> ## Documentation Index
> Fetch the complete documentation index at: https://docs.evermind.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Cloud Quickstart

> Get started with EverOS Cloud in under 5 minutes

## Prerequisites

* An [EverOS Cloud account](https://everos.evermind.ai/)
* An [API key](https://everos.evermind.ai/api-keys): click "Create API Key", name it, and copy it securely
* Python 3.12 or higher

<Tip>
  Before getting your API key, [configure your Memory Space](https://everos.evermind.ai/memory-spaces) Scenario Mode. It influences how memories are extracted and consolidated. Learn more in the [Space Scenario Mode](/cloud/space-scenario-mode) guide.
</Tip>

<Steps>
  <Step title="Install the SDK">
    ```bash theme={null}
    pip install everos-cloud
    ```
  </Step>

  <Step title="Create a client">
    ```python theme={null}
    from everos_cloud import EverOS

    client = EverOS(api_key="your_api_key")
    ```

    <Warning>
      Never commit API keys to version control. Use environment variables in production.
    </Warning>
  </Step>

  <Step title="Add memories">
    Store conversation messages into your Memory Space. Each message's `sender_id`
    is the user the memory belongs to.

    ```python theme={null}
    client.add(
        session_id="session_gs_001",
        messages=[
            {"sender_id": "user_demo_001", "role": "user",
             "content": "I like black Americano, no sugar, the stronger the better!"},
            {"sender_id": "user_demo_001", "role": "user",
             "content": "Today I want to discuss the project progress."},
        ],
    )
    ```

    <Note>
      The call returns `status: "queued"` and extraction runs in the background on its
      own — you do not have to trigger it. Give it a few seconds before you read the
      memories back.

      For a deterministic write — in a test, say — pass `async_mode=False`. The call
      then returns the engine's own result (`"accumulated"` or `"extracted"`) instead of
      an acknowledgement.
    </Note>

    <Warning>
      `client.flush(session_id)` forces extraction for a session that is still open, but
      it only sees messages that have already landed. Called immediately after a default
      (queued) add it returns `"no_extraction"` — nothing has arrived yet. That is not an
      error, and the extraction still happens on its own moments later.
    </Warning>
  </Step>

  <Step title="Retrieve memories">
    Fetch a user's stored memories by type.

    ```python theme={null}
    data = client.get("episode", user_id="user_demo_001")
    print(f"Fetched {data.count} memories")
    ```
  </Step>

  <Step title="Search memories">
    Find relevant memories using vector, keyword, hybrid, or agentic retrieval.

    ```python theme={null}
    results = client.search(
        "coffee preference",
        user_id="user_demo_001",
        method="vector",
        top_k=5,
    )
    episodes = results.episodes or []
    print(f"Found {len(episodes)} memories")
    ```

    <Note>
      The vector index lags extraction by a few seconds. To read back something you just
      wrote, use `client.get(...)` — it reads the stored memories directly and sees them
      as soon as they are extracted.
    </Note>
  </Step>
</Steps>

## What's Next?

<CardGroup cols={3}>
  <Card title="Core Concepts" icon="brain" href="/cloud/concepts/memory-lifecycle">
    Understand the memory lifecycle, memory types, and how EverOS processes your data.
  </Card>

  <Card title="API Reference" icon="code" href="/api-reference/introduction">
    Explore the full API with detailed parameter docs, request/response examples, and error codes.
  </Card>

  <Card title="Knowledge Bases" icon="book" href="/cloud/knowledge-bases">
    Ingest documents into a searchable topic library and query it alongside memory.
  </Card>

  <Card title="Console" icon="chart-line" href="https://everos.evermind.ai">
    Monitor quota usage, track API calls, and manage keys in the EverOS Console.
  </Card>
</CardGroup>

<Note>
  **Need help?** Join our [community](https://discord.gg/geHdX4F24B).
</Note>


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