Build a smart personal assistant with GROQ, LLaMA & search tools

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

A reasoning agent that can think, search, calculate, and remember — powered by GROQ inference and ready to deploy in one click. Unlike traditional AI bots that only respond, this assistant reasons ...

Best for

Personal Productivity automation workflows
AI Chatbot automation workflows
intermediate n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.chattrigger, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.toolthink, @n8n/n8n-nodes-langchain.toolserpapi, @n8n/n8n-nodes-langchain.toolcalculator, @n8n/n8n-nodes-langchain.memorybufferwindow, n8n-nodes-base.stickynote, @n8n/n8n-nodes-langchain.lmchatgroq

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by DigiMetaLab.

Original n8n.io source

1.1 Workflow description

Title: Build a smart personal assistant with GROQ, LLaMA & search tools
Workflow name: Build a smart personal assistant with GROQ, LLaMA & search tools

A reasoning agent that can think, search, calculate, and remember — powered by GROQ inference and ready to deploy in one click.

Unlike traditional AI bots that only respond, this assistant reasons before replying, fetches real-time facts, does math, and keeps short-term memory of your conversation.

🔧 How it works This template builds a conversational AI agent using the GROQ LLaMA 3 or LLaMA 4 API, combined with modular tools like:

🧠 Think Tool – performs step-by-step logical reasoning
🔍 SerpAPI – fetches live data from Google search
➗ Calculator – handles arithmetic and math queries
💾 Memory Buffer – keeps track of the last 5 messages for context

Everything is integrated inside n8n and optimized for blazing-fast replies using GROQ’s ultra-low latency.

🧠 Your Agent Will:

Understand and analyze your queries
Think through solutions before answering
Pull real-time data via SerpAPI
Perform calculations with the built-in math engine
Recall prior context using short-term memory
Respond clearly, conversationally — like a real assistant

🧑‍💼 Who is this template for? Perfect for:

AI builders and creators using GROQ + n8n
Teams needing a real-time LLaMA-powered assistant
Beginners exploring LangChain + n8n workflows
Developers combining LLMs + tools + memory

🚀 How to Set Up

Plug in your GROQ API key
Add your SerpAPI key
Import and run — it’s ready to chat!
All tools are pre-wired. You can expand the memory, customize prompts, or plug in more tools.

📬 Use Cases Connect this agent with:

Telegram Bots 🤖
WhatsApp via Twilio 📱
Slack, Discord, or Gmail 💬
Manual triggers in n8n 🔁

👉 Check out more templates by this creator: https://n8n.io/creators/digimetalab

1.2 Logical Blocks

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.

2. Block-by-Block Analysis

Block 1 - When chat message received

Type / Role: @n8n/n8n-nodes-langchain.chatTrigger - chatTrigger
Config choices: Version 1.1

Block 2 - AI Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 2

Block 3 - Think

Type / Role: @n8n/n8n-nodes-langchain.toolThink - toolThink
Config choices: Version 1

Block 4 - SerpAPI

Type / Role: @n8n/n8n-nodes-langchain.toolSerpApi - toolSerpApi
Config choices: Version 1

Block 5 - Calculator

Type / Role: @n8n/n8n-nodes-langchain.toolCalculator - toolCalculator
Config choices: Version 1

Block 6 - Simple Memory

Type / Role: @n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices: Version 1.3

Block 7 - Sticky Note10

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 8 - Sticky Note17

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 9 - Sticky Note18

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 10 - Sticky Note19

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 11 - Sticky Note20

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 12 - Sticky Note21

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 13 - Groq Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatGroq - lmChatGroq
Config choices: Version 1

3. Summary Table

Workflow	Build a smart personal assistant with GROQ, LLaMA & search tools
Complexity	intermediate
Nodes	13
Categories	Personal Productivity, AI Chatbot
Author	DigiMetaLab
Published	11 Jul 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/5870/5870.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

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.

Download workflow JSON Original n8n.io source Personal Productivity workflows AI Chatbot workflows

Frequently asked questions

What does Build a smart personal assistant with GROQ, LLaMA & search tools do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

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 Personal Productivity, AI Chatbot use case.

DigiMetaLab

4 workflows

Nodes

@n8n/n8n-nodes-langchain.chattrigger @n8n/n8n-nodes-langchain.agent @n8n/n8n-nodes-langchain.toolthink @n8n/n8n-nodes-langchain.toolserpapi @n8n/n8n-nodes-langchain.toolcalculator @n8n/n8n-nodes-langchain.memorybufferwindow n8n-nodes-base.stickynote @n8n/n8n-nodes-langchain.lmchatgroq

Complexity

intermediate

Published 11 Jul 2025

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/5870/5870.json

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Build a smart personal assistant with GROQ, LLaMA & search tools

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - When chat message received

Block 2 - AI Agent

Block 3 - Think

Block 4 - SerpAPI

Block 5 - Calculator

Block 6 - Simple Memory

Block 7 - Sticky Note10

Block 8 - Sticky Note17

Block 9 - Sticky Note18

Block 10 - Sticky Note19

Block 11 - Sticky Note20

Block 12 - Sticky Note21

Block 13 - Groq Chat Model

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions