_process_decision() — langchain Function Reference

Architecture documentation for the _process_decision() function in human_in_the_loop.py from the langchain codebase.

Function python LangChainCore ApiManagement called by 1

Entity Profile

LangChainCore→ ApiManagement→ _process_decision() — langchain Function Reference

Dependency Diagram

graph TD
  786034cd_4c3c_2a16_2580_fdaf6714c856["_process_decision()"]
  b706912e_28f0_afbf_eb10_723aa3e74c52["HumanInTheLoopMiddleware"]
  786034cd_4c3c_2a16_2580_fdaf6714c856 -->|defined in| b706912e_28f0_afbf_eb10_723aa3e74c52
  c27d424a_40fd_dcec_b4d0_8dbf62b73ff2["after_model()"]
  c27d424a_40fd_dcec_b4d0_8dbf62b73ff2 -->|calls| 786034cd_4c3c_2a16_2580_fdaf6714c856
  style 786034cd_4c3c_2a16_2580_fdaf6714c856 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/langchain_v1/langchain/agents/middleware/human_in_the_loop.py lines 247–286

    def _process_decision(
        decision: Decision,
        tool_call: ToolCall,
        config: InterruptOnConfig,
    ) -> tuple[ToolCall | None, ToolMessage | None]:
        """Process a single decision and return the revised tool call and optional tool message."""
        allowed_decisions = config["allowed_decisions"]

        if decision["type"] == "approve" and "approve" in allowed_decisions:
            return tool_call, None
        if decision["type"] == "edit" and "edit" in allowed_decisions:
            edited_action = decision["edited_action"]
            return (
                ToolCall(
                    type="tool_call",
                    name=edited_action["name"],
                    args=edited_action["args"],
                    id=tool_call["id"],
                ),
                None,
            )
        if decision["type"] == "reject" and "reject" in allowed_decisions:
            # Create a tool message with the human's text response
            content = decision.get("message") or (
                f"User rejected the tool call for `{tool_call['name']}` with id {tool_call['id']}"
            )
            tool_message = ToolMessage(
                content=content,
                name=tool_call["name"],
                tool_call_id=tool_call["id"],
                status="error",
            )
            return tool_call, tool_message
        msg = (
            f"Unexpected human decision: {decision}. "
            f"Decision type '{decision.get('type')}' "
            f"is not allowed for tool '{tool_call['name']}'. "
            f"Expected one of {allowed_decisions} based on the tool's configuration."
        )
        raise ValueError(msg)