Define Memory Purpose: Clarify what the memory layer should store: facts, user history, or conversation context for retrieval..Select Memory Structure: Choose vector memory, key-value stores or databases based on speed, size, and retrieval needs..Implement Embeddings: Encode inputs into dense vectors that capture semantic meaning for efficient memory comparison and search..Build Retriever Logic: Use similarity metrics (cosine, dot product) to fetch relevant memories matching new queries..Integrate with LLM: Feed retrieved memory chunks into model prompts so the LLM uses them during generation..Manage Memory Growth: Apply pruning, summarising or hierarchical storage to keep memory efficient and cost-effective..Design Update Rules: Allow memory to evolve: add new entries, update existing, and remove stale information..Ensure Privacy Controls: Secure sensitive memory data with encryption and access restrictions in compliance with policies..Evaluate & Iterate: Continuously test memory effectiveness, refine retrieval quality, and improve integration for better model responses..Read More Stories.Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp