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Extends `HumanInTheLoopMiddleware` with a new `respond` decision type
for "ask user" style tools — tools whose real implementation is the
human's response. The interrupt is raised with the tool call as usual;
the resume payload becomes the body of a synthetic `ToolMessage` with
`status="success"`, and the tool itself is not executed.
This complements `reject` (which produces a synthetic `ToolMessage` with
`status="error"`) by enabling the symmetric success path: a reviewer can
answer on the tool's behalf without invoking it.
## Changes
- New `RespondDecision` `TypedDict` with a required `message: str`
field; added to the `Decision` union.
- `"respond"` added to the `DecisionType` literal.
- `_process_decision` handles `"respond"` by emitting a `ToolMessage`
with `status="success"` and preserving the original tool call on the
`AIMessage` so provider-required tool-call/tool-message pairing is
maintained.
- The `True` shortcut in `interrupt_on` now expands to `["approve",
"edit", "reject", "respond"]`, so existing callers that opted into "all
decisions" pick up the new capability without code changes. The `reject`
decision already permits a reviewer to inject arbitrary `ToolMessage`
content, so `respond` extends the same trust model — not a new
capability class.
## Example
```python
from langchain.agents.middleware import HumanInTheLoopMiddleware
middleware = HumanInTheLoopMiddleware(
interrupt_on={"ask_user": {"allowed_decisions": ["respond"]}}
)
# Resume payload: {"decisions": [{"type": "respond", "message": "blue"}]}
# → synthetic ToolMessage(content="blue", status="success") for `ask_user`.
```
---
*Implementation drafted with AI-agent assistance.*
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>