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FAQ Chatbot using n8n + Groq LLM

This is a simple FAQ chatbot that uses n8n for automation and a Groq-hosted LLM to respond to user questions. The chatbot interface is built with HTML and interacts with a webhook flow deployed via n8n.

Features

• Clean and modern chatbot interface
• User input sent to an n8n webhook using the prompt
• n8n workflow forwards the question to a language model (via Groq)
• Scrapes and refers to a specific FAQ page for answers
• Provides concise, bot-style responses
• Hosted completely via n8n and static frontend

📂 Project Structure

📁 project-root
├── index.html          # Frontend chatbot UI
├── README.md           # This file
└── n8n-workflow.json   # Exported workflow from n8n

🧠 How It Works

1. Frontend (HTML page) A user types a question and clicks "Ask". The question is sent to a webhook hosted on n8n.

2. n8n Workflow The workflow consists of the following nodes:

   • Webhook Node: Accepts incoming POST requests with user questions.
   • Set Node: Extracts the question from the body and assigns it.
   • LLM Chain Node: Forms the prompt using the question and sends it to the Groq LLM.
   • Groq Chat Model: Calls a Groq-hosted language model.
   • Respond to Webhook Node: Returns the LLM's response to the frontend.

3. Web Scraping via Prompting The prompt instructs the model to refer to a specific FAQ page and answer only if the information is available on that page.

🖼️ Screenshot

Setup Instructions

1. Clone the Repo

git clone https://github.com/your-username/faq-chatbot.git
cd faq-chatbot

2. Deploy the HTML

You can open the index.html file directly or host it using GitHub Pages, Netlify, or any static host.

3. Setup the n8n Workflow

• Import the n8n-workflow.json file into your n8n instance.
• Make sure the webhook URL in index.html matches your n8n public webhook URL.
• Add your Groq API credentials in n8n.
• Activate the workflow.

🧪 Example Questions

• "What are the office hours?"
• "How can I register for the next semester?"
• "Where can I find the contact information?"

✅ To Do / Improvements

• Add fallback if LLM doesn’t know the answer
• Add chat history / memory
• Deploy frontend with a backend server for security
• Handle multiple languages

📄 License

This project is licensed under the MIT License.

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