Added Databricks support to MLflow Callback (#7906)

Added a quick check to make integration easier with Databricks; another
option would be to make a new class, but this seemed more
straightfoward.

cc: @liangz1 Can this be done in a more straightfoward way?

libs/langchain/langchain/callbacks/mlflow_callback.py

@@ -1,3 +1,4 @@
+import os
 import random
 import string
 import tempfile
@@ -127,6 +128,11 @@ class MlflowLogger:
 
     def __init__(self, **kwargs: Any):
         self.mlflow = import_mlflow()
+        if "DATABRICKS_RUNTIME_VERSION" in os.environ:
+            self.mlflow.set_tracking_uri("databricks")
+            self.mlf_expid = self.mlflow.tracking.fluent._get_experiment_id()
+            self.mlf_exp = self.mlflow.get_experiment(self.mlf_expid)
+        else:
             tracking_uri = get_from_dict_or_env(
                 kwargs, "tracking_uri", "MLFLOW_TRACKING_URI", ""
             )