memorylaier 0.1.0

Python SDK for MemoryLayer — persistent memory infrastructure for AI agents

MemoryLayer Python SDK

Python client for MemorylAIer — persistent memory infrastructure for AI agents. Knowledge graph, semantic dedup, decay, and behavioral lessons at $0.001/call. No subscription.

Install

pip install memorylaier

Quick Start

from memorylaier import MemoryLayerClient

client = MemoryLayerClient(api_key="your-api-key")

# Store facts (auto-dedup, entity extraction, relationship graph)
client.store_facts([
    {"text": "John Smith works at Acme Corp as a senior engineer"},
    {"text": "Acme Corp is based in New York"},
])

# Semantic search with time-decay scoring
results = client.query("Where does John work?")
for m in results["memories"]:
    print(f"{m['fact']} (score: {m['score']})")

# Hybrid search (vector + full-text) — best for entity names and exact terms
results = client.query("[e-mail]", hybrid=True)

# Knowledge graph traversal
graph = client.graph_traverse("John Smith", max_depth=2)
for edge in graph["edges"]:
    print(f"{edge['source']} --{edge['predicate']}--> {edge['target']}")

# Temporal query: what did we know last month?
past = client.query("John Smith", as_of="2026-02-01T00:00:00Z")

# Extract facts from conversation
client.extract_conversation([
    {"role": "user", "content": "My name is Alice and I work at Google"},
    {"role": "assistant", "content": "Nice to meet you Alice!"},
])

# Behavioral lessons
client.add_lesson("Always confirm before making changes")

# Temporal triggers
client.set_trigger(
    trigger_at="2026-03-10T09:00:00Z",
    label="Follow up with John about the project",
)

client.close()

Features

• Semantic search with time-decay and access-count boosting
• Knowledge graph with auto-extracted relationships and multi-hop traversal
• Write gate quality scoring on every write
• Auto-dedup with supersession tracking
• Temporal queries — "what did we know at date X?"
• Conversation extraction — auto-extract facts from chat messages
• Behavioral lessons — self-improvement primitives
• Temporal triggers — scheduled memory surfacing
• Memory health monitoring

Authentication

Two auth paths — use whichever fits your setup:

• API key: MemoryLayerClient(api_key="sk_...") — persistent integrations
• x402 micropayments: USDC on Base, zero-signup — see docs

Pricing

Operation	Price (USDC)
Write	$0.001
Read	$0.0005
Search	$0.001

Links

• Interactive API Docs
• OpenAPI Spec
• MCP Server — npx memorylaier-mcp
• GitHub

License

Apache-2.0