Chore: add language to event tracking

.github/workflows/ci.yaml

@@ -23,8 +23,8 @@ jobs:
       ragas: ${{ steps.filter.outputs.ragas }}
       docs: ${{ steps.filter.outputs.docs }}
     steps:
-      - uses: actions/checkout@v3
-      - uses: dorny/paths-filter@v2
+      - uses: actions/checkout@v4
+      - uses: dorny/paths-filter@v3
         id: filter
         with:
           base: "main"
@@ -59,7 +59,7 @@ jobs:
     runs-on: ${{ matrix.os }}
 
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
         with:
           fetch-depth: 0 # fetch all tags and branches
 
@@ -108,7 +108,7 @@ jobs:
     if: ${{ (github.event_name == 'pull_request' && needs.diff.outputs.ragas == 'true') || github.event_name == 'push' }}
 
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
 
       - name: Setup python
         uses: actions/setup-python@v4

src/ragas/_analytics.py

@@ -87,12 +87,14 @@ class EvaluationEvent(BaseEvent):
     metrics: t.List[str]
     evaluation_mode: str
     num_rows: int
+    language: str
 
 
 class TesetGenerationEvent(BaseEvent):
     evolution_names: t.List[str]
     evolution_percentages: t.List[float]
     num_rows: int
+    language: str
 
 
 @silent

src/ragas/evaluation.py

@@ -18,6 +18,7 @@
 from ragas.metrics.base import Metric, MetricWithEmbeddings, MetricWithLLM
 from ragas.metrics.critique import AspectCritique
 from ragas.run_config import RunConfig
+from ragas.utils import get_feature_language
 
 # from ragas.metrics.critique import AspectCritique
 from ragas.validation import (
@@ -249,12 +250,15 @@ def evaluate(
 
     # log the evaluation event
     metrics_names = [m.name for m in metrics]
+    metric_lang = [get_feature_language(m) for m in metrics]
+    metric_lang = np.unique([m for m in metric_lang if m is not None])
     track(
         EvaluationEvent(
             event_type="evaluation",
             metrics=metrics_names,
             evaluation_mode="",
             num_rows=dataset.shape[0],
+            language=metric_lang[0] if len(metric_lang) > 0 else "",
         )
     )
     return result

src/ragas/testset/generator.py

@@ -28,7 +28,7 @@
 )
 from ragas.testset.extractor import KeyphraseExtractor
 from ragas.testset.filters import EvolutionFilter, NodeFilter, QuestionFilter
-from ragas.utils import check_if_sum_is_close, is_nan
+from ragas.utils import check_if_sum_is_close, get_feature_language, is_nan
 
 if t.TYPE_CHECKING:
     from langchain_core.documents import Document as LCDocument
@@ -251,12 +251,15 @@ def generate(
         # due to failed evolutions. MaxRetriesExceeded is a common reason
         test_data_rows = [r for r in test_data_rows if not is_nan(r)]
         test_dataset = TestDataset(test_data=test_data_rows)
+        evol_lang = [get_feature_language(e) for e in distributions]
+        evol_lang = [e for e in evol_lang if e is not None]
         track(
             TesetGenerationEvent(
                 event_type="testset_generation",
                 evolution_names=[e.__class__.__name__.lower() for e in distributions],
                 evolution_percentages=[distributions[e] for e in distributions],
                 num_rows=len(test_dataset.test_data),
+                language=evol_lang[0] if len(evol_lang) > 0 else "",
             )
         )
 

src/ragas/utils.py

@@ -7,6 +7,10 @@
 
 import numpy as np
 
+if t.TYPE_CHECKING:
+    from ragas.metrics.base import Metric
+    from ragas.testset.evolutions import Evolution
+
 DEBUG_ENV_VAR = "RAGAS_DEBUG"
 
 
@@ -57,3 +61,14 @@ def is_nan(x):
         return np.isnan(x)
     except TypeError:
         return False
+
+
+def get_feature_language(feature: t.Union[Metric, Evolution]) -> t.Optional[str]:
+    from ragas.llms.prompt import Prompt
+
+    languags = [
+        value.language
+        for _, value in vars(feature).items()
+        if isinstance(value, Prompt)
+    ]
+    return languags[0] if len(languags) > 0 else None

tests/unit/test_analytics.py

@@ -21,13 +21,18 @@ def test_evaluation_event():
     from ragas._analytics import EvaluationEvent
 
     evaluation_event = EvaluationEvent(
-        event_type="evaluation", metrics=["harmfulness"], num_rows=1, evaluation_mode=""
+        event_type="evaluation",
+        metrics=["harmfulness"],
+        num_rows=1,
+        evaluation_mode="",
+        language="english",
     )
 
     payload = dict(evaluation_event)
     assert isinstance(payload.get("user_id"), str)
     assert isinstance(payload.get("evaluation_mode"), str)
     assert isinstance(payload.get("metrics"), list)
+    assert isinstance(payload.get("language"), str)
 
 
 def setup_user_id_filepath(tmp_path, monkeypatch):
@@ -101,6 +106,7 @@ def test_testset_generation_tracking(monkeypatch):
         evolution_names=[e.__class__.__name__.lower() for e in distributions],
         evolution_percentages=[distributions[e] for e in distributions],
         num_rows=10,
+        language="english",
     )
 
     assert dict(testset_event_payload)["evolution_names"] == [