Update app.py

app.py

@@ -94,6 +94,23 @@ def similarity_search(query, chunks, method="Cosine", index=None, k=5):
             distances, indices = index.search(query_embedding, k)
             return [(chunks[i], 1 - distances[0][j]) for j, i in enumerate(indices[0])]
     return []
+    
+DEFAULT_SYSTEM_PROMPTS = {
+    "Multi-Query": """You are an AI language model assistant. Your task is to generate five 
+different versions of the given user question to retrieve relevant documents from a vector 
+database. By generating multiple perspectives on the user question, your goal is to help
+the user overcome some of the limitations of the distance-based similarity search. 
+Provide these alternative questions separated by newlines. Original question: {question}""",
+    "RAG Fusion": """You are an AI language model assistant. Your task is to combine multiple 
+queries into a single, refined query to improve retrieval accuracy. Original question: {question}""",
+    "Decomposition": """You are an AI language model assistant. Your task is to break down 
+the given user question into simpler sub-questions. Provide these sub-questions separated 
+by newlines. Original question: {question}""",
+    "Step Back": """You are an AI language model assistant. Your task is to refine the given 
+user question by taking a step back and asking a more general question. Original question: {question}""",
+    "HyDE": """You are an AI language model assistant. Your task is to generate a hypothetical 
+document that would be relevant to the given user question. Original question: {question}""",
+}
 
 # Streamlit App
 def main():