🤖 Enatega Website Chatbot

An AI-powered chatbot that answers questions about Enatega using RAG (Retrieval-Augmented Generation).
It scrapes Enatega's website, rewrites text into structured paragraphs, chunks content, embeds it into Qdrant, and serves a chatbot API with FastAPI + LangChain + OpenAI.

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✨ Features

• 🔍 Automated Web Scraping with Playwright & BeautifulSoup
• 📝 Text Rewriting into headings & paragraphs for optimized chunking
• 🧩 Smart Chunking (token-based with overlap for context retention)
• 📦 Vector Storage in Qdrant (Cloud or Local)
• 🧠 RAG Chatbot API powered by LangChain & OpenAI
• 🌐 Frontend Widget easily embeddable into any website
• 🔄 Automated Refresh Workflow (scrape → rewrite → chunk → ingest → deploy) every 2 months via GitHub Actions
• ☁️ Deployable on Render / Railway / AWS / Docker

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📂 Project Structure

Enatega_website_chatbot/
├── api/                     # FastAPI app
│   └── main.py
├── data/
│   ├── raw/                 # Raw HTML
│   └── clean/               # Cleaned & rewritten text + chunks
├── frontend/                # Simple HTML/JS chatbot widget
├── web_scraping.py          # Scrapes website pages
├── rewrite_texts.py         # Rewrites text into structured form (headings/paragraphs)
├── chunking.py              # Splits text into chunks for embeddings
├── ingest_qdrant.py         # Ingests chunks into Qdrant
├── ensure_indexes.py        # Ensures indexes exist in Qdrant
├── run_pipeline.sh          # End-to-end pipeline runner
├── requirements.txt         # Python dependencies
├── Dockerfile               # For containerized deployment
└── .github/workflows/       # GitHub Actions automation

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⚙️ Setup

1. Clone the repo

git clone https://github.com/voiceofarsalan/Enatega_website_chatbot.git
cd Enatega_website_chatbot

2. Create virtual environment

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

3. Environment variables

Create a .env file:

OPENAI_API_KEY=your_openai_api_key
QDRANT_URL=https://your-qdrant-instance.qdrant.io:6333
QDRANT_API_KEY=your_qdrant_api_key
COLLECTION_NAME=enatega_home

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🛠️ Usage

Run the pipeline manually

./run_pipeline.sh

This will:

• Scrape Enatega website pages
• Rewrite text into structured format
• Chunk content
• Ingest into Qdrant
• Ensure indexes

Run chatbot locally

uvicorn api.main:app --reload --port 8000

Test endpoint:

curl -s -X POST http://127.0.0.1:8000/chat \
  -H "Content-Type: application/json" \
  -d '{"session_id":"demo","message":"What is Enatega?"}'

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🌐 Deployment

Docker

docker build -t enatega-bot .
docker run -p 8000:8000 enatega-bot

Render (recommended)

1. Push repo to GitHub
2. Create a Web Service on Render
3. Point to this repo
4. Expose port 8000

Your bot will be live at https://<your-app>.onrender.com.

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💬 Embedding Chat Widget

Add this snippet to your website:

<div id="chatbot"></div>
<link rel="stylesheet" href="https://enatega-bot.onrender.com/style.css">
<script src="https://enatega-bot.onrender.com/app.js"></script>
<script>
  ChatbotWidget.init({
    endpoint: "https://enatega-bot.onrender.com/chat",
    title: "Enatega Assistant 🤖",
    subtitle: "Ask me anything about Enatega"
  });
</script>

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🔄 Automated Workflow

GitHub Actions runs the full pipeline every 2 months.

The job:

• Scrapes & rewrites site content
• Updates chunks in Qdrant
• Auto-commits new data back to the repo

Trigger manually:

gh workflow run "RAG Refresh (bi-monthly)"

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🧪 Example Queries

• What is Enatega and who is it for?
• How fast can I launch?
• Do you offer lifetime updates?
• What apps are included?
• Share some case studies.
• Does Enatega support non-food delivery?
• Who can deploy for me if I don't have a dev team?

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🤝 Contributing

PRs are welcome! Open an issue for feature requests or bugs.

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📜 License

MIT License © 2025 voiceofarsalan