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src/langbot/pkg/workflow/nodes/reply_message.py

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+"""Reply Message Node - reply to the triggering message
+
+Node metadata is loaded from: ../../templates/metadata/nodes/reply_message.yaml
+"""
+
+from __future__ import annotations
+
+import logging
+from typing import Any, ClassVar
+
+from ..entities import ExecutionContext
+from ..node import WorkflowNode, workflow_node, NodePort, NodeConfig
+
+logger = logging.getLogger(__name__)
+
+
+@workflow_node('reply_message')
+class ReplyMessageNode(WorkflowNode):
+    """Reply message node - reply to the triggering message"""
+
+    type_name = "reply_message"
+    category = "action"
+    icon = "↩️"
+    name = "reply_message"
+    description = "reply_message"
+    name_zh = "回复消息"
+    name_en = "Reply Message"
+    description_zh = "回复触发工作流的消息"
+    description_en = "Reply to the message that triggered the workflow"
+
+    inputs: ClassVar[list[NodePort]] = []
+    outputs: ClassVar[list[NodePort]] = []
+    config_schema: ClassVar[list[NodeConfig]] = []
+
+    async def execute(self, inputs: dict[str, Any], context: ExecutionContext) -> dict[str, Any]:
+        message = inputs.get("message")
+        if message in (None, ""):
+            message = inputs.get("input")
+        if message in (None, ""):
+            message = inputs.get("response")
+        if message in (None, "") and context.message_context:
+            message = context.message_context.message_content
+        if message is None:
+            message = ""
+
+        template = self.get_config("message_template")
+
+        if template:
+            message = template
+            for key, value in inputs.items():
+                message = message.replace(f"{{{{{key}}}}}", str(value))
+            for key, value in context.variables.items():
+                message = message.replace(f"{{{{variables.{key}}}}}", str(value))
+
+        logger.info(
+            "ReplyMessageNode resolved message",
+            extra={
+                'node_id': self.node_id,
+                'execution_id': context.execution_id,
+                'input_keys': list(inputs.keys()),
+                'message_preview': str(message)[:200],
+                'has_template': bool(template),
+                'session_id': context.session_id,
+            },
+        )
+
+        if not str(message).strip():
+            logger.warning(
+                "ReplyMessageNode has empty message after resolution",
+                extra={
+                    'node_id': self.node_id,
+                    'execution_id': context.execution_id,
+                    'input_keys': list(inputs.keys()),
+                },
+            )
+
+        # 实际发送消息
+        if self.ap:
+            from langbot_plugin.api.entities.builtin.platform.message import MessageChain, Plain
+            message_chain = MessageChain([Plain(text=str(message))])
+            await self.ap.platform_mgr.websocket_proxy_bot.adapter.send_message(
+                target_type='person',
+                target_id=f'websocket_{context.session_id}',
+                message=message_chain,
+            )
+        else:
+            logger.warning(
+                "ReplyMessageNode missing application instance",
+                extra={
+                    'node_id': self.node_id,
+                    'execution_id': context.execution_id,
+                },
+            )
+
+        return {"status": "sent", "message_id": f"reply_{context.execution_id}"}