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README.md
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ARGObot is a custom-built Retrieval-Augmented Generation (RAG) chatbot designed to answer university-related questions using either OpenAI or Google Gemini. It reads from official student handbooks and optionally supplements answers using Google Search.
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src/
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##
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### 1. Clone the Repository
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```bash
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1. Loads a PDF knowledge base (e.g., UWF Student Handbook)
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2. Splits it into text chunks using LangChain
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- [LangChain](https://www.langchain.com/)
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- [LangGraph](https://docs.langgraph.dev/)
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##
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Do **not** share your `.env` or `credentials.json` publicly. Always use `.env.example` for version control.
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##
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MIT License — free for personal and commercial use.
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##
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**
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[Contact me](mailto:mr@uwf.edu) for collaboration or custom deployments.
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ARGObot is a custom-built Retrieval-Augmented Generation (RAG) chatbot designed to answer university-related questions using either OpenAI or Google Gemini. It reads from official student handbooks and optionally supplements answers using Google Search.
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## Features
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- Switchable backend (OpenAI or Gemini)
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- LangGraph for stateful chat memory
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- RAG pipeline using LangChain + ChromaDB
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- Clean Streamlit interface
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- Modular file structure
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- Secure `.env`-based configuration
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## Project Structure
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```
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src/
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## Getting Started
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### 1. Clone the Repository
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```bash
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## How It Works
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1. Loads a PDF knowledge base (e.g., UWF Student Handbook)
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2. Splits it into text chunks using LangChain
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## Technologies Used
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- [LangChain](https://www.langchain.com/)
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- [LangGraph](https://docs.langgraph.dev/)
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## Security Note
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Do **not** share your `.env` or `credentials.json` publicly. Always use `.env.example` for version control.
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## License
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MIT License — free for personal and commercial use.
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## Author
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**Maryam Taeb**
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[Contact me](mailto:mr@uwf.edu) for collaboration or custom deployments.
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