لدي سير عمل دردشة بسيط قمت بنسخه من صفحة النموذج:
<
{
“name”: “Chat with local LLMs using n8n and Ollama”,
“nodes”: [
{
“parameters”: {
“options”: {}
},
“id”: “475385fa-28f3-45c4-bd1a-10dde79f74f2”,
“name”: “When chat message received”,
“type”: “@n8n/n8n-nodes-langchain.chatTrigger”,
“position”: [
912,
624
],
“webhookId”: “ebdeba3f-6b4f-49f3-ba0a-8253dd226161”,
“typeVersion”: 1.1
},
{
“parameters”: {
“options”: {}
},
“id”: “61133dc6-dcd9-44ff-85f2-5d8cc2ce813e”,
“name”: “Ollama Chat Model”,
“type”: “@n8n/n8n-nodes-langchain.lmChatOllama”,
“position”: [
1104,
784
],
“typeVersion”: 1,
“credentials”: {
“ollamaApi”: {
“id”: “lCtwNqRXjkJytDLf”,
“name”: “Ollama Test”
}
}
},
{
“parameters”: {
“content”: “## Chat with local LLMs using n8n and Ollama\nThis n8n workflow allows you to seamlessly interact with your self-hosted Large Language Models (LLMs) through a user-friendly chat interface. By connecting to Ollama, a powerful tool for managing local LLMs, you can send prompts and receive AI-generated responses directly within n8n.\n\n### How it works\n1. When chat message received: Captures the user’s input from the chat interface.\n2. Chat LLM Chain: Sends the input to the Ollama server and receives the AI-generated response.\n3. Delivers the LLM’s response back to the chat interface.\n\n### Set up steps\n* Make sure Ollama is installed and running on your machine before executing this workflow.\n* Edit the Ollama address if different from the default.\n”,
“height”: 473,
“width”: 485
},
“id”: “3e89571f-7c87-44c6-8cfd-4903d5e1cdc5”,
“name”: “Sticky Note”,
“type”: “n8n-nodes-base.stickyNote”,
“position”: [
368,
240
],
“typeVersion”: 1
},
{
“parameters”: {
“content”: “## Ollama setup\n* Connect to your local Ollama, usually on http://localhost:11434\n* If running in Docker, make sure that the n8n container has access to the host’s network in order to connect to Ollama. You can do this by passing --net=host option when starting the n8n Docker container”,
“height”: 258,
“width”: 368,
“color”: 6
},
“id”: “9345cadf-a72e-4d3d-b9f0-d670744065fe”,
“name”: “Sticky Note1”,
“type”: “n8n-nodes-base.stickyNote”,
“position”: [
1280,
800
],
“typeVersion”: 1
},
{
“parameters”: {},
“id”: “eeffdd4e-6795-4ebc-84f7-87b5ac4167d9”,
“name”: “Chat LLM Chain”,
“type”: “@n8n/n8n-nodes-langchain.chainLlm”,
“position”: [
1136,
624
],
“typeVersion”: 1.4
}
],
“pinData”: {},
“connections”: {
“Ollama Chat Model”: {
“ai_languageModel”: [
[
{
“node”: “Chat LLM Chain”,
“type”: “ai_languageModel”,
“index”: 0
}
]
]
},
“When chat message received”: {
“main”: [
[
{
“node”: “Chat LLM Chain”,
“type”: “main”,
“index”: 0
}
]
]
}
},
“active”: false,
“settings”: {
“executionOrder”: “v1”,
“binaryMode”: “separate”,
“availableInMCP”: false
},
“versionId”: “4175a286-4d6a-42a5-915e-f8855614221f”,
“meta”: {
“templateId”: “2384”,
“templateCredsSetupCompleted”: true,
“instanceId”: “92d82d8eddeb75c1632295d367de7c0a28a1a65bbe8e484bc9236a3b35962a42”
},
“nodeGroups”: ,
“id”: “rR55c5eeONtyLGm9”,
“tags”:
}
/>
أنا أستخدم Ollama على http://192.168.2.145:11434. نموذج اللغة الذي أستخدمه هو llama3.2:latest.
للأسف، عندما أقوم بتشغيل سير العمل، بغض النظر عما أدخله في الدردشة، أحصل على
الخطأ التالي:
Error: Failed to receive response
عندما أتحقق من مخرجات مكون الدردشة، أرى «no chat output». وبطبيعة الحال، لا توجد
بيانات إدخال يتم استقبالها بواسطة مكون «Chat LLM Chain».
كان هناك منشور آخر حيث لم يتمكن الشخص من استقبال رد باستخدام مكون الدردشة.
الحل كان إعداد عنوان URL محرر النصوص:
- N8N_EDITOR_BASE_URL=http://localhost:5678
- WEBHOOK_URL=http://localhost:5678/
حاولت ذلك. لم ينجح.
هل هناك خطأ ما في مكون الدردشة؟ أم أنني أفتقد شيئًا في إعدادات
المكونات؟
يرجى نصحي بأي شخص.
