Fix TRL 0.25.1+ GRPO vision crash and reward function TypeError

unsloth/models/rl.py

@@ -1559,10 +1559,48 @@ def patch_trl_openenv():
     return
 
 
+def _patch_prepare_multimodal_messages():
+    """Fix 2: TRL >= 0.25.1 calls prepare_multimodal_messages unconditionally for
+    vision models. When notebooks pre-apply chat templates (converting prompts to strings),
+    the function crashes iterating over characters. This patch adds isinstance(messages, str)
+    guard to return strings unchanged."""
+    try:
+        import trl.data_utils as _du
+    except ImportError:
+        return
+
+    _original = getattr(_du, "prepare_multimodal_messages", None)
+    if _original is None:
+        return
+    if getattr(_original, "_unsloth_patched", False):
+        return
+
+    def _safe_prepare_multimodal_messages(messages, *args, **kwargs):
+        # If messages is already a string (pre-applied chat template), return as-is
+        if isinstance(messages, str):
+            return messages
+        return _original(messages, *args, **kwargs)
+
+    _safe_prepare_multimodal_messages._unsloth_patched = True
+    _du.prepare_multimodal_messages = _safe_prepare_multimodal_messages
+
+    # Also patch in grpo_trainer module if imported
+    try:
+        import trl.trainer.grpo_trainer as _gt
+
+        if hasattr(_gt, "prepare_multimodal_messages"):
+            _gt.prepare_multimodal_messages = _safe_prepare_multimodal_messages
+    except ImportError:
+        pass
+
+    logger.info("Unsloth: Patched prepare_multimodal_messages with string guard")
+
+
 def PatchFastRL(algorithm = None, FastLanguageModel = None):
     if FastLanguageModel is not None:
         PatchRL(FastLanguageModel)
     patch_trl_rl_trainers()
     patch_trl_openenv()
+    _patch_prepare_multimodal_messages()
     if type(algorithm) is str and algorithm.islower():
         PatchRLStatistics(algorithm)

unsloth/models/rl_replacements.py

@@ -577,6 +577,35 @@ def grpo_trainer__generate_and_score_completions(function_name, function):
 RL_FUNCTIONS["grpo_trainer"].append(grpo_trainer__generate_and_score_completions)
 
 
+# Fix 6: TRL 0.25.0+ _calculate_rewards text arguments
+#
+# TRL 0.25.0+ passes `prompts` and `completions` to _calculate_rewards in different formats:
+#   - For conversational inputs: list of dicts [{"role": "assistant", "content": "..."}]
+#   - For non-conversational inputs: plain text strings
+#
+# This inconsistency causes reward functions to fail when they expect one format but get the other.
+# The variables `prompts_text` and `completions_text` always contain plain decoded text strings.
+#
+# Fix: Always pass plain text (prompts_text, completions_text) to _calculate_rewards for consistency.
+# This ensures reward functions receive predictable string format regardless of conversational mode.
+def grpo_trainer__calculate_rewards_text_fix(function_name, function):
+    if function_name != "_generate_and_score_completions":
+        return function
+
+    # Only apply if prompts_text and completions_text exist (TRL 0.25.0+)
+    if "prompts_text" in function and "completions_text" in function:
+        # Replace the _calculate_rewards call to use text versions
+        function = function.replace(
+            "self._calculate_rewards(inputs, prompts, completions, completion_ids_list)",
+            "self._calculate_rewards(inputs, prompts_text, completions_text, completion_ids_list)",
+        )
+
+    return function
+
+
+RL_FUNCTIONS["grpo_trainer"].append(grpo_trainer__calculate_rewards_text_fix)
+
+
 # Fix {"reasoning_effort" : "high"} not applied
 def grpo_trainer_fix_maybe_apply_chat_template(function_name, function):
     spaces = function.find("def ")