fix: update ImportError for 'metrics' dependency (#4778)

haystack/modeling/evaluation/metrics.py

@@ -30,7 +30,7 @@
 try:
     from seqeval.metrics import classification_report as token_classification_report
 except ImportError as exc:
-    logger.debug("seqeval could not be imported. Run 'pip install farm-haystack[eval]' to fix this issue.")
+    logger.debug("seqeval could not be imported. Run 'pip install farm-haystack[metrics]' to fix this issue.")
     token_classification_report = None
 
 
@@ -150,7 +150,9 @@ def compute_report_metrics(head: PredictionHead, preds, labels):
         report_fn = registered_reports[head.ph_output_type]  # type: ignore [index]
     elif head.ph_output_type == "per_token":
         if not token_classification_report:
-            raise ImportError("seqeval could not be imported. Run 'pip install farm-haystack[eval]' to fix this issue.")
+            raise ImportError(
+                "seqeval could not be imported. Run 'pip install farm-haystack[metrics]' to fix this issue."
+            )
         report_fn = token_classification_report
     elif head.ph_output_type == "per_sequence":
         if not classification_report:

haystack/utils/context_matching.py

@@ -14,7 +14,7 @@
 try:
     from rapidfuzz import fuzz
 except ImportError as exc:
-    logger.debug("rapidfuzz could not be imported. Run 'pip install farm-haystack[eval]' to fix this issue.")
+    logger.debug("rapidfuzz could not be imported. Run 'pip install farm-haystack[metrics]' to fix this issue.")
     fuzz = None  # type: ignore
 
 
@@ -56,7 +56,9 @@ def calculate_context_similarity(
                                  Thus [AB] <-> [BC] (score ~50) gets recalculated with B <-> B (score ~100) scoring ~75 in total.
     """
     if not fuzz:
-        raise ImportError("rapidfuzz could not be imported. Run 'pip install farm-haystack[eval]' to fix this issue.")
+        raise ImportError(
+            "rapidfuzz could not be imported. Run 'pip install farm-haystack[metrics]' to fix this issue."
+        )
     # we need to handle short contexts/contents (e.g single word)
     # as they produce high scores by matching if the chars of the word are contained in the other one
     # this has to be done after normalizing

haystack/utils/experiment_tracking.py

@@ -18,7 +18,7 @@
 try:
     import mlflow
 except ImportError as exc:
-    logger.debug("mlflow could not be imported. Run 'pip install farm-haystack[eval]' to fix this issue.")
+    logger.debug("mlflow could not be imported. Run 'pip install farm-haystack[metrics]' to fix this issue.")
     mlflow = None
 
 
@@ -165,7 +165,9 @@ def __init__(self, tracking_uri: str, auto_track_environment: bool = True) -> No
         Experiment tracking head for MLflow.
         """
         if not mlflow:
-            raise ImportError("mlflow could not be imported. Run 'pip install farm-haystack[eval]' to fix this issue.")
+            raise ImportError(
+                "mlflow could not be imported. Run 'pip install farm-haystack[metrics]' to fix this issue."
+            )
         super().__init__()
         self.tracking_uri = tracking_uri
         self.auto_track_environment = auto_track_environment