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

# Converse Modes

> Map in-app Ask / Extended / Execute to config.agent_model and chat_mode on Converse.

In the **Datagrid web app**, chat uses three modes—**Ask**, **Extended**, and **Execute**—which correspond to the Converse **`chat_mode`** field (`llm_router`, `light_agent`, `full_agent`). This page documents **`config.agent_model`**, which selects the model implementation and which tools are allowed.

**Structured outputs:** For any **`agent_model`**, you can request JSON that matches a schema by passing **`text.format`** (JSON Schema) on the Converse request. The same mechanism applies across modes; tool limits below still apply.

**Important:** The **Ask** mode in the web app is the **`llm_router`** `chat_mode`, not `magpie-1.1-flash`. The **`magpie-1.1-flash`** model aligns with **Extended** in the app (search-backed, lighter agent). Use both `chat_mode` and `agent_model` when reproducing in-app behavior from the API.

## Ask (in-app; `chat_mode: llm_router`)

**Ask** is a **product / routing mode**, not a value of **`config.agent_model`**. In the web app it is selected with **`chat_mode: llm_router`**.

**What it is good for:** Fast, LLM-forward answers when the product has already chosen an agent for instructions and context. The server resolves routing (including agent context), then follows an LLM-focused path rather than full **Execute**-style multi-tool planning.

**How it differs from `llm-only`:** **`llm-only`** is an explicit **`agent_model`** on the Converse API: you get the direct LLM tier with **no tool execution** and predictable behavior from that string alone. **`llm_router`** instead means “use the in-app Ask routing rules” (agent resolution, mode refinement, default models) on top of whatever **`agent_model`** and **`agent_id`** you pass. To mirror **Ask** from the API, set **`chat_mode`** to **`llm_router`** and the same agent identifiers you use in the app; do not assume **`agent_model: llm-only`** alone reproduces **Ask**, and do not confuse **`llm_router`** with **Extended** (**`light_agent`** / **`magpie-1.1-flash`**).

Structured outputs for turns that use **`llm_router`** still use **`text.format`** like any other Converse call.

## Execute (full agent models)

Full agent with multi-step planning, reasoning, and broad tool execution. Matches **Execute** in the Datagrid web app (`chat_mode: full_agent`). This is the default when `agent_model` is omitted.

| `agent_model` | Description                                                                                                      |
| ------------- | ---------------------------------------------------------------------------------------------------------------- |
| `magpie-2.0`  | **Default.** Full agent model with proactive planning and reasoning.                                             |
| `magpie-2.5`  | Beta. Latest full-agent model — faster, more adaptable, and built to handle a broader range of real-world tasks. |
| `magpie-1.1`  | Previous-generation full agent model.                                                                            |

All tools listed for agents are available for **Execute**-tier models. Structured outputs use `text.format` (see [Structured outputs](./structured-outputs)).

<CodeGroup>
  ```python Python theme={null}
  response = datagrid.converse(
      prompt="Analyze my sales data and create a summary report",
      config={
          "agent_model": "magpie-2.0",
          "tools": ["data_analysis", "semantic_search", "create_dataset"]
      }
  )
  ```

  ```javascript JavaScript theme={null}
  const response = await datagrid.converse({
      prompt: "Analyze my sales data and create a summary report",
      config: {
          agent_model: "magpie-2.0",
          tools: ["data_analysis", "semantic_search", "create_dataset"],
      },
  });
  ```
</CodeGroup>

## Extended (search-focused agent)

Lightweight turns optimized for RAG (retrieval-augmented generation). Matches **Extended** in the Datagrid web app (`chat_mode: light_agent`). Faster than **Execute**-tier models with lower latency.

| `agent_model`      | Description                                               |
| ------------------ | --------------------------------------------------------- |
| `magpie-1.1-flash` | Fast model that only supports the `semantic_search` tool. |

Only the `semantic_search` tool is supported for **`magpie-1.1-flash`**. Requests specifying other tools will be rejected. Structured outputs use **`text.format`** like other models (see [Structured outputs](./structured-outputs)).

<CodeGroup>
  ```python Python theme={null}
  response = datagrid.converse(
      prompt="What is our refund policy?",
      config={
          "agent_model": "magpie-1.1-flash",
          "tools": ["semantic_search"]
      }
  )
  ```

  ```javascript JavaScript theme={null}
  const response = await datagrid.converse({
      prompt: "What is our refund policy?",
      config: {
          agent_model: "magpie-1.1-flash",
          tools: ["semantic_search"],
      },
  });
  ```
</CodeGroup>

## Direct LLM (`llm-only`)

Direct LLM response with no planning or tool execution. Lowest latency, best for simple conversational or structured JSON answers that do not need retrieval or actions.

| `agent_model` | Description                                 |
| ------------- | ------------------------------------------- |
| `llm-only`    | Direct LLM conversation with no tool calls. |

**`llm-only`** is the API’s explicit tool-free model key. It is **not** the same thing as selecting **Ask** in the web app: **Ask** is **`chat_mode: llm_router`** (see the **Ask** section at the top of this page).

No tools are executed for **`llm-only`**. Requests specifying tools will be rejected. Structured outputs use **`text.format`** (see [Structured outputs](./structured-outputs)).

<CodeGroup>
  ```python Python theme={null}
  response = datagrid.converse(
      prompt="Summarize the key differences between GAAP and IFRS",
      config={
          "agent_model": "llm-only"
      }
  )
  ```

  ```javascript JavaScript theme={null}
  const response = await datagrid.converse({
      prompt: "Summarize the key differences between GAAP and IFRS",
      config: {
          agent_model: "llm-only",
      },
  });
  ```
</CodeGroup>

## Choosing a mode

| Tier (in-app label) | API surface                                               | Use when                                                            | Latency | Tools                       | Structured outputs |
| ------------------- | --------------------------------------------------------- | ------------------------------------------------------------------- | ------- | --------------------------- | ------------------ |
| **Ask**             | **`chat_mode: llm_router`** (not an `agent_model` string) | Routed LLM-first answers with agent context in the product          | Lower   | Per routing / resolved path | Yes                |
| **Execute**         | `magpie-2.0`, `magpie-2.5`, `magpie-1.1`                  | Multi-step reasoning, tool calls, or data analysis                  | Higher  | All                         | Yes                |
| **Extended**        | `magpie-1.1-flash`                                        | Fast answers from knowledge bases (RAG) with `semantic_search` only | Medium  | `semantic_search` only      | Yes                |
| **Direct LLM**      | `llm-only`                                                | Tool-free conversational or structured JSON from a fixed model key  | Lowest  | None                        | Yes                |

When `config.agent_model` is omitted, the API defaults to `magpie-2.0` (**Execute** tier).