Memory that gets smarter
the more your agent uses it

Change one import. Every conversation is remembered automatically.

# Claude
from extremis.wrap import Anthropic  # drop-in for anthropic.Anthropic
from extremis import Extremis

client = Anthropic(api_key="sk-ant-...", memory=Extremis())

# Your existing code — unchanged
response = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[{"role": "user", "content": user_message}]
)
# ↑ extremis recalled context, injected it, saved the reply
#   nothing else needed

# OpenAI
from extremis.wrap import OpenAI

client = OpenAI(api_key="sk-...", memory=Extremis())
response = client.chat.completions.create(model="gpt-4o", messages=[...])

Install: pip3.11 install "extremis[wrap-anthropic]"  ·  pip3.11 install "extremis[wrap-openai]"

Full control — call remember, recall, and report_outcome yourself.

from extremis import Extremis, MemoryLayer

mem = Extremis()

# Store
mem.remember("User is building a WhatsApp AI", conversation_id="c1")
mem.remember_now("Always ask about deadlines first", layer=MemoryLayer.PROCEDURAL)

# Recall — every result explains why it ranked
results = mem.recall("what is the user building?")
for r in results:
    print(r.memory.content)
    print(r.reason)  # "similarity 0.87 · score +2.0 · used 5× · 3d old"

# Reinforcement — good memories surface first over time
mem.report_outcome([r.memory.id for r in results[:2]], success=True)