""" title: n8n Pipe Function author: Cole Medin author_url: https://www.youtube.com/@ColeMedin version: 0.1.0 This module defines a Pipe class that utilizes an N8N workflow for an Agent """ from typing import Optional, Callable, Awaitable from pydantic import BaseModel, Field import os import time import requests class Pipe: class Valves(BaseModel): n8n_url: str = Field( default="https://n8n.[your domain].com/webhook/[your webhook URL]" ) n8n_bearer_token: str = Field(default="...") input_field: str = Field(default="chatInput") response_field: str = Field(default="output") emit_interval: float = Field( default=2.0, description="Interval in seconds between status emissions" ) enable_status_indicator: bool = Field( default=True, description="Enable or disable status indicator emissions" ) def __init__(self): self.type = "pipe" self.id = "n8n_pipe" self.name = "N8N Pipe" self.valves = self.Valves() self.last_emit_time = 0 pass async def emit_status( self, __event_emitter__: Callable[[dict], Awaitable[None]], level: str, message: str, done: bool, ): current_time = time.time() if ( __event_emitter__ and self.valves.enable_status_indicator and ( current_time - self.last_emit_time >= self.valves.emit_interval or done ) ): await __event_emitter__( { "type": "status", "data": { "status": "complete" if done else "in_progress", "level": level, "description": message, "done": done, }, } ) self.last_emit_time = current_time async def pipe( self, body: dict, __user__: Optional[dict] = None, __event_emitter__: Callable[[dict], Awaitable[None]] = None, __event_call__: Callable[[dict], Awaitable[dict]] = None, ) -> Optional[dict]: await self.emit_status( __event_emitter__, "info", "/Calling N8N Workflow...", False ) messages = body.get("messages", []) # Verify a message is available if messages: question = messages[-1]["content"] if "Prompt: " in question: question = question.split("Prompt: ")[-1] try: # Invoke N8N workflow headers = { "Authorization": f"Bearer {self.valves.n8n_bearer_token}", "Content-Type": "application/json", } payload = {"sessionId": f"{__user__['id']} - {messages[0]['content'].split('Prompt: ')[-1][:100]}"} payload[self.valves.input_field] = question response = requests.post( self.valves.n8n_url, json=payload, headers=headers ) if response.status_code == 200: n8n_response = response.json()[self.valves.response_field] else: raise Exception(f"Error: {response.status_code} - {response.text}") # Set assitant message with chain reply body["messages"].append({"role": "assistant", "content": n8n_response}) except Exception as e: await self.emit_status( __event_emitter__, "error", f"Error during sequence execution: {str(e)}", True, ) return {"error": str(e)} # If no message is available alert user else: await self.emit_status( __event_emitter__, "error", "No messages found in the request body", True, ) body["messages"].append( { "role": "assistant", "content": "No messages found in the request body", } ) await self.emit_status(__event_emitter__, "info", "Complete", True) return n8n_response