feat(rag): expose similarity_top_k and similarity_score to settings (#1771)

* Added RAG settings to settings.py, vector_store and chat_service to add similarity_top_k and similarity_score

* Updated settings in vector and chat service per Ivans request

* Updated code for mypy

private_gpt/server/chat/chat_service.py

@@ -8,6 +8,9 @@ from llama_index.core.chat_engine.types import (
 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 (
+    SimilarityPostprocessor,
+)
 from llama_index.core.storage import StorageContext
 from llama_index.core.types import TokenGen
 from pydantic import BaseModel
@@ -20,6 +23,7 @@ from private_gpt.components.vector_store.vector_store_component import (
 )
 from private_gpt.open_ai.extensions.context_filter import ContextFilter
 from private_gpt.server.chunks.chunks_service import Chunk
+from private_gpt.settings.settings import Settings
 
 
 class Completion(BaseModel):
@@ -68,14 +72,18 @@ class ChatEngineInput:
 
 @singleton
 class ChatService:
+    settings: Settings
+
     @inject
     def __init__(
         self,
+        settings: Settings,
         llm_component: LLMComponent,
         vector_store_component: VectorStoreComponent,
         embedding_component: EmbeddingComponent,
         node_store_component: NodeStoreComponent,
     ) -> None:
+        self.settings = settings
         self.llm_component = llm_component
         self.embedding_component = embedding_component
         self.vector_store_component = vector_store_component
@@ -98,9 +106,12 @@ class ChatService:
         use_context: bool = False,
         context_filter: ContextFilter | None = None,
     ) -> BaseChatEngine:
+        settings = self.settings
         if use_context:
             vector_index_retriever = self.vector_store_component.get_retriever(
-                index=self.index, context_filter=context_filter
+                index=self.index,
+                context_filter=context_filter,
+                similarity_top_k=self.settings.rag.similarity_top_k,
             )
             return ContextChatEngine.from_defaults(
                 system_prompt=system_prompt,
@@ -108,6 +119,9 @@ class ChatService:
                 llm=self.llm_component.llm,  # Takes no effect at the moment
                 node_postprocessors=[
                     MetadataReplacementPostProcessor(target_metadata_key="window"),
+                    SimilarityPostprocessor(
+                        similarity_cutoff=settings.rag.similarity_value
+                    ),
                 ],
             )
         else: