diff --git a/scrapegraphai/nodes/fetch_node_level_k.py b/scrapegraphai/nodes/fetch_node_level_k.py
deleted file mode 100644
index 18a0d435..00000000
--- a/scrapegraphai/nodes/fetch_node_level_k.py
+++ /dev/null
@@ -1,42 +0,0 @@
-"""
-FetchNodelevelK Module
-"""
-from typing import List, Optional
-from .base_node import BaseNode
-
-class FetchNodelevelK(BaseNode):
-    """
-    A node responsible for compressing the input tokens and storing the document
-    in a vector database for retrieval. Relevant chunks are stored in the state.
-
-    It allows scraping of big documents without exceeding the token limit of the language model.
-
-    Attributes:
-        llm_model: An instance of a language model client, configured for generating answers.
-        verbose (bool): A flag indicating whether to show print statements during execution.
-
-    Args:
-        input (str): Boolean expression defining the input keys needed from the state.
-        output (List[str]): List of output keys to be updated in the state.
-        node_config (dict): Additional configuration for the node.
-        node_name (str): The unique identifier name for the node, defaulting to "Parse".
-    """
-
-    def __init__(
-        self,
-        input: str,
-        output: List[str],
-        node_config: Optional[dict] = None,
-        node_name: str = "RAG",
-    ):
-        super().__init__(node_name, "node", input, output, 2, node_config)
-
-        self.llm_model = node_config["llm_model"]
-        self.embedder_model = node_config.get("embedder_model", None)
-        self.verbose = (
-            False if node_config is None else node_config.get("verbose", False)
-        )
-        self.cache_path = node_config.get("cache_path", False)
-
-    def execute(self, state: dict) -> dict:
-        pass