diff --git a/examples/rag/rag_example.ipynb b/examples/rag/rag_example.ipynb
index 7cbf6d6..c07a234 100644
--- a/examples/rag/rag_example.ipynb
+++ b/examples/rag/rag_example.ipynb
@@ -87,7 +87,7 @@
           "name": "stderr",
           "output_type": "stream",
           "text": [
-            "5it [00:00, 6295.86it/s]\n"
+            "5it [00:00, 37786.52it/s]\n"
           ]
         },
         {
@@ -101,7 +101,7 @@
           "name": "stderr",
           "output_type": "stream",
           "text": [
-            "100%|██████████| 1/1 [00:02<00:00,  2.04s/it]"
+            "100%|██████████| 1/1 [00:01<00:00,  1.83s/it]"
           ]
         },
         {
@@ -147,7 +147,17 @@
       },
       "outputs": [],
       "source": [
-        "ragLM = RAGLanguageModel(base=language_model, datastore=datastore)"
+        "rag_LM = RAGLanguageModel(base=language_model, datastore=datastore)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "id": "456ecd6c",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "rag_LM.generate(condition=None)"
       ]
     },
     {
diff --git a/llments/lm/rag.py b/llments/lm/rag.py
index a850f90..0a0a85b 100644
--- a/llments/lm/rag.py
+++ b/llments/lm/rag.py
@@ -14,5 +14,23 @@ def __init__(self, base: LanguageModel, datastore: Datastore):
             LanguageModel: The enhanced language model.
         """
         
+    def generate(self, condition: str | None, do_sample: bool = False, max_length: int | None = None, temperature: float = 1, num_return_sequences: int = 1) -> list[str]:
+        """Generate an output given the language model.
+
+        Args:
+            condition: The conditioning sequence for the output.
+                If None, the output is not conditioned.
+            do_sample: Whether to use sampling or greedy decoding.
+            max_length: The maximum length of the output sequence,
+                (defaults to model max).
+            temperature: The value used to module the next token probabilities.
+            num_return_sequences: The number of independently computed returned
+                sequences for each element in the batch.
+
+        Returns:
+            str: Sampled output sequences from the language model.
+        """
+        pass
+