Update app.py

app.py

@@ -8,6 +8,7 @@ from langchain.prompts import ChatPromptTemplate
 from langchain_core.output_parsers import StrOutputParser
 from langchain_core.runnables import RunnablePassthrough
 from qdrant_client import QdrantClient
+from operator import itemgetter
 
 # Set up API keys
 os.environ["OPENAI_API_KEY"] = st.secrets["OPENAI_API_KEY"]
@@ -71,4 +72,43 @@ def create_rag_pipeline(vector_store):
     5. If the context doesn't contain sufficient information to fully answer the question, state this clearly and say,'I don't know'.
     6. Do not introduce any information not present in the context.
     7. If asked for an opinion or recommendation, base it strictly on insights from the context.
-    8. Use
+    8. Use a confident, authoritative tone while maintaining accuracy.
+    9. If you cannot provide a clear answer to the question, reply with "I don't know".
+
+    Question:
+    {question}
+
+    Context:
+    {context}
+
+    Answer:
+    """
+
+    prompt = ChatPromptTemplate.from_template(template)
+    primary_qa_llm = ChatOpenAI(model_name="gpt-4", temperature=0)
+
+    retrieval_augmented_qa_chain = (
+        {"context": itemgetter("question") | retriever, "question": itemgetter("question")}
+        | RunnablePassthrough.assign(context=itemgetter("context"))
+        | {"response": prompt | primary_qa_llm, "context": itemgetter("context")}
+    )
+
+    return retrieval_augmented_qa_chain
+
+# Streamlit UI
+st.title("Ask About AI Ethics!")
+
+vector_store = setup_vectorstore()
+rag_pipeline = create_rag_pipeline(vector_store)
+
+user_query = st.text_input("Enter your question about AI Ethics:")
+
+if user_query:
+    with st.spinner("Generating response..."):
+        result = rag_pipeline.invoke({"question": user_query})
+    
+    st.write("Response:")
+    st.write(result["response"].content)
+
+    st.write("Context Used:")
+    st.write(result["context"])