README.md

---
title: ARGObot
emoji: 🤖
colorFrom: indigo
colorTo: gray
sdk: streamlit
sdk_version: "1.32.2"
app_file: app.py
pinned: false
---



# ARGObot: UWF's Custom AI Advisor

ARGObot is a modular question-answering chatbot that uses either OpenAI (GPT-4) or Google's Gemini with Retrieval-Augmented Generation (RAG). Designed with Langchain, LangGraph, and Streamlit, it allows students to query university policies directly from documents like the UWF Student Handbook.

## Features

-  Easily switch between `OpenAI` and `Gemini` models.
-  Retrieval-Augmented Generation (RAG) using PDF knowledge base.
-  Tool integration for fallback search (Google Search).
-  Conversational memory with LangGraph.
-  Custom UI with UWF branding and Streamlit.

## Local Development

```bash
# Install dependencies
pip install -r requirements.txt

# Set environment
export MODEL_PROVIDER=openai  # or gemini
export OPENAI_API_KEY=your-key
export GOOGLE_API_KEY=your-key

# Run Streamlit
streamlit run app.py
```

## Project Structure

```
.
├── app.py                  # Unified entrypoint
├── requirements.txt
└── src/
    ├── agents/             # Prompt templates and tool config
    ├── chains/             # OpenAI & Gemini RAG logic
    ├── config/             # Environment setup
    ├── interface/          # Streamlit UI
    └── state.py            # LangGraph definition
```

## Hugging Face Secrets (Required)
Add the following secrets in the Hugging Face UI:

- `OPENAI_API_KEY`
- `GOOGLE_API_KEY`
- `MODEL_PROVIDER` (default: `openai`)