Update app.py

app.py

@@ -152,15 +152,7 @@ if query:
         st.success("✅ Context retrieved successfully!")
 
     # ----------------- Run Individual Chains Explicitly -----------------
-    context_relevancy_chain = LLMChain(llm=llm_judge, prompt=PromptTemplate(input_variables=["retriever_query", "context"], template=relevancy_prompt), output_key="relevancy_response")
-    relevant_context_chain = LLMChain(llm=llm_judge, prompt=PromptTemplate(input_variables=["relevancy_response"], template=relevant_context_picker_prompt), output_key="context_number")
-    relevant_contexts_chain = LLMChain(llm=llm_judge, prompt=PromptTemplate(input_variables=["context_number", "context"], template=response_synth), output_key="relevant_contexts")
-    response_chain = LLMChain(llm=rag_llm, prompt=PromptTemplate(input_variables=["query", "context"], template=rag_prompt), output_key="final_response")
-
-    response_crisis = context_relevancy_chain.invoke({"context": context, "retriever_query": query})
-    relevant_response = relevant_context_chain.invoke({"relevancy_response": response_crisis["relevancy_response"]})
-    contexts = relevant_contexts_chain.invoke({"context_number": relevant_response["context_number"], "context": context})
-    final_response = response_chain.invoke({"query": query, "context": contexts["relevant_contexts"]})
+
 
     # ----------------- Display All Outputs -----------------
     st.markdown("### Context Relevancy Evaluation")