memblock 0.4.2

Typed block tree + knowledge graph memory SDK for AI agents

MemBlock

Structured memory SDK for AI agents.

Typed blocks · Knowledge graph · Hybrid search · Encryption · Decay engine — all local, all yours.

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Install

pip install memblock

Quick Start

from memblock import MemBlock, BlockType

mem = MemBlock(storage="sqlite:///memory.db")

# Store structured memories
mem.store("User prefers Python", type=BlockType.PREFERENCE)
mem.store("User works at Acme Corp", type=BlockType.FACT, confidence=0.95)

# Query with hybrid search
results = mem.query(text_search="programming", type=BlockType.PREFERENCE)

# Build LLM-ready context
context = mem.build_context(query="user preferences", token_budget=4000)

# Knowledge graph
mem.link(results[0].id, other.id, relation="related_to")

# Tamper detection
mem.verify()

What's Included

• 5 typed memory blocks — FACT, PREFERENCE, EVENT, ENTITY, RELATION
• Knowledge graph — 8 relation types, traversal, no external DB
• Hybrid search — FTS5 + vector similarity with Reciprocal Rank Fusion
• Memory decay — Exponential decay with access reinforcement
• AES-256 encryption — Field-level, your keys, no enterprise tier
• Tamper detection — SHA-256 hash chain on every operation
• LLM extraction — Auto-extract memories from conversations (OpenAI, Anthropic, Gemini)
• Conflict resolution — LLM-powered ADD/UPDATE/DELETE decisions
• Context builder — Token-budgeted, 3 strategies
• Async API — Full async support via AsyncMemBlock
• Event hooks — on_add, on_update, on_delete, on_query
• Hierarchical scoping — org → project → user → agent → session
• Rerankers — BM25, Cohere, CrossEncoder
• Storage — SQLite (local) or PostgreSQL (production)
• CLI — init, query, stats, prune, export, reindex

Optional Extras

pip install "memblock[postgres]"            # PostgreSQL backend
pip install "memblock[embeddings]"          # Local vector embeddings (FastEmbed)
pip install "memblock[llm]"                 # LLM extraction (OpenAI, Anthropic, Gemini)
pip install "memblock[reranker-cohere]"     # Cohere reranker
pip install "memblock[reranker-cross-encoder]"  # HuggingFace reranker
pip install "memblock[all]"                 # Everything

Documentation

Full docs, API reference, and examples: memblock.xyz

License

Proprietary. Copyright (c) 2025-2026 iexcalibur. All Rights Reserved.