engrammemory-ai 0.1.0

Memory infrastructure for AI agents. Your Qdrant, your hardware, our intelligence.

engrammemory

Memory infrastructure for AI agents. Your Qdrant, your hardware, our intelligence.

pip install engrammemory

Quick Start

from engrammemory import Engram

client = Engram(
    api_key="eng_live_xxx",
    qdrant_url="http://localhost:6333"
)

# Store — embedded & deduplicated by Engram, stored in YOUR Qdrant
client.store("User prefers TypeScript and dark mode", category="preference")

# Search — three-tier recall (hot → hash → vector)
results = client.search("What does the user prefer?")
for r in results:
    print(f"[{r.tier}] {r.memory.content} ({r.score:.2f})")

# Forget
client.forget("mem_abc123")

Async

from engrammemory import AsyncEngram

async with AsyncEngram(api_key="eng_live_xxx") as client:
    await client.store("User prefers TypeScript")
    results = await client.search("language preferences")

Multi-Agent / Fleet

# Each agent gets its own namespace
client = Engram(api_key="eng_live_xxx", project="icu-floor-3")

# Store with agent tracking
client.store("Patient allergic to penicillin", category="fact", agent="tablet-icu-3a")

# Search scoped to project
results = client.search("allergies", agent="tablet-icu-3a")

MiroFish Integration

Replace Zep with Engram in your MiroFish .env:

MEMORY_PROVIDER=engram
ENGRAM_API_KEY=eng_live_xxx
ENGRAM_QDRANT_URL=http://localhost:6333

Links

• Documentation
• Dashboard
• GitHub
• Community Edition