Update app.py

app.py

@@ -20,6 +20,8 @@ from pinecone_text.sparse import BM25Encoder
 from langchain_huggingface import HuggingFaceEmbeddings
 from langchain_community.retrievers import PineconeHybridSearchRetriever
 from langchain_groq import ChatGroq
+from langchain.retrievers import ContextualCompressionRetriever
+from langchain.retrievers.document_compressors import FlashrankRerank
 
 # Load environment variables
 # load_dotenv(".env")
@@ -56,14 +58,9 @@ def initialize_pinecone(index_name: str):
 ##################################################
 ##          Change down here
 ##################################################
-
-
 # #### This is for UAE Economic Department Website
 pinecone_index = initialize_pinecone("saudi-arabia-ministry-of-justice")
 bm25 = BM25Encoder().load("./saudi-arabia-bm25-encoder.json")
-
-
-
 ##################################################
 ##################################################
 
@@ -74,13 +71,19 @@ retriever = PineconeHybridSearchRetriever(
     embeddings=embed_model, 
     sparse_encoder=bm25, 
     index=pinecone_index, 
-    top_k=20, 
+    top_k=10, 
     alpha=0.5
 )
 
 # Initialize LLM
 llm = ChatGroq(model="llama-3.1-70b-versatile", temperature=0, max_tokens=1024, max_retries=2)
 
+# Initialize Reranker
+compressor = FlashrankRerank()
+compression_retriever = ContextualCompressionRetriever(
+    base_compressor=compressor, base_retriever=retriever
+)
+
 # Contextualization prompt and retriever
 contextualize_q_system_prompt = """Given a chat history and the latest user question \
 which might reference context in the chat history, formulate a standalone question \
@@ -94,7 +97,7 @@ contextualize_q_prompt = ChatPromptTemplate.from_messages(
         ("human", "{input}")
     ]
 )
-history_aware_retriever = create_history_aware_retriever(llm, retriever, contextualize_q_prompt)
+history_aware_retriever = create_history_aware_retriever(llm, compression_retriever, contextualize_q_prompt)
 
 # QA system prompt and chain
 qa_system_prompt = """You are a highly skilled information retrieval assistant. Use the following context to answer questions effectively. \
@@ -114,7 +117,7 @@ When responding to queries, follow these guidelines: \
         - Downloadable Materials: Provide links to any relevant downloadable resources if applicable. \
     
     3. Formatting for Readability: \
-        - The answer should be in a proper HTML format with appropriate tags. \
+        - The answer should be in a proper Markdown format with appropriate tags. \
         - For arabic language response align the text to right and convert numbers also.
         - Double check if the language of answer is correct or not.
         - Use bullet points or numbered lists where applicable to present information clearly. \