fix: Revert "Allow passing in required project_name (#445)" (#467)

* Revert "Allow passing in required project_name (#445)"

This reverts commit ffe86a9.

* fix: Fail early when API params are not correctly passed to the evaluator
doc: Update docstring to mention required API parameters

* Add back dependencies required for integration testing

integrations/uptrain/src/haystack_integrations/components/evaluators/uptrain/evaluator.py

@@ -36,7 +36,6 @@ def __init__(
         api: str = "openai",
         api_key: Secret = Secret.from_env_var("OPENAI_API_KEY"),
         api_params: Optional[Dict[str, Any]] = None,
-        project_name: Optional[str] = None,
     ):
         """
         Construct a new UpTrain evaluator.
@@ -53,16 +52,15 @@ def __init__(
             The API key to use.
         :param api_params:
             Additional parameters to pass to the API client.
-        :param project_name:
-            Name of the project required when using UpTrain API.
+
+            Required parameters for the UpTrain API: `project_name`.
         """
         self.metric = metric if isinstance(metric, UpTrainMetric) else UpTrainMetric.from_str(metric)
         self.metric_params = metric_params
         self.descriptor = METRIC_DESCRIPTORS[self.metric]
         self.api = api
         self.api_key = api_key
         self.api_params = api_params
-        self.project_name = project_name
 
         self._init_backend()
         expected_inputs = self.descriptor.input_parameters
@@ -94,7 +92,7 @@ def run(self, **inputs) -> Dict[str, Any]:
 
         :param inputs:
             The inputs to evaluate. These are determined by the
-            metric being calculated. See :class:`UpTrainMetric` for more
+            metric being calculated. See `UpTrainMetric` for more
             information.
         :returns:
             A nested list of metric results. Each input can have one or more
@@ -116,7 +114,7 @@ def run(self, **inputs) -> Dict[str, Any]:
         if isinstance(self._backend_client, EvalLLM):
             results = self._backend_client.evaluate(**eval_args)
         else:
-            results = self._backend_client.log_and_evaluate(**eval_args, project_name=self.project_name)
+            results = self._backend_client.log_and_evaluate(**eval_args)
 
         OutputConverters.validate_outputs(results)
         converted_results = [
@@ -148,7 +146,6 @@ def check_serializable(obj: Any):
             api=self.api,
             api_key=self.api_key.to_dict(),
             api_params=self.api_params,
-            project_name=self.project_name,
         )
 
     @classmethod
@@ -197,9 +194,12 @@ def _init_backend(self):
         assert api_key is not None
         if self.api == "openai":
             backend_client = EvalLLM(openai_api_key=api_key)
+            if self.api_params is not None:
+                msg = "OpenAI API does not support additional parameters"
+                raise ValueError(msg)
         elif self.api == "uptrain":
-            if not self.project_name:
-                msg = "project_name not provided. UpTrain API requires a project name."
+            if self.api_params is None or "project_name" not in self.api_params:
+                msg = "UpTrain API requires a 'project_name' API parameter"
                 raise ValueError(msg)
             backend_client = APIClient(uptrain_api_key=api_key)
 

integrations/uptrain/tests/test_evaluator.py

@@ -115,17 +115,32 @@ def test_evaluator_api(monkeypatch):
         UpTrainMetric.RESPONSE_COMPLETENESS,
         api="uptrain",
         api_key=Secret.from_env_var("UPTRAIN_API_KEY"),
-        project_name="test",
+        api_params={"project_name": "test"},
     )
     assert eval.api == "uptrain"
     assert eval.api_key == Secret.from_env_var("UPTRAIN_API_KEY")
+    assert eval.api_params == {"project_name": "test"}
 
     with pytest.raises(ValueError, match="Unsupported API"):
         UpTrainEvaluator(UpTrainMetric.CONTEXT_RELEVANCE, api="cohere")
 
     with pytest.raises(ValueError, match="None of the following authentication environment variables are set"):
         UpTrainEvaluator(UpTrainMetric.CONTEXT_RELEVANCE, api="uptrain", api_key=Secret.from_env_var("asd39920qqq"))
 
+    with pytest.raises(ValueError, match="does not support additional parameters"):
+        UpTrainEvaluator(
+            UpTrainMetric.CONTEXT_RELEVANCE,
+            api_params={"project_name": "test"},
+            api="openai",
+        )
+
+    with pytest.raises(ValueError, match="requires .* API parameter"):
+        UpTrainEvaluator(
+            UpTrainMetric.CONTEXT_RELEVANCE,
+            api_params=None,
+            api="uptrain",
+        )
+
 
 def test_evaluator_metric_init_params():
     eval = UpTrainEvaluator(
@@ -158,8 +173,7 @@ def test_evaluator_serde(os_environ_get):
         "metric_params": {"method": "rouge"},
         "api": "uptrain",
         "api_key": Secret.from_env_var("ENV_VAR", strict=False),
-        "api_params": {"eval_name": "test"},
-        "project_name": "test",
+        "api_params": {"project_name": "test"},
     }
     eval = UpTrainEvaluator(**init_params)
     serde_data = eval.to_dict()
@@ -170,13 +184,12 @@ def test_evaluator_serde(os_environ_get):
     assert eval.api_key == new_eval.api_key
     assert eval.metric_params == new_eval.metric_params
     assert eval.api_params == new_eval.api_params
-    assert eval.project_name == new_eval.project_name
     assert type(new_eval._backend_client) == type(eval._backend_client)
     assert type(new_eval._backend_metric) == type(eval._backend_metric)
 
     with pytest.raises(DeserializationError, match=r"cannot serialize the API/metric parameters"):
         init_params3 = copy.deepcopy(init_params)
-        init_params3["api_params"] = {"arg": Unserializable("")}
+        init_params3["api_params"] = {"arg": Unserializable(""), "project_name": "test"}
         eval = UpTrainEvaluator(**init_params3)
         eval.to_dict()
 
@@ -205,10 +218,8 @@ def test_evaluator_valid_inputs(metric, inputs, params):
     init_params = {
         "metric": metric,
         "metric_params": params,
-        "api": "uptrain",
         "api_key": Secret.from_token("Aaa"),
         "api_params": None,
-        "project_name": "test",
     }
     eval = UpTrainEvaluator(**init_params)
     eval._backend_client = MockBackend([metric])
@@ -234,10 +245,8 @@ def test_evaluator_invalid_inputs(metric, inputs, error_string, params):
         init_params = {
             "metric": metric,
             "metric_params": params,
-            "api": "uptrain",
             "api_key": Secret.from_token("Aaa"),
             "api_params": None,
-            "project_name": "test",
         }
         eval = UpTrainEvaluator(**init_params)
         eval._backend_client = MockBackend([metric])
@@ -311,10 +320,8 @@ def test_evaluator_outputs(metric, inputs, expected_outputs, metric_params):
     init_params = {
         "metric": metric,
         "metric_params": metric_params,
-        "api": "uptrain",
         "api_key": Secret.from_token("Aaa"),
         "api_params": None,
-        "project_name": "test",
     }
     eval = UpTrainEvaluator(**init_params)
     eval._backend_client = MockBackend([metric])