diff --git a/private_gpt/server/chat/chat_service.py b/private_gpt/server/chat/chat_service.py
index 16e464dc..6ae771d4 100644
--- a/private_gpt/server/chat/chat_service.py
+++ b/private_gpt/server/chat/chat_service.py
@@ -9,7 +9,6 @@ from llama_index.core.indices import VectorStoreIndex
 from llama_index.core.indices.postprocessor import MetadataReplacementPostProcessor
 from llama_index.core.llms import ChatMessage, MessageRole
 from llama_index.core.postprocessor import (
-    KeywordNodePostprocessor,
     SimilarityPostprocessor,
 )
 from llama_index.core.storage import StorageContext
@@ -107,38 +106,17 @@ class ChatService:
             vector_index_retriever = self.vector_store_component.get_retriever(
                 index=self.index, context_filter=context_filter
             )
-
-            # To use the keyword search, you must install spacy:
-            # pip install spacy
-            if settings().llm.keywords_include or settings().llm.keywords_exclude:
-                return ContextChatEngine.from_defaults(
-                    system_prompt=system_prompt,
-                    retriever=vector_index_retriever,
-                    llm=self.llm_component.llm,  # Takes no effect at the moment
-                    node_postprocessors=[
-                        MetadataReplacementPostProcessor(target_metadata_key="window"),
-                        SimilarityPostprocessor(
-                            similarity_cutoff=settings().llm.similarity_value
-                        ),
-                        KeywordNodePostprocessor(
-                            required_keywords=settings().llm.keywords_include,
-                            exclude_keywords=settings().llm.keywords_exclude,
-                        ),
-                    ],
-                )
-            else:
-                return ContextChatEngine.from_defaults(
-                    system_prompt=system_prompt,
-                    retriever=vector_index_retriever,
-                    llm=self.llm_component.llm,  # Takes no effect at the moment
-                    node_postprocessors=[
-                        MetadataReplacementPostProcessor(target_metadata_key="window"),
-                        SimilarityPostprocessor(
-                            similarity_cutoff=settings().llm.similarity_value
-                        ),
-                    ],
-                )
-
+            return ContextChatEngine.from_defaults(
+                system_prompt=system_prompt,
+                retriever=vector_index_retriever,
+                llm=self.llm_component.llm,  # Takes no effect at the moment
+                node_postprocessors=[
+                    MetadataReplacementPostProcessor(target_metadata_key="window"),
+                    SimilarityPostprocessor(
+                        similarity_cutoff=settings().llm.similarity_value
+                    ),
+                ],
+            )
         else:
             return SimpleChatEngine.from_defaults(
                 system_prompt=system_prompt,
diff --git a/private_gpt/settings/settings.py b/private_gpt/settings/settings.py
index b345c738..6f8d2809 100644
--- a/private_gpt/settings/settings.py
+++ b/private_gpt/settings/settings.py
@@ -106,14 +106,6 @@ class LLMSettings(BaseModel):
         None,
         description="If set, any documents retrieved from the RAG must meet a certain score. Acceptable values are between 0 and 1.",
     )
-    keywords_include: list[str] = Field(
-        [],
-        description="If set, any documents retrieved from the RAG Must include this keyword",
-    )
-    keywords_exclude: list[str] = Field(
-        [],
-        description="If set, any documents retrieved from the RAG Must exclude this keyword",
-    )
 
 
 class VectorstoreSettings(BaseModel):
diff --git a/settings.yaml b/settings.yaml
index 6ee5d35c..8eb5c839 100644
--- a/settings.yaml
+++ b/settings.yaml
@@ -41,8 +41,6 @@ llm:
   context_window: 3900
   temperature: 0.1      # The temperature of the model. Increasing the temperature will make the model answer more creatively. A value of 0.1 would be more factual. (Default: 0.1)
   #similarity_value: 0.4    #If set, any documents retrieved from the RAG must meet a certain score. Acceptable values are between 0 and 1.
-  #keywords_include: ["Apples","Bananas"] #Optional - requires spacy package: pip install spacy
-  #keywords_exclude: ["Pears","Mangos"]   #Optional - requires spacy package: pip install spacy
 
 llamacpp:
   prompt_style: "mistral"