Block 1 - OpenAI Chat Model
- Type / Role
- @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
- Config choices
- Version 1.2
This workflow is provided as-is. Please review and test before using in production.
How it works This workflow powers an intelligent, conversational AI bot for VK that can understand and respond to both text and voice messages . The bot uses an AI agent with built in memory, allow...
@n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.memorybufferwindow, n8n-nodes-base.webhook, @n8n/n8n-nodes-langchain.openai, @n8n/n8n-nodes-langchain.agent, n8n-nodes-base.httprequest, n8n-nodes-base.set, n8n-nodes-base.filter
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Konstantin.
Original n8n.io sourceThis workflow powers an intelligent, conversational AI bot for VK that can understand and respond to both text and voice messages. The bot uses an AI agent with built-in memory, allowing it to remember the conversation history for each unique user (or in each chat) and answer follow-up questions. It's a complete solution for creating an engaging, automated assistant within your VK group.
x-retry-counter header. This is a crucial step to prevent processing duplicate retry requests sent by the VK API.message.text) or a voice attachment (audio_message.link_mp3).prompt variable.prompt variable is passed to the AI Agent. This agent is powered by an OpenAI Chat Model and uses Simple Memory to retain conversation history, using the VK peer_id as the sessionKey. This allows it to maintain a separate history for both private messages and group chats.onError). If it fails, the flow is redirected to the Error (HTTP Request) node, which sends a fallback message to the user.Estimated set up time: 10 minutes
Response Mode to On Received.Options -> Response Data, temporarily paste the confirmation string that VK provides.Response Mode to Immediate.Options -> Response Data, type the word ok (lowercase).This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
| Workflow | Conversational VK bot with GPT-4 mini & Whisper voice transcription |
|---|---|
| Complexity | advanced |
| Nodes | 17 |
| Categories | Support Chatbot, AI Chatbot |
| Author | Konstantin |
| Published | 06 Nov 2025 |
Use the JSON export at /data/workflows/10579/10579.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
How it works This workflow powers an intelligent, conversational AI bot for VK that can understand and respond to both text and voice messages . The bot uses an AI agent with built in memory, allow...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Support Chatbot, AI Chatbot use case.