Update app.py

app.py

@@ -206,14 +206,14 @@ async def run_hackrx(req: RunRequest):
     # dense_retriever = Chroma.from_documents(documents=chunks, embedding=ml_models["embedder"]).as_retriever()
     ensemble_retriever = EnsembleRetriever(retrievers=[keyword_retriever, dense_retriever], weights=[0.4, 0.6],search_kwargs={"k": 11})
     ### to make it faster we are now using our built reranker thats why commenting the code below
-    # compression_retriever = ContextualCompressionRetriever(
-    #     base_retriever=ensemble_retriever, base_compressor=ml_models["reranker_compressor"]
-    # )
+    compression_retriever = ContextualCompressionRetriever(
+        base_retriever=ensemble_retriever, base_compressor=ml_models["reranker_compressor"]
+    )
 
     
     # Define the RAG chain using pre-loaded components
     hybrid_rag_chain = (
-        {"context": itemgetter("full_query") | ensemble_retriever, "full_query": itemgetter("full_query")}
+        {"context": itemgetter("full_query") | compression_retriever, "full_query": itemgetter("full_query")}
         | ml_models["prompt_template"]
         | ml_models["llm"]
     )