feat(README)

README.md

@@ -1,6 +1,6 @@
 ---
 title: AnythingQ&A
-emoji: 🌍
+emoji: ❓
 colorFrom: blue
 colorTo: red
 sdk: gradio
@@ -9,14 +9,47 @@ app_file: app.py
 pinned: false
 ---
 
-# Anything Q&A
+## Anything Q&A
 
-A clone of the amazing https://huggingface.co/spaces/Ekimetrics/climate-question-answering.
+This tool serves as a customizable version of the amazing ClimateQA by Ekimetrics. It allows you to rapidly create a new question-answering tool using any set of documents as a data source.
 
-We abstracted the code so it's easy to build another tool based on another domain.
+## Quick Start
 
-## Build vector index
+0. **Fork the Repository**  
+   Fork the original HuggingFace space: [Anything Q&A on HuggingFace](https://huggingface.co/spaces/LouisSanna/anything-question-answering).
 
-```bash
-python -m anyqa.build_index
-```
+1. **Install Dependencies**
+
+   ```shell
+   pip install -r requirements.txt
+   ```
+
+2. **Add your data.**
+   Place the PDFs to be used as sources in the data folder. The subfolder and file names will be used as default identifiers by the tool.
+
+   ```txt
+   data/
+       type_1/
+           source_1.pdf
+           source_2.pdf
+       type_2/
+           source_3.pdf
+   ```
+
+3. **Build the index of semantic vectors**
+
+   ```bash
+   python -m anyqa.build_index
+   ```
+
+4. **Launch the app**
+
+   ```shell
+   python app.py
+   ```
+
+And you're done!
+
+## Deployment
+
+Deploying via Hugging Face Spaces is the most straightforward approach. Simply push your code to a HuggingFace Gradio space, and it will function as is.