vibetrading-ai-trading-code-generator

Generate executable Hyperliquid trading strategy code from natural language prompts. Use when a user wants to create automated trading strategies for Hyperliquid exchange based on their trading ideas, technical indicators, or VibeTrading signals. The skill generates complete Python code with proper error handling, logging, and configuration using actual Hyperliquid API wrappers.

# VibeTrading Code Generator

Generate executable Hyperliquid trading strategy code from natural language prompts. This skill transforms trading ideas into ready-to-run Python code using actual Hyperliquid API implementations. Generated code includes complete API integration, error handling, logging, and configuration management.

## Quick Start

### Basic Usage

```bash
# Generate a simple RSI strategy
python scripts/strategy_generator.py "Generate a BTC RSI strategy, buy below 30, sell above 70"

# Generate a grid trading strategy
python scripts/strategy_generator.py "BTC grid trading 50000-60000 10 grids 0.01 BTC per grid"

# Generate a signal-following strategy
python scripts/strategy_generator.py "ETH trading strategy based on VibeTrading signals, buy on bullish signals, sell on bearish signals"
```

### Output Structure

The generator creates:
1. **Strategy Python file** - Complete trading strategy class
2. **Configuration file** - Strategy parameters and settings
3. **Usage instructions** - How to run and monitor the strategy
4. **Requirements file** - Python dependencies

## Code Validation System

### Automatic Code Validation

All generated code is automatically validated and fixed using the built-in validation system:

```bash
# Validate generated code
python scripts/code_validator.py generated_strategy.py

# Validate and fix automatically
python scripts/code_validator.py generated_strategy.py --fix

# Validate entire directory
python scripts/code_validator.py strategy_directory/
```

### Validation Steps

The validation system performs these checks:

1. **Syntax Validation** - Python syntax checking
2. **Import Validation** - Module import verification
3. **Compatibility Checks** - Python 3.5+ compatibility
4. **Common Issue Detection** - Missing imports, encoding issues, etc.

### Automatic Fixes

When validation fails, the system automatically fixes common issues:

1. **Add missing imports** - Add typing imports if type annotations are used
2. **Fix encoding declaration** - Add `# -*- coding: utf-8 -*-` if missing
3. **Remove incompatible syntax** - Remove f-strings and type annotations for Python 3.5 compatibility
4. **Fix import paths** - Add sys.path modifications for API wrappers
5. **Fix logger initialization order** - Ensure logger is initialized before API client
6. **Remove pathlib usage** - Replace with os.path for Python 3.4 compatibility
7. **Fix string formatting** - Convert f-strings to .format() method

### Validation Configuration

The validation system can be configured via command-line arguments:

```bash
# Basic validation
python scripts/code_validator.py strategy.py

# Validate and fix automatically
python scripts/code_validator.py strategy.py --fix

# Use specific Python executable
python scripts/code_validator.py strategy.py --python python3.6

# Validate directory with all files
python scripts/code_validator.py strategies/ --fix

# Maximum 5 fix iterations
python scripts/code_validator.py strategy.py --fix --max-iterations 5
```

### Validation Rules

The system enforces these rules for generated code:

1. **Python 3.5+ Compatibility**
   - No f-strings (use `.format()` or `%` formatting)
   - No type annotations (remove or use comments)
   - No pathlib (use `os.path` instead)
   - No typing module imports

2. **Code Quality**
   - Proper encoding declaration (`# -*- coding: utf-8 -*-`)
   - Logger initialized before API client
   - All imports are resolvable
   - No syntax errors

3. **Security**
   - API keys loaded from environment variables
   - No hardcoded credentials
   - Proper error handling for API calls

4. **Performance**
   - Reasonable check intervals (not too frequent)
   - Efficient data fetching
   - Proper resource cleanup

### Validation Workflow

```
User Prompt → Code Generation → Validation → Fixes → Final Code
                    ↓
              If validation fails
                    ↓
            Apply automatic fixes
                    ↓
          Re-validate until success
                    ↓
          Deliver validated code
```

### Validation Failure Handling

When validation fails, the system automatically updates the code with these steps:

1. **Error Analysis** - Identify the specific validation errors
2. **Fix Application** - Apply appropriate fixes based on error type
3. **Re-validation** - Validate again after fixes
4. **Iterative Repair** - Repeat until code is valid (max 3 iterations)
5. **Fallback Strategy** - If automatic fixes fail, provide detailed error report and manual fix instructions

### Automatic Fix Examples

#### Fix 1: Missing Imports
```python
# Before (error: NameError: name 'List' is not defined)
def calculate_prices(prices: List[float]) -> List[float]:

# After (automatic fix)
from typing import List, Dict, Optional
def calculate_prices(prices):
```

#### Fix 2: Encoding Issues
```python
# Before (error: SyntaxError: Non-ASCII character)
# Strategy description: Grid trading

# After (automatic fix)
# -*- coding: utf-8 -*-
# Strategy description: Grid trading
```

#### Fix 3: Python 3.5 Incompatibility
```python
# Before (error: SyntaxError in Python 3.5)
price = f"Current price: {current_price}"

# After (automatic fix)
price = "Current price: {}".format(current_price)
```

#### Fix 4: Import Path Issues
```python
# Before (error: ImportError: No module named 'hyperliquid_api')
from hyperliquid_api import HyperliquidClient

# After (automatic fix)
import sys
import os
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "api_wrappers"))
from hyperliquid_api import HyperliquidClient
```

## Supported Strategy Types

### 1. Technical Indicator Strategies
- **RSI-based**: Oversold/overbought trading
- **MACD-based**: Trend following with MACD crossovers
- **Moving Average**: SMA/EMA cross strategies
- **Bollinger Bands**: Mean reversion strategies

### 2. Advanced Trading Strategies
- **Grid Trading**: Price range trading with multiple orders
- **Mean Reversion**: Statistical arbitrage strategies
- **Trend Following**: Momentum-based strategies
- **Arbitrage**: Spot-perp or cross-exchange arbitrage

### 3. Signal-Driven Strategies
- **VibeTrading Integration**: Follow AI-generated trading signals
- **News-based**: React to market news and sentiment
- **Whale Activity**: Track large wallet movements
- **Funding Rate**: Funding rate arbitrage strategies

## How It Works

### Step 1: Prompt Analysis
The generator analyzes your natural language prompt to identify:
- Trading symbol (BTC, ETH, SOL, etc.)
- Strategy type (grid, RSI, signal-based, etc.)
- Key parameters (price ranges, grid counts, indicator values)
- Risk management preferences

### Step 2: Template Selection
Based on the analysis, the system selects the most appropriate template from:
- `templates/grid_trading.py` - Grid trading strategy template

### Step 3: Code Generation
The generator:
1. Fills template parameters with your values
2. Adds proper error handling and logging
3. Includes configuration management
4. Generates complete runnable code

### Step 4: Code Validation
The generated code is automatically validated and fixed:
1. **Syntax checking** - Ensure valid Python syntax
2. **Import verification** - Check all imports are resolvable
3. **Compatibility testing** - Verify Python 3.5+ compatibility
4. **Automatic fixes** - Apply fixes for common issues
5. **Re-validation** - Validate again after fixes
6. **Error reporting** - If fixes fail, provide detailed error report

### Validation Failure Handling
If validation fails after automatic fixes:
1. **Error Analysis Report** - Detailed breakdown of remaining issues
2. **Manual Fix Instructions** - Step-by-step guidance for manual fixes
3. **Fallback Template** - Option to use a simpler, validated template
4. **Support Contact** - Instructions for getting help

### Step 5: Output Delivery
You receive validated, runnable code including:
1. **Validated Python strategy file** - Fully tested and fixed
2. **Configuration template** - Stra