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.

Default mode: New chats and omitted/default chat_mode run as Execute (full_agent) with the default agent_model: magpie-2.5, unless you explicitly set a different supported agent_model.

Auto mode: chat_mode: auto is still accepted for compatibility, but currently runs as Execute (full_agent). It does not predict Ask, Extended, or Execute per message.

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.

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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.

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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 for new chats and omitted/default chat_mode; when agent_model is omitted, Execute uses magpie-2.5.

agent_model	Description
magpie-2.0	Legacy full-agent model with proactive planning and reasoning.
magpie-2.5	Default. 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).

Python

response = datagrid.converse(
    prompt="Analyze my sales data and create a summary report",
    config={
        "agent_model": "magpie-2.5",
        "tools": ["data_analysis", "semantic_search", "create_dataset"]
    }
)

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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).

Python

response = datagrid.converse(
    prompt="What is our refund policy?",
    config={
        "agent_model": "magpie-1.1-flash",
        "tools": ["semantic_search"]
    }
)

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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).

Python

response = datagrid.converse(
    prompt="Summarize the key differences between GAAP and IFRS",
    config={
        "agent_model": "llm-only"
    }
)

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Beta (magpie-3.0)

BETA: Magpie 3.0. Behavior and schema may change.

config.agent_model: "magpie-3.0" selects Magpie 3.0 on the public Converse API. The request runs Magpie 3.0 whether or not Magpie 3.0 is enabled for that user in the Datagrid web app. It is not an Ask, Extended, or Execute model.

Structured outputs use text.format (see Structured outputs).

Python

response = datagrid.converse(
    prompt="Summarize open RFIs and the drawings they reference",
    config={
        "agent_model": "magpie-3.0"
    }
)

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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	Default; chat_mode: full_agent; magpie-2.5 when agent_model is omitted	Multi-step reasoning, tool calls, or data analysis	Higher	All	Yes
Auto	chat_mode: auto	Compatibility value that currently runs as Execute (full_agent)	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
Beta	magpie-3.0	BETA. Magpie 3.0 on the public Converse API. Behavior and schema may change.	Higher	Magpie 3.0 tools	Yes

When config.agent_model is omitted, the API defaults to magpie-2.5 (Execute tier).