> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cube.dev/llms.txt
> Use this file to discover all available pages before exploring further.
> Configure the agent that ships with every Cube deployment — accessible views, LLM, runtime, and memory.
# Overview
Every Cube deployment ships with an agent that powers AI features such as [Analytics Chat](/docs/explore-analyze/analytics-chat). You can customize the agent's behavior with rules, certified queries, accessible views, model selection, and memory configuration.
Configuring the agent in the UI is **deprecated** in favor of code-first configuration. Cube version 1.6.5 or above is required.
Deployments created after **April 30, 2026** have code-first agent configuration enabled by default. Existing deployments need to opt in by setting `CUBE_CLOUD_AGENTS_CONFIG_ENABLED=true`. The directory path defaults to `agents` and can be overridden with `CUBE_CLOUD_AGENTS_CONFIG_PATH`.
## Agent configuration
Agent configuration lives in your **Cube data model repository**, alongside your cubes and views. Configuration is defined as YAML and Markdown files under an `agents/` directory in your project:
```text theme={"dark"}
your-cube-project/
├── model/
│ └── cubes/
│ └── orders.yml
├── agents/
│ ├── config.yml # Agent configuration
│ ├── rules/ # Rules as Markdown
│ │ └── fiscal-year.md
│ └── certified_queries/ # Certified queries as Markdown
│ └── quarterly-revenue.md
└── cube.py
```
Storing configuration as code in your repository enables version control, code review, and consistent behavior across environments.
## Configure the agent
Place agent properties at the root of `agents/config.yml`:
```yaml theme={"dark"}
# agents/config.yml
llm: claude_4_sonnet
runtime: plain
accessible_views:
- orders_view
- customers_view
memory_mode: user
```
### Properties
| Property | Type | Default | Description |
| ------------------ | ---------------- | ------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `llm` | string or object | `auto` | LLM provider — `auto`, a [predefined model](#llm) name, or a [BYOM](/admin/ai/bring-your-own-model) reference. |
| `embedding_llm` | string or object | `text-embedding-3-large` | Embedding model — a predefined name or a BYOM reference. |
| `runtime` | string | `plain` | [Runtime mode](#runtime) — `plain` or `reasoning`. |
| `accessible_views` | array | *all views* | List of view names exposed to the agent as context guidance for which views to query. This is not a security control — if omitted or empty, all views are exposed. Use [access policies](/reference/data-modeling/data-access-policies) to enforce actual access restrictions. |
| `memory_mode` | string | `space` | [Memory isolation mode](#memory) — `space`, `user`, or `disabled`. |
Rules and certified queries have their own dedicated pages:
* [Rules](/admin/ai/rules) — instructions that guide the agent's behavior
* [Certified queries](/admin/ai/certified-queries) — a library of trusted SQL examples for the agent
* [Skills](/admin/ai/skills) — reusable, named agent workflows users can run on demand from chat
## LLM
The default value is `auto` — Cube picks a recommended model on your behalf and may change it as better models become available. Use `auto` unless you have a reason to pin a specific model.
To pin a specific model, set the `llm` property to one of the predefined models:
**Anthropic Claude:**
* `claude_3_5_sonnetv2`
* `claude_3_7_sonnet`
* `claude_3_7_sonnet_thinking`
* `claude_4_sonnet`
* `claude_4_5_sonnet`
* `claude_4_5_haiku`
* `claude_4_5_opus`
* `claude_4_6_sonnet`
* `claude_4_6_opus`
* `claude_4_7_opus`
**OpenAI GPT:**
* `gpt_4o`
* `gpt_4_1`
* `gpt_4_1_mini`
* `gpt_5`
* `gpt_5_mini`
* `gpt_5_3`
* `gpt_5_4`
* `o3`
* `o4_mini`
To use your own model, see [Bring your own model](/admin/ai/bring-your-own-model).
### Embedding models
Predefined embedding models for the `embedding_llm` property:
* `text-embedding-3-large`
* `text-embedding-3-small`
BYOM is also supported for embedding models.
## Runtime
The `runtime` property controls how the agent processes requests:
| Mode | Description |
| ----------- | ---------------------------------------------------------------------- |
| `plain` | Default. Optimized for speed and cost. Recommended for most use cases. |
| `reasoning` | Enables extended thinking for complex analysis. |
`reasoning` is **experimental**. It may be unstable and is not yet feature-complete. Stick with `plain` unless you have a specific need for extended reasoning.
## Memory
The `memory_mode` property controls how the agent persists context across conversations:
| Mode | Description |
| ---------- | ------------------------------------------------------------------------------------------- |
| `space` | Default. Memories are shared across all users — useful when the agent serves a single team. |
| `user` | Memories are isolated per user — useful when each user has private context. |
| `disabled` | The agent does not persist memory between conversations. |
See [Memories](/admin/ai/memory-isolation) for details on how memories are stored and used.
## Customize the agent
Define instructions that guide how the agent responds and analyzes data.
Provide a library of trusted SQL queries for the agent to reference.
Package reusable, named agent workflows that users can run on demand from chat.
Configure the agent to use your own LLM provider or model.
Control how the agent persists context across conversations and users.