FAQ Application

🧠 AI-Powered FAQ Chatbot

An interactive AI-powered chatbot built using FastAPI, LangChain, Gemini (Google Generative AI), and FAISS. It loads FAQ content from a CSV file and provides intelligent, contextual answers to user questions through a frontend interface.

🚀 Features

• 📁 Load FAQs from CSV
• 🤖 Answer questions using Gemini (via LangChain)
• 📚 Vector search with FAISS
• 🖥️ Beautiful chat UI with typing animation
• 🌐 Full-stack with FastAPI + Bootstrap frontend
• 📦 Modular and extensible codebase
• 📄 download the live chat History

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🛠️ Tech Stack

Layer	Technology
Frontend	HTML, CSS (Bootstrap), JavaScript
Backend	FastAPI, LangChain
Embeddings	GoogleGenerativeAIEmbeddings (Gemini)
LLM	Gemini 1.5 Flash
Vector DB	FAISS
Hosting	Localhost (Uvicorn)

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📁 Folder Structure

FAQ/
├── app/
│ ├── main.py             # FastAPI entry point
│ ├── routers/
│ │ └── faq_chain.py      # LLM chain logic with LangChain + Gemini
│ ├── schemas/
│ │ └── models.py         # Pydantic models
├── static/
│ ├── app.js              # Frontend logic
│ ├── style.css           # UI styling
├── template/
│ └── index.html          # Chat UI
├── data/
│ └── faqs.csv            # FAQ dataset
├── .env                  # Gemini API Key
├── requirements.txt      # All dependencies

📦 Installation

1. Clone the repository

git clone https://github.com/18Prashanth/FAQ.git
cd FAQ

2. Create a virtual environment

python -m venv venv
source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install dependencies

pip install -r requirements.txt

4. Set your Google Gemini API key

Create a .env file in the root directory:

GOOGLE_API_KEY=your-gemini-api-key-here

🧪 Run the App

uvicorn app.main:app --reload

👉 Visit the app in your browser:

 http://localhost:8000

📄 API Endpoint

Method	Endpoint	Description
POST	/faq_question	Ask a question and get a response
GET	/	Loads the frontend (chat UI)

📷 UI Preview

💡 Author

Prashanth Gowda A S