Block 1 - Google Gemini Chat Model
- Type / Role
- @n8n/n8n-nodes-langchain.lmChatGoogleGemini - lmChatGoogleGemini
- Config choices
- Version 1
This workflow is provided as-is. Please review and test before using in production.
AI Chatbot with Conditional Execution for Cost Efficiency Description This n8n workflow implements an AI powered chatbot that only runs when a chat is initiated on a website . By introducing a cond...
@n8n/n8n-nodes-langchain.lmchatgooglegemini, @n8n/n8n-nodes-langchain.agent, n8n-nodes-base.if, @n8n/n8n-nodes-langchain.memorybufferwindow, @n8n/n8n-nodes-langchain.chattrigger
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Amjid Ali.
Original n8n.io sourceThis n8n workflow implements an AI-powered chatbot that only runs when a chat is initiated on a website. By introducing a conditional step, the workflow ensures that AI tokens are not consumed unnecessarily, making it a cost-efficient and resource-optimized solution.
The chatbot, named Sophia, serves as an interactive assistant for SyncBricks. It helps users with guest posting services, YouTube review videos, IT consultancy, and online courses while collecting user details step by step. The chatbot ensures that inquiries are properly logged and confirmed before proceeding to AI-driven responses.
This template is ideal for businesses, service providers, and content creators who want to optimize AI token usage while delivering personalized, interactive engagement with their users.
Chat Message Trigger
Condition Check: Is Chat Input Provided?
AI-Powered Chat Response
Memory Buffer for Context Retention
Response Optimization
Confirmation & User Engagement
Final Confirmation Message
Before using this workflow, make sure you have:
Developed by: Amjid Ali
Website: SyncBricks
Email: [email protected]
LinkedIn: Amjid Ali
YouTube: SyncBricks
If you find this workflow helpful, consider supporting my work:
For full courses on n8n, visit:
This n8n workflow ensures optimal AI token usage while engaging users with an intelligent chatbot. By integrating conditional execution, it prevents unnecessary API calls, making it cost-effective and efficient for businesses looking to automate chat-based customer interactions.
Let me know if you need any modifications!
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 | AI chatbot for website with conditional execution for cost efficiency |
|---|---|
| Complexity | intermediate |
| Nodes | 5 |
| Categories | AI, AI Chatbot |
| Author | Amjid Ali |
| Published | 12 Jan 2025 |
Use the JSON export at /data/workflows/2717/2717.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.
AI Chatbot with Conditional Execution for Cost Efficiency Description This n8n workflow implements an AI powered chatbot that only runs when a chat is initiated on a website . By introducing a cond...
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 AI, AI Chatbot use case.