Update README.md

README.md

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-# Whale Wallet AI – Market Manipulation Detection
-
-A powerful Streamlit-based tool that tracks large holders ("whales") on the Arbitrum network to uncover potential market manipulation tactics.
-
-## 1. Prerequisites & Setup
-
-### 1.1. Python & Dependencies  
-- Ensure you have Python 3.8+ installed.  
-- Install required packages via:
-  ```bash
-  pip install -r requirements.txt
-  ```
-
-### 1.2. API Keys  
-You need API keys to fetch on-chain data and real-time prices:
-- **ARBISCAN_API_KEY**: For fetching Arbitrum transaction data
-- **GEMINI_API_KEY**: For retrieving live token prices
-- **OPENAI_API_KEY**: For powering the CrewAI agents
-
-Save these in a file named `.env` at the project root:
-```env
-ARBISCAN_API_KEY=your_arbiscan_key
-GEMINI_API_KEY=your_gemini_key
-OPENAI_API_KEY=your_openai_key
-```
-Note: Sample API keys are provided in the default .env file, but you should replace them with your own for production use.
-
-### 1.3. Run the App  
-Launch the web interface with:
-```bash
-streamlit run app.py
-```
-
-## 2. Core Features & How to Use Them
-
-### 2.1 Track Large Buy/Sell Transactions
-
-**What it does:**  
-Monitors on-chain transfers exceeding a configurable threshold (e.g., 1,000 tokens or $100K) for any wallet or contract you specify.
-
-**How to use:**  
-1. In the sidebar, enter one or more wallet addresses  
-2. Set your minimum token or USD value filter  
-3. Click **Track Transactions**  
-4. The dashboard will list incoming/outgoing transfers above the threshold.
-
-### 2.2 Identify Trading Patterns of Whale Wallets
-
-**What it does:**  
-Uses time-series clustering and sequence analysis to surface recurring behaviors (e.g., cyclical dumping, accumulation bursts).
-
-**How to use:**  
-1. Select a wallet address  
-2. Choose a time period (e.g., last 7 days)  
-3. Click **Analyze Patterns**  
-4. View a summary of detected clusters and drill down into individual events.
-
-### 2.3 Analyze Impact of Whale Transactions on Token Prices
-
-**What it does:**  
-Correlates large trades against minute-by-minute price ticks to quantify slippage, price spikes, or dumps.
-
-**How to use:**  
-1. Enable **Price Impact** analysis in settings  
-2. Specify lookback/lookahead windows (e.g., 5 minutes)  
-3. Click **Run Impact Analysis**  
-4. See interactive line charts and slippage metrics.
-
-### 2.4 Detect Potential Market Manipulation Techniques
-
-**What it does:**  
-Automatically flags suspicious behaviors such as:
-- **Pump-and-Dump:** Rapid buys followed by coordinated sell-offs  
-- **Wash Trading:** Self-trading across multiple addresses  
-- **Spoofing:** Large orders placed then canceled
-
-**How to use:**  
-1. Toggle **Manipulation Detection** on  
-2. Adjust sensitivity slider (Low/Medium/High)  
-3. Click **Detect**  
-4. Examine the **Alerts** panel for flagged events.
-
-### 2.5 Generate Reports & Visualizations
-
-**What it does:**  
-Compiles whale activity into PDF/CSV summaries and interactive charts.
-
-**How to use:**  
-1. Select **Export** in the top menu  
-2. Choose **CSV**, **PDF**, or **PNG**  
-3. Specify time range and wallets to include  
-4. Click **Download**  
-5. Saved file will appear in your browser's download folder.
-
-## 3. Advanced Features: CrewAI Integration
-
-This application leverages CrewAI to provide advanced analysis through specialized AI agents:
-
-- **Blockchain Data Collector**: Extracts and organizes on-chain data
-- **Price Impact Analyst**: Correlates trading activity with price movements
-- **Trading Pattern Detector**: Identifies recurring behavioral patterns
-- **Market Manipulation Investigator**: Detects potential market abuse
-- **Insights Reporter**: Transforms data into actionable intelligence
-
-## 4. Project Structure
-
-```
-/Whale_Arbitrum/
-├── app.py                # Main Streamlit application entry point
-├── requirements.txt      # Dependencies and package versions
-├── .env                  # API keys and environment variables
-├── modules/
-│   ├── api_client.py     # Arbiscan and Gemini API clients
-│   ├── data_processor.py # Data processing and analysis
-│   ├── detection.py      # Market manipulation detection algorithms
-│   ├── visualizer.py     # Visualization and report generation
-│   └── crew_system.py    # CrewAI agentic system
-```
-
-## 5. Use Cases
-
-- **Regulatory Compliance & Fraud Detection**  
-  Auditors and regulators can monitor DeFi markets for wash trades and suspicious dumps.
-
-- **Investment Strategy Optimization**  
-  Traders gain insight into institutional flows and can calibrate entry/exit points.
-
-- **Market Research & Analysis**  
-  Researchers study whale behavior to gauge token health and potential volatility.
-
-- **DeFi Protocol Security Monitoring**  
-  Protocol teams receive alerts on large dumps that may destabilize liquidity pools.
-
-- **Token Project Risk Assessment**  
-  Token issuers review top-holder actions to flag governance or distribution issues.
+title: CryptoAI
+emoji: 📚
+colorFrom: green
+colorTo: gray
+sdk: streamlit
+sdk_version: 1.44.1
+app_file: app.py
+pinned: false