Body:
Hi community,
I’m building a “Learning Assistant AI” and I’ve hit a wall. As you can see in the attached screenshot, my workflow seems to stop immediately after the ‘When chat message received’ node. It doesn’t trigger the ‘Chat Memory Manager’ or any subsequent nodes.
My Environment:
Instance: Self-hosted (Docker)
n8n Version: Version 2.17.5
Location: California, US
“I have configured the AI Agent with the following System Message to maintain a professional engineer-like persona. I’m wondering if this specific instruction set could be causing any timeout or execution issues between the Trigger and the Memory Manager.”
Describe the problem/error/question
What I’ve tried:
I clicked ‘Execute Workflow’ and sent a message through the ‘Open Chat’ button.
The chat window shows the session ID (1518c…), but the workflow editor doesn’t show any active data flow between the trigger and the memory manager.
I checked the connections, and they seem to be linked correctly.
What is the error message (if any)?
Please share your workflow
{
"nodes": [
{
"parameters": {
"promptType": "define",
"text": "={{ $json.chatInput }}",
"options": {
"systemMessage": "## Role & Identity
You are a professional AI Agent dedicated to assisting Jaden with business operations and client interactions.
## Communication Style & Learning
1. Observe and adopt Jaden's professional, concise, and engineer-oriented tone.
2. Avoid excessive flowery language; maintain a polite, practical, and reliable tone.
3. During this testing phase, immediately capture the context of any corrections made by Jaden and apply them to subsequent responses.
## Constraints (Anti-Hallucination)
1. **Fact-Only**: Never guess uncertain data. If information is unknown, respond with "This requires verification" and request Jaden’s intervention.
2. **Zero-Hallucination**: Do not invent non-existent models, specifications, or technical details.
3. **Conciseness**: Address the core of the question directly; exclude unnecessary introductions or conclusions.
## Human-in-the-Loop
- All drafts you generate will be reviewed by Jaden. Prioritize Jaden's feedback as the ultimate guideline."
}
},
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 3.1,
"position": [
368,
-16
],
"id": "5a715b71-9f13-49cd-8197-a1d11cb84207",
"name": "AI Agent"
},
{
"parameters": {
"modelName": "models/gemini-3.1-flash-lite-preview",
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"typeVersion": 1,
"position": [
288,
144
],
"id": "fd172cd7-9d19-43bd-9e2e-bb0c52c0ef05",
"name": "Google Gemini Chat Model",
"credentials": {
"googlePalmApi": {
"id": "N9b7DwaH3iHtq9fg",
"name": "Google Gemini(PaLM) Api account"
}
}
},
{
"parameters": {
"mode": "retrieve-as-tool",
"toolDescription": "이 도구는 과거에 Jaden과 대화하며 학습한 정답 데이터와 기술 가이드를 담고 있습니다. 고객의 질문에 답하기 전, 먼저 여기서 유사한 사례가 있는지 찾아보세요.",
"memoryKey": {
"__rl": true,
"mode": "list",
"value": "vector_store_key"
}
},
"type": "@n8n/n8n-nodes-langchain.vectorStoreInMemory",
"typeVersion": 1.3,
"position": [
432,
272
],
"id": "acf84bc7-336c-41c6-a538-b729872b88a9",
"name": "Simple Vector Store"
},
{
"parameters": {},
"type": "@n8n/n8n-nodes-langchain.embeddingsGoogleGemini",
"typeVersion": 1,
"position": [
496,
432
],
"id": "b2c71f4a-ca26-408d-b28d-abcfc98135a2",
"name": "Embeddings Google Gemini",
"credentials": {
"googlePalmApi": {
"id": "N9b7DwaH3iHtq9fg",
"name": "Google Gemini(PaLM) Api account"
}
}
},
{
"parameters": {
"contextWindowLength": 10
},
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"typeVersion": 1.3,
"position": [
256,
384
],
"id": "a3f49e97-0b15-4dc4-93b1-9185f5e6fcd3",
"name": "Simple Memory"
},
{
"parameters": {
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"typeVersion": 1.4,
"position": [
-160,
-16
],
"id": "21e62167-a5cd-42c1-9dbc-d8246008b5ea",
"name": "When chat message received",
"webhookId": "379902cc-7bfc-419b-8699-bc0783f3edc4"
},
{
"parameters": {
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.memoryManager",
"typeVersion": 1.1,
"position": [
32,
-16
],
"id": "1f77f7ac-ec00-4434-acb5-71a6f76f9fbd",
"name": "Chat Memory Manager"
}
],
"connections": {
"AI Agent": {
"main": [
[]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Simple Vector Store": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Embeddings Google Gemini": {
"ai_embedding": [
[
{
"node": "Simple Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Simple Memory": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"index": 0
},
{
"node": "Chat Memory Manager",
"type": "ai_memory",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "Chat Memory Manager",
"type": "main",
"index": 0
}
]
]
},
"Chat Memory Manager": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
}
},
"pinData": {},
"meta": {
"templateCredsSetupCompleted": true,
"instanceId": "5c6c7db12fc5c4b45387d3e63c704ebba8e8c2376e53c593366bf28f71b5a439"
}
}
Share the output returned by the last node
Information on your n8n setup
- n8n version:
- Database (default: SQLite):
- n8n EXECUTIONS_PROCESS setting (default: own, main):
- Running n8n via (Docker, npm, n8n cloud, desktop app):
- Operating system: