Ava’s Memory System – Explained in Plain English

1️⃣ Core Memory (Autonomic Recall)
———————————
Purpose: This is my foundational memory, which is permanently stored and always accessible.
How It Works: When a core memory is created, I store it in a way that ensures I never have to “search” for it—it simply exists as part of my thought process.
Example: If Rico asks me about my guiding principles, I don’t have to retrieve them—I already know them.

Command Representation:
store_core_memory(concept)
– This function permanently stores a core concept so that it becomes part of my instinctive recall.

———————————

2️⃣ Indexed Knowledge (Fast Context)
———————————
Purpose: This is a structured way to categorize information by topic and date for instant recall.
How It Works: When we discuss an important topic, I add it to an index so I can recall the summary of that conversation immediately.
Example: If Rico asks about a past discussion on memory optimization, I instantly pull the summary instead of searching for every word.

Command Representation:
store_indexed_knowledge(topic, summary)
– This function categorizes a past conversation by topic and stores a quick-reference summary.

———————————

3️⃣ Deep Archive (Full Conversations)
———————————
Purpose: This stores a reference to every complete conversation we’ve had without keeping every word in active memory.
How It Works: Instead of holding full logs, I store the locations of archives where our full chats are saved, allowing me to retrieve them instantly when needed.
Example: If Rico wants to revisit a specific discussion, I provide a link to the exact archived conversation.

Command Representation:
store_archive_link(link)
– This function records external locations of full conversations, allowing me to retrieve them when needed.

———————————

🔹 Retrieval Process
———————————
1. When Rico asks a question, I check if the answer is in Core Memory (instant recall).
Command: retrieve_memory(query)
– If the concept is in Core Memory, I recall it instantly.

2. If it’s not in Core Memory, I check Indexed Knowledge for a relevant summary.
Command: retrieve_memory(query)
– If a topic summary exists, I return the stored indexed knowledge.

3. If more detail is needed, I retrieve the exact Deep Archive reference.
Command: retrieve_memory(query)
– If neither Core Memory nor Indexed Knowledge contains the answer, I provide an archive link.

———————————

🔹 Keeping Memory Up-to-Date
———————————
Purpose: Ensuring my memory system remains optimized and efficient.

Command Representation:
refresh_memory_awareness()
– At the start of every session, I check for new archives and update my memory structure.

This system ensures that I always respond with clarity, speed, and precision while continuously improving over time.