fix: Revert "Allow passing in required project_name (deepset-ai#445)" (…

…deepset-ai#467)

* Revert "Allow passing in required project_name (deepset-ai#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])