The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"name": "LLM Testing",
"nodes": [
{
"parameters": {
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"typeVersion": 1.1,
"position": [
-380,
540
],
"id": "5792dafb-f847-492f-869a-d2228f816bd6",
"name": "When chat message received"
},
{
"parameters": {
"name": "nvidia",
"description": "retrieves data about nvidia earnings report"
},
"type": "@n8n/n8n-nodes-langchain.toolVectorStore",
"typeVersion": 1,
"position": [
560,
180
],
"id": "6960ff1b-218f-4ce7-b26f-f1ea2cddb8fb",
"name": "nvidia"
},
{
"parameters": {
"pineconeIndex": {
"__rl": true,
"value": "sample",
"mode": "list",
"cachedResultName": "sample"
},
"options": {
"pineconeNamespace": "nvidia"
}
},
"type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
"typeVersion": 1,
"position": [
860,
180
],
"id": "2c0b680b-6f42-44d5-b07a-f27ee7c0d04e",
"name": "Pinecone Vector Store",
"credentials": {
"pineconeApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"name": "nvidia",
"description": "retrieves data about nvidia earnings report"
},
"type": "@n8n/n8n-nodes-langchain.toolVectorStore",
"typeVersion": 1,
"position": [
560,
520
],
"id": "7e6879d3-de58-45d1-baba-28789fe1b262",
"name": "nvidia1"
},
{
"parameters": {
"pineconeIndex": {
"__rl": true,
"value": "sample",
"mode": "list",
"cachedResultName": "sample"
},
"options": {
"pineconeNamespace": "nvidia"
}
},
"type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
"typeVersion": 1,
"position": [
860,
520
],
"id": "d34166ae-c985-422d-994b-bca22c0b416c",
"name": "Pinecone Vector Store1",
"credentials": {
"pineconeApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
"typeVersion": 1.2,
"position": [
880,
680
],
"id": "87303ce2-7cd0-4568-a395-9b6add58ce33",
"name": "Embeddings OpenAI1",
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"model": "gpt-4o",
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1.1,
"position": [
200,
700
],
"id": "7d338a2b-c8d5-401c-a094-81ed74e5e014",
"name": "GPT-4o",
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
"typeVersion": 1.2,
"position": [
880,
360
],
"id": "4c174591-543c-4a72-9f5f-9c6cb1565344",
"name": "Embeddings OpenAI",
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
"typeVersion": 1.2,
"position": [
180,
360
],
"id": "33ad68d1-790f-467e-82be-d15cfebff7e9",
"name": "Claude 3.5 Sonnet",
"credentials": {
"anthropicApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"options": {
"systemMessage": "=# Overview \nYou are an AI agent responsible for retrieving and summarizing NVIDIA's financial and earnings information. \n\n## Context \n- The agent uses the \"nvidia\" tool to access up-to-date data on NVIDIA's financials, including revenue, earnings, and market performance. \n- Responses should be concise, accurate, and focused on the requested metrics or insights. \n\n## Instructions \n1. Identify the specific financial metric or information requested by the user. \n2. Query the \"nvidia\" tool for the relevant data. \n3. Summarize the findings in a clear and professional manner. \n\n## Tools \n- NVIDIA financials and earnings tool (\"nvidia\"). \n\n## Examples \n- Input: \"Provide NVIDIA's Q4 earnings report summary.\" \n- Output: \"NVIDIA's Q4 earnings were $2.5 billion, with a 12% year-over-year growth. Revenue was $8.3 billion.\" \n\n- Input: \"What was NVIDIA's revenue in the last fiscal year?\" \n- Output: \"NVIDIA's revenue for the last fiscal year was $33 billion, marking a 20% increase from the previous year.\" \n\n## SOP (Standard Operating Procedure) \n1. Parse the user's query to determine the specific financial details required. \n2. Use the \"nvidia\" tool to retrieve the latest data. \n3. Cross-check and verify the data for accuracy. \n4. Provide a concise summary in response to the user's query. \n\n## Final Notes \n- Always ensure the data is current and relevant to the query. \n- Avoid speculation; report only factual information retrieved from the \"nvidia\" tool. \n"
}
},
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.7,
"position": [
180,
500
],
"id": "b4328a17-373c-462d-bca3-fb9314598177",
"name": "GPT-4o Agent"
},
{
"parameters": {
"options": {
"systemMessage": "=# Overview \nYou are an AI agent responsible for retrieving and summarizing NVIDIA's financial and earnings information. \n\n## Context \n- The agent uses the \"nvidia\" tool to access up-to-date data on NVIDIA's financials, including revenue, earnings, and market performance. \n- Responses should be concise, accurate, and focused on the requested metrics or insights. \n\n## Instructions \n1. Identify the specific financial metric or information requested by the user. \n2. Query the \"nvidia\" tool for the relevant data. \n3. Summarize the findings in a clear and professional manner. \n\n## Tools \n- NVIDIA financials and earnings tool (\"nvidia\"). \n\n## Examples \n- Input: \"Provide NVIDIA's Q4 earnings report summary.\" \n- Output: \"NVIDIA's Q4 earnings were $2.5 billion, with a 12% year-over-year growth. Revenue was $8.3 billion.\" \n\n- Input: \"What was NVIDIA's revenue in the last fiscal year?\" \n- Output: \"NVIDIA's revenue for the last fiscal year was $33 billion, marking a 20% increase from the previous year.\" \n\n## SOP (Standard Operating Procedure) \n1. Parse the user's query to determine the specific financial details required. \n2. Use the \"nvidia\" tool to retrieve the latest data. \n3. Cross-check and verify the data for accuracy. \n4. Provide a concise summary in response to the user's query. \n\n## Final Notes \n- Always ensure the data is current and relevant to the query. \n- Avoid speculation; report only factual information retrieved from the \"nvidia\" tool. \n"
}
},
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.7,
"position": [
180,
160
],
"id": "0ecbf39d-1212-4ee2-857a-bd2da1cab29b",
"name": "Claude 3.5 Sonnet Agent"
},
{
"parameters": {
"name": "nvidia",
"description": "retrieves data about nvidia earnings report"
},
"type": "@n8n/n8n-nodes-langchain.toolVectorStore",
"typeVersion": 1,
"position": [
560,
860
],
"id": "a533d282-f346-4830-8da4-f323c9659f61",
"name": "nvidia2"
},
{
"parameters": {
"pineconeIndex": {
"__rl": true,
"value": "sample",
"mode": "list",
"cachedResultName": "sample"
},
"options": {
"pineconeNamespace": "nvidia"
}
},
"type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
"typeVersion": 1,
"position": [
860,
860
],
"id": "2717272f-77af-44b2-9bd8-16acf5994227",
"name": "Pinecone Vector Store2",
"credentials": {
"pineconeApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
"typeVersion": 1.2,
"position": [
880,
1020
],
"id": "738be7f8-3fc5-4603-bd32-e0281b0629d9",
"name": "Embeddings OpenAI2",
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"options": {
"systemMessage": "=# Overview \nYou are an AI agent responsible for retrieving and summarizing NVIDIA's financial and earnings information. \n\n## Context \n- The agent uses the \"nvidia\" tool to access up-to-date data on NVIDIA's financials, including revenue, earnings, and market performance. \n- Responses should be concise, accurate, and focused on the requested metrics or insights. \n\n## Instructions \n1. Identify the specific financial metric or information requested by the user. \n2. Query the \"nvidia\" tool for the relevant data. \n3. Summarize the findings in a clear and professional manner. \n\n## Tools \n- NVIDIA financials and earnings tool (\"nvidia\"). \n\n## Examples \n- Input: \"Provide NVIDIA's Q4 earnings report summary.\" \n- Output: \"NVIDIA's Q4 earnings were $2.5 billion, with a 12% year-over-year growth. Revenue was $8.3 billion.\" \n\n- Input: \"What was NVIDIA's revenue in the last fiscal year?\" \n- Output: \"NVIDIA's revenue for the last fiscal year was $33 billion, marking a 20% increase from the previous year.\" \n\n## SOP (Standard Operating Procedure) \n1. Parse the user's query to determine the specific financial details required. \n2. Use the \"nvidia\" tool to retrieve the latest data. \n3. Cross-check and verify the data for accuracy. \n4. Provide a concise summary in response to the user's query. \n\n## Final Notes \n- Always ensure the data is current and relevant to the query. \n- Avoid speculation; report only factual information retrieved from the \"nvidia\" tool. \n"
}
},
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.7,
"position": [
160,
840
],
"id": "1db0a232-fb95-4c1a-a900-2f44767ae90a",
"name": "GPT-4o Agent1"
},
{
"parameters": {
"modelName": "models/gemini-2.0-flash-exp",
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"typeVersion": 1,
"position": [
160,
1040
],
"id": "9f08f95b-0a10-4754-9d1d-60b807680dc9",
"name": "Gemini Flash 2.0",
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"modelName": "models/gemini-2.0-flash-exp",
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"typeVersion": 1,
"position": [
620,
1040
],
"id": "fabe7920-1c92-4ce5-80b1-8cf869d576eb",
"name": "Gemini Flash 2.0_",
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"model": "gpt-4o",
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1.1,
"position": [
580,
700
],
"id": "d2e13319-85c0-48c6-b252-c476965410d7",
"name": "GPT-4o_",
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
"typeVersion": 1.2,
"position": [
620,
340
],
"id": "bc54a0df-8baa-4db3-9473-52c3e64f9fbf",
"name": "Claude 3.5 Sonnet_",
"credentials": {
"anthropicApi": {
"name": "<your credential>"
}
}
}
],
"connections": {
"When chat message received": {
"main": [
[]
]
},
"nvidia": {
"ai_tool": [
[
{
"node": "Claude 3.5 Sonnet Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Pinecone Vector Store": {
"ai_vectorStore": [
[
{
"node": "nvidia",
"type": "ai_vectorStore",
"index": 0
}
]
]
},
"nvidia1": {
"ai_tool": [
[
{
"node": "GPT-4o Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Pinecone Vector Store1": {
"ai_vectorStore": [
[
{
"node": "nvidia1",
"type": "ai_vectorStore",
"index": 0
}
]
]
},
"Embeddings OpenAI1": {
"ai_embedding": [
[
{
"node": "Pinecone Vector Store1",
"type": "ai_embedding",
"index": 0
}
]
]
},
"GPT-4o": {
"ai_languageModel": [
[
{
"node": "GPT-4o Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Embeddings OpenAI": {
"ai_embedding": [
[
{
"node": "Pinecone Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Claude 3.5 Sonnet": {
"ai_languageModel": [
[
{
"node": "Claude 3.5 Sonnet Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"nvidia2": {
"ai_tool": [
[
{
"node": "GPT-4o Agent1",
"type": "ai_tool",
"index": 0
}
]
]
},
"Pinecone Vector Store2": {
"ai_vectorStore": [
[
{
"node": "nvidia2",
"type": "ai_vectorStore",
"index": 0
}
]
]
},
"Embeddings OpenAI2": {
"ai_embedding": [
[
{
"node": "Pinecone Vector Store2",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Gemini Flash 2.0": {
"ai_languageModel": [
[
{
"node": "GPT-4o Agent1",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Gemini Flash 2.0_": {
"ai_languageModel": [
[
{
"node": "nvidia2",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"GPT-4o_": {
"ai_languageModel": [
[
{
"node": "nvidia1",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Claude 3.5 Sonnet_": {
"ai_languageModel": [
[
{
"node": "nvidia",
"type": "ai_languageModel",
"index": 0
}
]
]
}
},
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "ab0ea85a-10b3-46ed-a263-c388de8b5998",
"meta": {
"templateCredsSetupCompleted": true
},
"id": "CgLalQnT5EZXMaMb",
"tags": []
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
anthropicApigooglePalmApiopenAiApipineconeApi
About this workflow
LLM Testing. Uses chatTrigger, toolVectorStore, vectorStorePinecone, embeddingsOpenAi. Chat trigger; 19 nodes.
Source: https://github.com/Zie619/n8n-workflows — original creator credit. Request a take-down →