Update app.py

app.py

@@ -82,6 +82,12 @@ retriever = PineconeHybridSearchRetriever(
 # llm = ChatGroq(model="llama-3.1-70b-versatile", temperature=0, max_tokens=1024, max_retries=2)
 llm = ChatPerplexity(temperature=0, pplx_api_key=GROQ_API_KEY, model="llama-3.1-sonar-large-128k-online", 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 \
@@ -95,7 +101,7 @@ 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. \