everos-cloud 1.0.0rc3

EverOS Cloud Memory API

☁️ Managed long-term memory for AI agents — the official Cloud Python SDK

Website · Documentation · Console

Which package? This is EverOS Cloud — the managed SaaS client (pip install everos-cloud).

Want to self-host? Use the open-source everos library instead.

EverOS Cloud — Python SDK

Give your AI agents memory that persists across sessions — managed, searchable, and typed. Add a conversation; EverOS turns it into structured, retrievable memory you can query in one call.

Why EverOS Cloud

• Self-evolving memory — memory doesn't just pile up, it improves. Background consolidation merges related episodes and refines user profiles over time, so recall gets sharper the more your agent is used.
• Structured memory, not chat logs — extracts episodes, user profiles, and reusable agent cases & skills from raw conversations, so retrieval returns meaning, not transcripts.
• Retrieval that fits the query — keyword, vector, hybrid (default), or agentic multi-step search.
• Multimodal — attach images, audio, and documents to any message.
• Built for production — fully managed (no vector DB or extraction pipeline to run), with low-latency retrieval and high-concurrency throughput. The engineering guarantees you don't get from self-hosting.
• Fully typed (pydantic v2) — every request/response is a typed model with full hints, so you get editor autocomplete and validation instead of raw dicts.

Install

pip install everos-cloud

Pre-releases need --pre: pip install --pre everos-cloud.

Upgrading from the 0.4.x client? 1.x is a rewrite with a new API surface — see the migration guide. Pin everos-cloud<1 to stay on the old client.

Quickstart

Get an API key from the EverOS Console, then:

from everos_cloud import ApiClient, Configuration, MemoryApi
from everos_cloud.models import AddInput, MessageItem, Content, SearchInput

config = Configuration(access_token="sk-...")

with ApiClient(config) as client:
    memory = MemoryApi(client)

    memory.add_memory(AddInput(
        session_id="session-1",
        messages=[MessageItem(
            sender_id="user-1", role="user", timestamp=1700000000,
            content=Content("I love hiking in the mountains"),
        )],
    ))

    result = memory.search_memory(SearchInput(query="outdoor hobbies", method="hybrid"))
    print(result.data)

Full usage — all six Memory endpoints, profile editing, deletion, and multimodal uploads — is in quickstart.md.

Documentation

• Full SDK usage
• Quickstart
• API Reference
• Core Concepts

back to top