استفاده از n8n

برای استفاده از n8n با سرویس هوش مصنوعی آروان‌کلاد و Langchain می‌توانید از نمونه‌کدهای زیر کمک بگیرید:

Python

شیوه اجرا:

Pip install langchain langchain-openai langchain-core
Python main.py

نمونه کد:

from langchain_openai import ChatOpenAI
from langchain_core.messages import HumanMessage


# Set up the LangChain ChatOpenAI with custom base URL and API key
llm = ChatOpenAI(
    api_key="apikey ...",
    base_url="https://arvancloudai.ir/gateway/models/Gemini-2.5-Pro/.../v1",
    model="Gemini-2.5-Pro",
    max_tokens=10000,
    temperature=0.8,
)


# Create a human message
messages = [HumanMessage(content="tell me a joke about product managers")]


# Invoke the model
response = llm.invoke(messages)


print(response)

Golang

شیوه اجرا:

Go mod tidy
Go run main.go

نمونه کد:

package main


import (
  "context"
  "fmt"
  "log"


  "github.com/tmc/langchaingo/llms"
  "github.com/tmc/langchaingo/llms/openai"
)


func main() {
  // Create LangChain OpenAI LLM with custom base URL and API key
  llm, err := openai.New(
    openai.WithToken("apikey ..."),
    openai.WithBaseURL("https://arvancloudai.ir/gateway/models/Gemini-2.5-Pro/.../v1"),
    openai.WithModel("Gemini-2.5-Pro"),
  )
  if err != nil {
    log.Fatalf("Failed to create OpenAI LLM: %v", err)
  }


  // Create context
  ctx := context.Background()


  // Create message content
  content := "tell me a joke about product managers"


  // Generate response using LangChain
  response, err := llms.GenerateFromSinglePrompt(
    ctx,
    llm,
    content,
    llms.WithTemperature(0.8),
    llms.WithMaxTokens(10000),
  )
  if err != nil {
    log.Fatalf("Failed to generate response: %v", err)
  }


  fmt.Printf("Response: %s\n", response)


  // Alternative: Using the Call method directly with prompt
  callResponse, err := llm.Call(
    ctx,
    content,
    llms.WithTemperature(0.8),
    llms.WithMaxTokens(10000),
  )
  if err != nil {
    log.Fatalf("Failed to call LLM: %v", err)
  }


  fmt.Printf("Call Response: %s\n", callResponse)
}

TypeScript

فایل package.json:

{
  "name": "ai-chat-langchain-client",
  "version": "1.0.0",
  "description": "TypeScript LangChain LLM chat client",
  "main": "main.ts",
  "scripts": {
    "start": "ts-node main.ts",
    "build": "tsc main.ts",
    "dev": "ts-node-dev main.ts"
  },
  "dependencies": {
    "@langchain/openai": "^0.3.11",
    "@langchain/core": "^0.3.18",
    "langchain": "^0.3.6"
  },
  "devDependencies": {
    "@types/node": "^22.12.0",
    "ts-node": "^10.9.2",
    "ts-node-dev": "^2.0.0",
    "typescript": "^5.5.4"
  }
}

نمونه کد:

import { ChatOpenAI } from "@langchain/openai";
import { HumanMessage } from "@langchain/core/messages";


async function main() {
  try {
    // Create LangChain ChatOpenAI with custom base URL and API key
    const llm = new ChatOpenAI({
      apiKey: "apikey ...",
      configuration: {
        baseURL: "https://arvancloudai.ir/gateway/models/Gemini-2.5-Pro/.../v1",
      },
      model: "Gemini-2.5-Pro",
      maxTokens: 10000,
      temperature: 0.8,
    });


    // Create a human message
    const messages = [new HumanMessage("tell me a joke about product managers")];


    // Invoke the model
    const response = await llm.invoke(messages);


    console.log("Response:", response.content);


  } catch (error) {
    console.error('Error:', error);
  }
}


main();

دستور زیر را اجرا کنید:

Npm start