this img show you empty problem
how can i add to output of qdrant this things from points of document:
text
id
title
or other things …
edit this?
but how?
{
“should”: [
{
“key”: “metadata.batch”,
“match”: {
“value”: 12345
}
}
]
}
workflow:
{
“nodes”: [
{
“parameters”: {},
“type”: “@n8n/n8n-nodes-langchain.memoryBufferWindow”,
“typeVersion”: 1.3,
“position”: [
-380,
-1100
],
“id”: “ab2a1a68-8c8f-4cb5-a1ee-7487656f2202”,
“name”: “Simple Memory”
},
{
“parameters”: {
“hasOutputParser”: true,
“options”: {
“systemMessage”: “Answer the user questions based on qdrant information”
}
},
“type”: “@n8n/n8n-nodes-langchain.agent”,
“typeVersion”: 1.8,
“position”: [
-480,
-1340
],
“id”: “2dcc86e7-1ce2-4d48-9762-f43a70173142”,
“name”: “AI Agent1”
},
{
“parameters”: {
“public”: true,
“options”: {}
},
“type”: “@n8n/n8n-nodes-langchain.chatTrigger”,
“typeVersion”: 1.1,
“position”: [
-1440,
-700
],
“id”: “a6b82b4b-148d-4b20-b9cb-01dc3ee776f9”,
“name”: “When chat message received”,
“webhookId”: “04c2097c-9210-467e-b862-4a7e75e68b3e”
},
{
“parameters”: {
“name”: “Qdrant”,
“description”: “about RAG system”
},
“type”: “@n8n/n8n-nodes-langchain.toolVectorStore”,
“typeVersion”: 1,
“position”: [
-140,
-1140
],
“id”: “a44b451f-cb32-41b7-9c40-9b63a29e6980”,
“name”: “Answer questions with a vector store”
},
{
“parameters”: {
“qdrantCollection”: {
“__rl”: true,
“value”: “test1”,
“mode”: “list”,
“cachedResultName”: “test1”
},
“options”: {
“searchFilterJson”: “{\n "should": [\n {\n "key": "metadata.batch",\n "match": {\n "value": 12345\n }\n }\n ]\n}”
}
},
“type”: “@n8n/n8n-nodes-langchain.vectorStoreQdrant”,
“typeVersion”: 1,
“position”: [
-200,
-940
],
“id”: “09c30e7a-4338-4fe8-a6a6-7bf5e50bede7”,
“name”: “Qdrant Vector Store”,
“credentials”: {
“qdrantApi”: {
“id”: “He3E1WGvX5IEp25K”,
“name”: “QdrantApi account”
}
}
},
{
“parameters”: {
“model”: “google/gemini-2.0-flash-001”,
“options”: {
“topP”: 0.7
}
},
“type”: “@n8n/n8n-nodes-langchain.lmChatOpenRouter”,
“typeVersion”: 1,
“position”: [
-520,
-1100
],
“id”: “a30ecb23-aa0b-4e07-afda-dc34a60db003”,
“name”: “OpenRouter Chat Model”,
“credentials”: {
“openRouterApi”: {
“id”: “SrothWP8ZIbXWABF”,
“name”: “OpenRouter account”
}
}
},
{
“parameters”: {
“model”: “google/gemini-2.0-flash-001”,
“options”: {
“topP”: 0.7
}
},
“type”: “@n8n/n8n-nodes-langchain.lmChatOpenRouter”,
“typeVersion”: 1,
“position”: [
200,
-980
],
“id”: “3e7a901c-d275-47cc-b62c-7bd74710f3ae”,
“name”: “OpenRouter Chat Model2”,
“credentials”: {
“openRouterApi”: {
“id”: “SrothWP8ZIbXWABF”,
“name”: “OpenRouter account”
}
}
},
{
“parameters”: {
“modelName”: “sentence-transformers/all-MiniLM-L6-v2”,
“options”: {}
},
“type”: “@n8n/n8n-nodes-langchain.embeddingsHuggingFaceInference”,
“typeVersion”: 1,
“position”: [
-360,
-780
],
“id”: “2929653e-7b8c-4f68-b11f-db68ab8344c1”,
“name”: “Embeddings HuggingFace Inference”,
“credentials”: {
“huggingFaceApi”: {
“id”: “nsIxWXYouOPfI9xG”,
“name”: “HuggingFaceApi account”
}
}
}
],
“connections”: {
“Simple Memory”: {
“ai_memory”: [
[
{
“node”: “AI Agent1”,
“type”: “ai_memory”,
“index”: 0
}
]
]
},
“When chat message received”: {
“main”: [
[
{
“node”: “AI Agent1”,
“type”: “main”,
“index”: 0
}
]
]
},
“Answer questions with a vector store”: {
“ai_tool”: [
[
{
“node”: “AI Agent1”,
“type”: “ai_tool”,
“index”: 0
}
]
]
},
“Qdrant Vector Store”: {
“ai_vectorStore”: [
[
{
“node”: “Answer questions with a vector store”,
“type”: “ai_vectorStore”,
“index”: 0
}
]
],
“ai_tool”: [
]
},
“OpenRouter Chat Model”: {
“ai_languageModel”: [
[
{
“node”: “AI Agent1”,
“type”: “ai_languageModel”,
“index”: 0
}
]
]
},
“OpenRouter Chat Model2”: {
“ai_languageModel”: [
[
{
“node”: “Answer questions with a vector store”,
“type”: “ai_languageModel”,
“index”: 0
}
]
]
},
“Embeddings HuggingFace Inference”: {
“ai_embedding”: [
[
{
“node”: “Qdrant Vector Store”,
“type”: “ai_embedding”,
“index”: 0
}
]
]
}
},
“pinData”: {},
“meta”: {
“templateCredsSetupCompleted”: true,
“instanceId”: “08a08bd53266df01a99dce46f993f25ac7318116ddc747a568f09a82a2d35d3d”
}
}