Update README.md

README.md

@@ -6,14 +6,41 @@ colorTo: red
 sdk: docker
 app_port: 8501
 tags:
+- financial-analysis
+- nlp
+- sentiment-analysis
+- finbert
 - streamlit
 pinned: false
-short_description: Streamlit template space
+short_description: Market Sentiment & Volatility Prediction using FinBERT
 ---
 
-# Welcome to Streamlit!
+# 🚀 Alpha Predict: Market Sentiment Engine
 
-Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
+Alpha Predict is an AI-driven financial analysis tool that leverages **FinBERT** (Financial BERT) to quantify market sentiment from real-time and historical headlines. It correlates sentiment with **S&P 500 (SPY)** performance and the **VIX (Fear Index)** to provide a holistic view of market psychology.
 
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
+## 🧠 Core Features
+* **NLP Sentiment Analysis:** Uses `ProsusAI/finbert` to perform high-fidelity sentiment classification on thousands of market headlines.
+* **Hybrid Data Fetching:** Integrated with **Finnhub API** for live market news and price action, with a **robust CSV fallback** mechanism for maximum uptime.
+* **Predictive Indicators:** Analyzes "Panic Interaction" (Sentiment x Volatility) to detect market dislocations.
+* **Interactive Analytics:** Visualizes the relationship between news sentiment trends and price movements via Streamlit.
+
+## 🛠️ Technical Stack
+* **UI Framework:** Streamlit
+* **Model:** FinBERT (Hugging Face Transformers)
+* **Data Providers:** Finnhub API, Yahoo Finance (via backup)
+* **Deployment:** Docker / Hugging Face Spaces
+
+## 📂 Project Structure
+* `app.py`: Main entry point for the Streamlit dashboard.
+* `src/data_fetcher.py`: Handles API interactions and data resilience.
+* `src/processor.py`: Feature engineering and sentiment batch processing.
+* `data/`: Secure storage for historical backup data to ensure 100% availability.
+
+## 🚦 Getting Started
+1.  **API Keys:** Ensure your `FINNHUB_API_KEY` is set in the Hugging Face Space Secrets.
+2.  **Processing:** Upon launch, the app will fetch the last 45-60 days of data.
+3.  **Inference:** FinBERT runs batch inference on the latest headlines to calculate the `Sent_Mean` index.
+
+---
+**Note:** *This project was developed for academic purposes to demonstrate the application of Transformer-based models in quantitative finance.*