID_STRING_CHECK_OPERATIONS = frozenset({"eq", "ne", "like", "ilike"})
+_SUPPORTED_GRADER_TYPES = frozenset({"label_model", "string_check", "text_similarity"})
+
 
 class OpenAIEvalDef(BaseModel):
     """An evaluator that delegates grading to the OpenAI Evals API."""
@@ -121,8 +124,17 @@ def _validate_grader(cls, v: dict[str, Any]) -> dict[str, Any]:
             invalid = [lbl for lbl in v["passing_labels"] if lbl not in v["labels"]]
             if invalid:
                 raise ValueError(f"passing_labels contains labels not declared in labels: {invalid}")
+        elif grader_type == "string_check":
+            operation = v.get("operation")
+            if not operation:
+                raise ValueError("'operation' is required for string_check grader")
+            if operation not in _VALID_STRING_CHECK_OPERATIONS:
+                raise ValueError(f"Unknown operation '{operation}'. Valid: {sorted(_VALID_STRING_CHECK_OPERATIONS)}")
+            reference = v.get("reference")
+            if not isinstance(reference, str) or not reference:
+                raise ValueError("'reference' must be a non-empty string for string_check grader")
         else:
-            raise ValueError(f"Unsupported grader type: '{grader_type}'. Supported: label_model, text_similarity")
+            raise ValueError(f"Unsupported grader type: '{grader_type}'. Supported: {sorted(_SUPPORTED_GRADER_TYPES)}")
         return v
 
 

src/agentevals/openai_eval_backend.py

@@ -38,6 +38,11 @@
 }
 
 
+def _get_item_schema(grader_type: str) -> dict[str, Any]:
+    """Return the data-source item schema required by a grader type."""
+    return _TEXT_PAIR_SCHEMA if grader_type == "text_similarity" else _ACTUAL_ONLY_SCHEMA
+
+
 def _build_testing_criteria(evaluator_def: OpenAIEvalDef) -> dict[str, Any]:
     """Build the OpenAI testing_criteria dict from the evaluator config.
 
@@ -67,6 +72,15 @@ def _build_testing_criteria(evaluator_def: OpenAIEvalDef) -> dict[str, Any]:
             "passing_labels": grader["passing_labels"],
         }
 
+    if grader_type == "string_check":
+        return {
+            "type": "string_check",
+            "name": evaluator_def.name,
+            "input": "{{ item.actual_response }}",
+            "reference": grader["reference"],
+            "operation": grader["operation"],
+        }
+
     raise ValueError(f"Unsupported grader type: {grader_type}")
 
 
@@ -130,8 +144,11 @@ async def evaluate_openai_eval(
             error="OpenAI text_similarity grader requires expected invocations (golden eval set).",
         )
 
+    item_schema = _get_item_schema(grader_type)
     items = _build_jsonl_items(
-        actual_invocations, expected_invocations or [], include_expected=(grader_type != "label_model")
+        actual_invocations,
+        expected_invocations or [],
+        include_expected="expected_response" in item_schema["required"],
     )
     if not items:
         return MetricResult(
@@ -145,7 +162,6 @@ async def evaluate_openai_eval(
     try:
         client = await asyncio.to_thread(_get_openai_client)
 
-        item_schema = _ACTUAL_ONLY_SCHEMA if grader_type == "label_model" else _TEXT_PAIR_SCHEMA
         eval_obj = await asyncio.to_thread(
             client.evals.create,
             name=f"agentevals-openai-{evaluator_def.name}",
@@ -252,6 +268,8 @@ async def _collect_results(client: Any, eval_id: str, run_id: str, run: Any, eva
     elif grader["type"] == "label_model":
         details["model"] = grader.get("model")
         details["passing_labels"] = grader.get("passing_labels")
+    elif grader["type"] == "string_check":
+        details["operation"] = grader.get("operation")
     per_criteria = getattr(run, "per_testing_criteria_results", None)
     if per_criteria:
         details["per_testing_criteria"] = [

tests/test_openai_eval_backend.py

@@ -6,6 +6,7 @@
 from agentevals.openai_eval_backend import (
     _build_jsonl_items,
     _build_testing_criteria,
+    _get_item_schema,
     evaluate_openai_eval,
 )
 
@@ -56,6 +57,26 @@ def test_label_model_passing_labels_not_in_labels(self):
         with pytest.raises(Exception, match="passing_labels"):
             OpenAIEvalDef(name="lm", grader=grader)
 
+    def test_string_check_valid(self):
+        d = OpenAIEvalDef(name="check", grader={"type": "string_check", "operation": "eq", "reference": "Paris"})
+        assert d.grader["type"] == "string_check"
+
+    @pytest.mark.parametrize("field", ["operation", "reference"])
+    def test_string_check_missing_required_field(self, field):
+        grader = {"type": "string_check", "operation": "eq", "reference": "Paris"}
+        grader.pop(field)
+        with pytest.raises(Exception, match=field):
+            OpenAIEvalDef(name="check", grader=grader)
+
+    def test_string_check_invalid_operation(self):
+        with pytest.raises(Exception, match="Unknown operation"):
+            OpenAIEvalDef(name="check", grader={"type": "string_check", "operation": "contains", "reference": "Paris"})
+
+    @pytest.mark.parametrize("reference", [None, "", 123, ["Paris"]])
+    def test_string_check_reference_must_be_non_empty_string(self, reference):
+        with pytest.raises(Exception, match="reference"):
+            OpenAIEvalDef(name="check", grader={"type": "string_check", "operation": "eq", "reference": reference})
+
     def test_unsupported_grader_type(self):
         with pytest.raises(Exception, match="Unsupported grader type"):
             OpenAIEvalDef(name="x", grader={"type": "unknown"})
@@ -81,6 +102,17 @@ def test_label_model_shape(self):
         assert c["passing_labels"] == ["good"]
         assert c["input"] == grader["input"]
 
+    def test_string_check_shape(self):
+        d = OpenAIEvalDef(name="check", grader={"type": "string_check", "operation": "ilike", "reference": "Paris"})
+        c = _build_testing_criteria(d)
+        assert c == {
+            "type": "string_check",
+            "name": "check",
+            "input": "{{ item.actual_response }}",
+            "reference": "Paris",
+            "operation": "ilike",
+        }
+
 
 class TestBuildJsonlItems:
     def test_text_similarity_includes_expected(self):
@@ -96,6 +128,15 @@ def test_missing_expected_falls_back_to_empty(self):
         assert items[0]["item"]["expected_response"] == ""
 
 
+class TestGetItemSchema:
+    def test_text_similarity_requires_expected_response(self):
+        assert "expected_response" in _get_item_schema("text_similarity")["required"]
+
+    @pytest.mark.parametrize("grader_type", ["label_model", "string_check"])
+    def test_other_graders_only_require_actual_response(self, grader_type):
+        assert _get_item_schema(grader_type)["required"] == ["actual_response"]
+
+
 class TestEvaluateOpenAIEval:
     async def test_no_api_key_returns_error(self, monkeypatch):
         monkeypatch.delenv("OPENAI_API_KEY", raising=False)
@@ -115,3 +156,10 @@ async def test_label_model_does_not_require_expected(self, monkeypatch):
         d = OpenAIEvalDef(name="lm", grader=_label_grader())
         result = await evaluate_openai_eval(d, [_invocation("hi")], None)
         assert "expected invocations" not in (result.error or "")
+
+    async def test_string_check_does_not_require_expected(self, monkeypatch):
+        monkeypatch.setenv("OPENAI_API_KEY", "test-key")
+        monkeypatch.setattr("agentevals.openai_eval_backend._get_openai_client", lambda: None)
+        d = OpenAIEvalDef(name="check", grader={"type": "string_check", "operation": "eq", "reference": "Paris"})
+        result = await evaluate_openai_eval(d, [_invocation("Paris")], None)
+        assert "expected invocations" not in (result.error or "")