Shorten short_description to meet Hugging Face metadata requirements

README.md

@@ -8,7 +8,7 @@ sdk_version: 0.115.0
 app_file: app.py
 pinned: false
 license: apache-2.0
-short_description: API for integrating T5 and Mistral-7B (GGUF) models in Hugging Face Spaces
+short_description: API for T5 and Mistral-7B in Hugging Face Spaces
 ---
 
 # MGZON Smart Assistant
@@ -17,14 +17,13 @@ This project provides a FastAPI-based API for integrating two language models:
 - **MGZON-FLAN-T5**: A pre-trained T5 model fine-tuned to respond to questions containing keywords like "mgzon", "flan", or "t5".
 - **Mistral-7B-GGUF**: A Mistral-7B model in GGUF format for answering general questions.
 
-![Demo](https://huggingface.co/spaces/MGZON/api-mg/resolve/main/demo.png)
-
 ## Setup
 - **Docker**: The image is built using `python:3.10-slim` with development tools (`gcc`, `g++`, `cmake`, `make`) installed to support building `llama-cpp-python`.
+- **Permissions**: The application runs as a non-root user (`appuser`), with cache (`/app/.cache/huggingface`) and model (`models/`) directories configured with appropriate permissions.
 - **System Requirements**: Dependencies are installed from `requirements.txt`, including `transformers`, `torch`, `fastapi`, and `llama-cpp-python`.
 - **Model Download**: The Mistral-7B GGUF model is downloaded via `setup.sh` using `huggingface_hub`.
 - **Environment Variables**:
-  - `HF_HOME` and `TRANSFORMERS_CACHE` are set to `/app/.cache/huggingface`.
+  - `HF_HOME` is set to `/app/.cache/huggingface`.
   - `HF_TOKEN` (secret) is required to access models from the Hugging Face Hub.
 
 ## How to Run
@@ -43,3 +42,4 @@ curl -X POST "https://mgzon-api-mg.hf.space/ask" \
 -H "Content-Type: application/json" \
 -d '{"question": "What is MGZON?", "max_new_tokens": 100}'
 ```
+