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
@@ -127,22 +128,27 @@ class MlflowLogger:
 
     def __init__(self, **kwargs: Any):
         self.mlflow = import_mlflow()
-        tracking_uri = get_from_dict_or_env(
-            kwargs, "tracking_uri", "MLFLOW_TRACKING_URI", ""
-        )
-        self.mlflow.set_tracking_uri(tracking_uri)
+        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", ""
+            )
+            self.mlflow.set_tracking_uri(tracking_uri)
 
-        # User can set other env variables described here
-        # > https://www.mlflow.org/docs/latest/tracking.html#logging-to-a-tracking-server
+            # User can set other env variables described here
+            # > https://www.mlflow.org/docs/latest/tracking.html#logging-to-a-tracking-server
 
-        experiment_name = get_from_dict_or_env(
-            kwargs, "experiment_name", "MLFLOW_EXPERIMENT_NAME"
-        )
-        self.mlf_exp = self.mlflow.get_experiment_by_name(experiment_name)
-        if self.mlf_exp is not None:
-            self.mlf_expid = self.mlf_exp.experiment_id
-        else:
-            self.mlf_expid = self.mlflow.create_experiment(experiment_name)
+            experiment_name = get_from_dict_or_env(
+                kwargs, "experiment_name", "MLFLOW_EXPERIMENT_NAME"
+            )
+            self.mlf_exp = self.mlflow.get_experiment_by_name(experiment_name)
+            if self.mlf_exp is not None:
+                self.mlf_expid = self.mlf_exp.experiment_id
+            else:
+                self.mlf_expid = self.mlflow.create_experiment(experiment_name)
 
         self.start_run(kwargs["run_name"], kwargs["run_tags"])