diff --git a/juddges/data/datasets/context_truncator.py b/juddges/data/datasets/context_truncator.py
new file mode 100644
index 0000000..875a93d
--- /dev/null
+++ b/juddges/data/datasets/context_truncator.py
@@ -0,0 +1,37 @@
+import warnings
+
+from tokenizers.implementations import BaseTokenizer
+
+
+class ContextTruncator:
+    def __init__(self, tokenizer: BaseTokenizer, max_length: int):
+        self.tokenizer = tokenizer
+        self.max_length = max_length
+
+        empty_messages = [
+            {"role": "user", "content": ""},
+            {"role": "assistant", "content": ""},
+        ]
+
+        self.empty_messages_length = self.tokenizer.apply_chat_template(
+            empty_messages, tokenize=True, return_dict=True, return_length=True
+        )["length"][0]
+
+    def __call__(self, prompt: str, context: str, output: str) -> str:
+        prompt_length, output_length = self.tokenizer(
+            [prompt, output], return_length=True, add_special_tokens=False
+        )["length"]
+
+        context_length = (
+            self.max_length - prompt_length - output_length - self.empty_messages_length
+        )
+        if context_length <= 0:
+            warnings.warn(
+                f"Context was truncated to 0 tokens. "
+                f"The prompt and output are too long for the max_length of {self.max_length}."
+            )
+            return ""
+        context_ids = self.tokenizer(
+            context, max_length=context_length, truncation=True, add_special_tokens=False
+        )["input_ids"]
+        return self.tokenizer.decode(context_ids)