diff --git a/langchain/callbacks/comet_ml_callback.py b/langchain/callbacks/comet_ml_callback.py
index f057cea84f..7917d26a50 100644
--- a/langchain/callbacks/comet_ml_callback.py
+++ b/langchain/callbacks/comet_ml_callback.py
@@ -96,7 +96,7 @@ class CometCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
         self,
         task_type: Optional[str] = "inference",
         workspace: Optional[str] = None,
-        project_name: Optional[str] = "comet-langchain-demo",
+        project_name: Optional[str] = None,
         tags: Optional[Sequence] = None,
         name: Optional[str] = None,
         visualizations: Optional[List[str]] = None,
@@ -106,7 +106,7 @@ class CometCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
     ) -> None:
         """Initialize callback handler."""
 
-        comet_ml = import_comet_ml()
+        self.comet_ml = import_comet_ml()
         super().__init__()
 
         self.task_type = task_type
@@ -133,7 +133,7 @@ class CometCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
             "https://github.com/comet-ml/issue_tracking/issues with the tag "
             "`langchain`."
         )
-        comet_ml.LOGGER.warning(warning)
+        self.comet_ml.LOGGER.warning(warning)
 
         self.callback_columns: list = []
         self.action_records: list = []
@@ -242,8 +242,6 @@ class CometCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
         resp.update(flatten_dict(serialized))
         resp.update(self.get_custom_callback_meta())
 
-        comet_ml = import_comet_ml()
-
         for chain_input_key, chain_input_val in inputs.items():
             if isinstance(chain_input_val, str):
                 input_resp = deepcopy(resp)
@@ -253,7 +251,7 @@ class CometCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
                 self.action_records.append(input_resp)
 
             else:
-                comet_ml.LOGGER.warning(
+                self.comet_ml.LOGGER.warning(
                     f"Unexpected data format provided! "
                     f"Input Value for {chain_input_key} will not be logged"
                 )
@@ -268,8 +266,6 @@ class CometCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
         resp.update({"action": "on_chain_end"})
         resp.update(self.get_custom_callback_meta())
 
-        comet_ml = import_comet_ml()
-
         for chain_output_key, chain_output_val in outputs.items():
             if isinstance(chain_output_val, str):
                 output_resp = deepcopy(resp)
@@ -278,7 +274,7 @@ class CometCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
                 output_resp.update({chain_output_key: chain_output_val})
                 self.action_records.append(output_resp)
             else:
-                comet_ml.LOGGER.warning(
+                self.comet_ml.LOGGER.warning(
                     f"Unexpected data format provided! "
                     f"Output Value for {chain_output_key} will not be logged"
                 )
@@ -449,7 +445,14 @@ class CometCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
         self._log_session(langchain_asset)
 
         if langchain_asset:
-            self._log_model(langchain_asset)
+            try:
+                self._log_model(langchain_asset)
+            except Exception:
+                self.comet_ml.LOGGER.error(
+                    "Failed to export agent or LLM to Comet",
+                    exc_info=True,
+                    extra={"show_traceback": True},
+                )
 
         if finish:
             self.experiment.end()
@@ -470,8 +473,6 @@ class CometCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
         self.experiment.log_text(prompt, metadata=metadata, step=step)
 
     def _log_model(self, langchain_asset: Any) -> None:
-        comet_ml = import_comet_ml()
-
         model_parameters = self._get_llm_parameters(langchain_asset)
         self.experiment.log_parameters(model_parameters, prefix="model")
 
@@ -487,24 +488,45 @@ class CometCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
                 langchain_asset.save_agent(langchain_asset_path)
                 self.experiment.log_model(model_name, str(langchain_asset_path))
             else:
-                comet_ml.LOGGER.warning(
+                self.comet_ml.LOGGER.error(
                     f"{e}"
                     " Could not save Langchain Asset "
                     f"for {langchain_asset.__class__.__name__}"
                 )
 
     def _log_session(self, langchain_asset: Optional[Any] = None) -> None:
-        llm_session_df = self._create_session_analysis_dataframe(langchain_asset)
-        # Log the cleaned dataframe as a table
-        self.experiment.log_table("langchain-llm-session.csv", llm_session_df)
+        try:
+            llm_session_df = self._create_session_analysis_dataframe(langchain_asset)
+            # Log the cleaned dataframe as a table
+            self.experiment.log_table("langchain-llm-session.csv", llm_session_df)
+        except Exception:
+            self.comet_ml.LOGGER.warning(
+                "Failed to log session data to Comet",
+                exc_info=True,
+                extra={"show_traceback": True},
+            )
 
-        metadata = {"langchain_version": str(langchain.__version__)}
-        # Log the langchain low-level records as a JSON file directly
-        self.experiment.log_asset_data(
-            self.action_records, "langchain-action_records.json", metadata=metadata
-        )
+        try:
+            metadata = {"langchain_version": str(langchain.__version__)}
+            # Log the langchain low-level records as a JSON file directly
+            self.experiment.log_asset_data(
+                self.action_records, "langchain-action_records.json", metadata=metadata
+            )
+        except Exception:
+            self.comet_ml.LOGGER.warning(
+                "Failed to log session data to Comet",
+                exc_info=True,
+                extra={"show_traceback": True},
+            )
 
-        self._log_visualizations(llm_session_df)
+        try:
+            self._log_visualizations(llm_session_df)
+        except Exception:
+            self.comet_ml.LOGGER.warning(
+                "Failed to log visualizations to Comet",
+                exc_info=True,
+                extra={"show_traceback": True},
+            )
 
     def _log_text_metrics(self, metrics: Sequence[dict], step: int) -> None:
         if not metrics:
@@ -519,7 +541,6 @@ class CometCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
             return
 
         spacy = import_spacy()
-        comet_ml = import_comet_ml()
 
         prompts = session_df["prompts"].tolist()
         outputs = session_df["text"].tolist()
@@ -544,7 +565,9 @@ class CometCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
                         step=idx,
                     )
                 except Exception as e:
-                    comet_ml.LOGGER.warning(e)
+                    self.comet_ml.LOGGER.warning(
+                        e, exc_info=True, extra={"show_traceback": True}
+                    )
 
         return