diff --git a/src/petals/client/remote_generation.py b/src/petals/client/remote_generation.py
index 4405121e..6d4d1c59 100644
--- a/src/petals/client/remote_generation.py
+++ b/src/petals/client/remote_generation.py
@@ -85,15 +85,18 @@ def generate(
         self, inputs: Optional[torch.Tensor] = None, *args, session: Optional[InferenceSession] = None, **kwargs
     ):
         self._fix_generate_kwargs(kwargs)
+        logger.debug("Entered generate method with kwargs: %s", kwargs)  # Added logging
         if inputs is None:
             inputs = kwargs.pop("input_ids", None)
 
         if session is not None:
             # If a session specified explicitly, use it
             context_manager = self.use_session(session)
+            logger.debug("Using specified session: %s", session)  # Added logging
         elif self.active_session is not None:
             # If there's an active session, don't do anything
             context_manager = contextlib.nullcontext(self.active_session)
+            logger.debug("Using active session: %s", self.active_session)  # Added logging
         else:
             # If there's no active session, create a new one
 
@@ -109,6 +112,7 @@ def generate(
             else:
                 session_max_length += (inputs.shape[1] if inputs is not None else 0) + max_new_tokens
             context_manager = self.inference_session(max_length=session_max_length)
+            logger.debug("Created new session with max length: %d", session_max_length)  # Added logging
 
         with context_manager as session:
             # Prepend the tokens from the previous .generate() call
@@ -134,7 +138,9 @@ def generate(
                 past_key_values.update_seen(session.position)
                 kwargs["past_key_values"] = past_key_values
 
+            logger.debug("Starting generation with input ids: %s", inputs)  # Added logging
             result = super().generate(inputs, *args, **kwargs)
+            logger.debug("Generated result: %s", result)  # Added logging
 
             sequences = result.sequences if isinstance(result, ModelOutput) else result
             # Save tokens from this .generate() call
@@ -162,3 +168,5 @@ def _fix_generate_kwargs(kwargs: dict):
     @staticmethod
     def _reorder_cache(past_key_values: RemotePastKeyValues, beam_idx: torch.LongTensor) -> RemotePastKeyValues:
         return dataclasses.replace(past_key_values, hypo_ids=beam_idx)
+
+