Update README.md

README.md

@@ -1,14 +1,45 @@
 ---
-title: Everychat
+title: Offline Survey Analysis
 emoji: 💬
 colorFrom: yellow
-colorTo: purple
+colorTo: blue
 sdk: gradio
 sdk_version: 5.0.1
 app_file: app.py
 pinned: false
 license: apache-2.0
-short_description: A unified service, "EveryChat," that allows you to choose an
+short_description: Analyse sensitive survey data in offline mode
 ---
 
-An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index).
+This space build from https://huggingface.co/spaces/VIDraft/EveryRAG and provide adjustements for this work offline with ollama when __working with sensitive data__ that can come with data protection concerns.
+
+The app now works completely offline (after downloading the model) wich means that you do not need to share any data on the cloud... 
+
+## Requirements:
+
+1. Install [Ollama](https://ollama.com/download) and run in a shell: `ollama serve`
+
+2.  You must have pulled the [Mistral-Nemo model](https://ollama.com/library/mistral-nemo), a model that excel in data analysis but can still run on regular consumer hardware: `ollama pull mistral-nemo`
+
+3.  Install [Visual Studio Code](https://code.visualstudio.com/) and make sure to install the last [stable version of python language](https://www.python.org/downloads/)
+
+4. Clone this repo in visual studio,
+
+5. Create a virtual environment in Python development. This is essential for managing dependencies, avoiding conflicts, and ensuring reproducibility. It allows you to isolate project-specific libraries and versions, preventing interference with other projects or the global Python installation. This isolation helps maintain a clean development environment, simplifies project setup for collaborators, and enhances security by reducing the risk of introducing vulnerabilities. Overall, virtual environments provide a consistent and organized way to manage your Python projects effectively.
+
+    - Open your terminal in VS code
+    - Run the following command to create a virtual environment, here called **`.venv`**: `python -m venv .venv`
+    - Then, activate the virtual environment - on windows with `.\.venv\Scripts\activate`
+    - Then install all require Python Modules with `pip install -r requirements.txt`
+
+## How to Use:
+
+
+1. Run the app.py script > `python app.py`
+
+2. Open your localhost and upload your survey data file (text, code, CSV, or Parquet)
+
+3. The app will automatically analyze the file structure
+
+4. __Et voilà!__ Ask questions about your file in natural language. The model can help you to write quickly any analysis notebook!
+