README.md

metadata

title: Alz Users' Retrieval Augmented System (AURAS) Chatbot
emoji: 📉
colorFrom: blue
colorTo: gray
sdk: gradio
sdk_version: 5.42.0
app_file: app.py
pinned: false
license: mit
short_description: Multimodal Linguistic Chatbot for AD patients

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Alzheimer’s AI Companion (RAG + Role-Aware)

A gentle Retrieval-Augmented Generation (RAG) assistant for Alzheimer’s care contexts, with patient vs caregiver role routing, optional speech-to-text (STT) and text-to-speech (TTS), and a Gradio UI suitable for a Hugging Face Space.

Features

• Role-aware prompting: simple, comforting tone for patient; concise, actionable tone for caregiver.
• RAG over your uploaded documents using FAISS + Sentence-Transformers.
• OpenAI LLM via langchain_openai.ChatOpenAI.
• STT using OpenAI (gpt-4o-transcribe or whisper-1), and TTS via gTTS.
• Gradio UI with tabs: Chat, Upload Knowledge, Settings.

⚕️ This is not medical advice, nor a diagnostic tool. Always consult clinicians for health decisions.

Quickstart (Local)

1. Install

   pip install -r requirements.txt
   

2. Environment

   export OPENAI_API_KEY=YOUR_KEY_HERE
   

3. Run

   python app.py
   

   Gradio will print a local URL.

Hugging Face Space

Upload the repo (including app.py and requirements.txt) to a new Gradio Space. Set a secret named OPENAI_API_KEY under Settings → Variables.

Project Layout

.
├── app.py                      # Gradio UI
├── requirements.txt
├── README.md
├── sample_data/
│   └── caregiving_tips.txt     # Example doc for indexing
└── alz_companion/
    ├── agent.py                # Core RAG + role routing + audio helpers
    └── prompts.py              # System & RAG prompts

Notes

• First run will download the embedding model (sentence-transformers/all-MiniLM-L6-v2).
• FAISS index persists in data/faiss_index. Delete that folder to rebuild.
• gTTS requires outbound Internet access to fetch the voice.

Licence

MIT