🏢 Virtual Reception

A Retrieval-Augmented Generation (RAG) powered application designed to serve as an intelligent Virtual Reception System.

This system allows users to interact with organizational or project documentation conversationally — getting precise answers instantly. If the requested information isn’t found in the documents, the model gracefully responds with:

“Sorry, I do not have this information.”

🚀 Overview

Virtual Reception bridges the gap between static documentation and natural language understanding. By combining LLMs (Large Language Models) with vector-based retrieval, it delivers accurate, document-grounded answers — making it ideal for businesses, projects, or institutions that want to automate FAQ-style or onboarding interactions.

🧠 Key Features

📄 RAG Framework — Combines LLMs with a vector store for context-aware responses.

🔍 Document Querying — Upload multiple docs (PDF, TXT, MD, etc.) and search naturally.

⚙️ Customizable Pipeline — Plug in your own models and embeddings (supports Hugging Face).

❌ Fallback Safety — When no relevant information is found, it politely declines with an appropriate response.

🧩 Modular Architecture — Easy to extend for domain-specific or enterprise setups.

🧱 Project Architecture
Virtual Reception
.
├── .env
├── .gitignore
├── .python-version
├── config
├── data
│   └──
├── models
│   └──
├── notebooks
│   └── index.ipynb
│   └── rag_pipeline.py
├── pyproject.toml
├── README.md
├── requirements.txt
├── src
│   └── main.py
├── tests
└── uv.lock

⚙️ Tech Stack

Component Technology Framework Python RAG Model Hugging Face (e.g. Mistral-7B-Instruct-v0.3, configurable) Embeddings Sentence Transformers / Hugging Face Embeddings Vector Database FAISS / ChromaDB Frontend (Optional) Streamlit / React Deployment Docker / Hugging Face Spaces

🧩 Setup Instructions

1️⃣ Clone the Repository

git clone https://github.com/Dhruvrana8/virtual-reception-rag
cd virtual-reception

2️⃣ Create Virtual Environment

python -m venv venv
source venv/bin/activate   # for Mac/Linux
venv\Scripts\activate      # for Windows

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Add Documents

Place your documents (PDFs, text files, or markdown) inside the data/ folder.

5️⃣ Run the Application python app.py

📄 License

This project is licensed under the MIT License — feel free to use and modify it as needed.

👨‍💻 Author

Dhruv Rana Post-Graduate in Artificial Intelligence and Machine Learning @ Lambton College • GitHub • LinkedIn