diff --git a/atroposlib/envs/base.py b/atroposlib/envs/base.py
index 59c2adf3..25183f6b 100644
--- a/atroposlib/envs/base.py
+++ b/atroposlib/envs/base.py
@@ -587,58 +587,74 @@ class BaseEnv(ABC):
         Send the chats to the API with robust error handling and support for multiple ScoredDataGroups.
 
         Args:
-            scored_data: List of scored items to send
+            scored_data: Single ScoredDataGroup or List of ScoredDataGroups to send
             item: Optional item for context
+            do_send_to_api: Whether to send the data to the API
+            abort_on_any_max_length_exceeded: Whether to abort if any token length exceeds the max
         """
-        group_size = scored_data.get("group_overrides", {}).get(
-            "group_size", self.config.group_size
-        )
-        if (
-            (scored_data is not None)
-            and (None not in scored_data)
-            and (len(scored_data["tokens"]) == group_size)
-        ):
-            if self.config.ensure_scores_are_not_same:
-                if len(set(scored_data["scores"])) == 1:
-                    # Scores are the same, don't send to API
-                    logger.warning("Scores are the same, skipping...")
-                    return
-            await self.add_rollouts_for_wandb(scored_data, item)
-            # Check for ref_logprobs
-            if "ref_logprobs" not in scored_data:
-                # Strongly typed dict, so we need to add it
-                scored_data["ref_logprobs"] = None
-            if "overrides" not in scored_data:
-                scored_data["overrides"] = None
-            if "group_overrides" not in scored_data:
-                scored_data["group_overrides"] = None
+        original_was_list = isinstance(scored_data, list) # not sure if this is needed
+        data_to_process = scored_data if original_was_list else [scored_data]
 
-            # Track completion lengths
-            for mask in scored_data["masks"]:
+        valid_groups = []
+        for group in data_to_process:
+            if group is None:
+                continue
+            
+            group_size = group.get("group_overrides", {}).get(
+                "group_size", self.config.group_size
+            )
+            
+            if not ((None not in group) and (len(group.get("tokens", [])) == group_size)):
+                logger.warning(
+                    f"Group structure invalid, or token count mismatch (expected {group_size}), or 'tokens' key missing. Skipping group: {str(group)[:200]}..."
+                )
+                continue
+            
+            if self.config.ensure_scores_are_not_same and len(set(group["scores"])) == 1:
+                logger.warning("Scores are the same in a group, skipping...")
+                continue
+            
+            group.setdefault("ref_logprobs", None)
+            group.setdefault("overrides", None)
+            group.setdefault("group_overrides", None)
+            
+            for mask in group["masks"]:
                 self.completion_lengths.append(len(mask))
-            # Add the scores to the queue
+            
             if abort_on_any_max_length_exceeded and any(
-                [len(x) >= self.max_token_len for x in scored_data["tokens"]]
+                [len(x) >= self.max_token_len for x in group["tokens"]]
             ):
-                # Don't send to API if the token length is too long
-                logger.warning("Token length is too long, skipping...")
-                return
-            # Save data, if applicable:
-            if self.config.include_messages and scored_data.get("messages") is None:
-                scored_data["messages"] = [
-                    self.tokenizer.decode(scored_data["tokens"][i])
-                    for i in range(group_size)
+                logger.warning("Token length is too long in a group, skipping...")
+                continue
+            
+            if self.config.include_messages and group.get("messages") is None:
+                group["messages"] = [
+                    self.tokenizer.decode(group["tokens"][i])
+                    for i in range(len(group["tokens"]))
                 ]
+            
+            await self.add_rollouts_for_wandb(group, item)
+            
             if self.jsonl_writer is not None:
-                self.jsonl_writer.write(scored_data)
+                self.jsonl_writer.write(group)
                 print(f"Wrote scored group to {self.config.data_path_to_save_groups}")
-            # Send data with retries and error handling
+            
+            valid_groups.append(group)
+        
+        if valid_groups and do_send_to_api:
+            data_to_send_to_api: Union[ScoredDataGroup, List[ScoredDataGroup]]
+            # send single or list of scored data groups
+            if not original_was_list and len(valid_groups) == 1:
+                data_to_send_to_api = valid_groups[0]
+            else:
+                data_to_send_to_api = valid_groups
+
             try:
-                if do_send_to_api:
-                    self.items_sent_this_step += 1
-                    await self._send_scored_data_to_api(scored_data)
+                self.items_sent_this_step += len(valid_groups)
+                await self._send_scored_data_to_api(data_to_send_to_api)
             except (Exception, TimeoutError) as e:
-                print(f"Failed to send scored data after retries: {e}")
+                data_type_str = "single ScoredDataGroup" if isinstance(data_to_send_to_api, dict) else f"{len(data_to_send_to_api)} ScoredDataGroups"
+                print(f"Failed to send {data_type_str} after retries: {e}")
 
     async def handle_env(
         self, item_uuid: str