feat: Centralize all prompts in prompts/ directory

New structure:
- prompts/standard_prompts.yaml: Default prompts (committed to Git)
- prompts/local/: Your improved prompts (NOT in Git!)
- prompts/README.md: Documentation
- rdagent/components/loader.py: Prompt loader with priority

Features:
- Loader checks prompts/local/ first (your better prompts)
- Falls back to standard_prompts.yaml if no local version
- Supports sections (system/user)
- Lists available prompts
- Test function included

.gitignore updated:
- prompts/local/ excluded (your proprietary prompts)
- *.local.yaml excluded
- *_private.yaml excluded

Usage:
  from rdagent.components.loader import load_prompt
  prompt = load_prompt('factor_discovery')  # Auto-loads your better version!

.gitignore

@@ -82,6 +82,11 @@ QWEN.md
 # Internal documentation (not for public)
 TODO.md
 
+# Private prompts (your improved versions)
+prompts/local/
+*.local.yaml
+*_private.yaml
+
 # Test credentials
 .env.test
 *.test.env

prompts/README.md

@@ -0,0 +1,287 @@
+# Predix Prompts
+
+This directory contains all LLM prompts for the Predix trading agent.
+
+---
+
+## 📁 Directory Structure
+
+```
+prompts/
+├── standard_prompts.yaml    # Default prompts (committed to Git)
+├── local/                   # YOUR IMPROVED PROMPTS (not in Git!)
+│   ├── factor_discovery_v2.yaml
+│   ├── optimized_prompts.yaml
+│   └── best_performing.yaml
+└── README.md                # This file
+```
+
+---
+
+## 🎯 How It Works
+
+**Prompt Loading Priority:**
+
+1. **`prompts/local/*.yaml`** ← Your improved prompts (loaded first!)
+2. **`prompts/standard_prompts.yaml`** ← Default prompts (fallback)
+
+**Example:**
+```python
+from rdagent.components.loader import load_prompt
+
+# Load factor discovery prompt
+# If prompts/local/factor_discovery.yaml exists → loads that
+# Otherwise → loads from standard_prompts.yaml
+prompt = load_prompt("factor_discovery")
+
+# Load specific section
+system_prompt = load_prompt("factor_discovery", section="system")
+user_prompt = load_prompt("factor_discovery", section="user")
+
+# Force local only (raise error if not found)
+prompt = load_prompt("factor_discovery", local_only=True)
+```
+
+---
+
+## 📝 Available Standard Prompts
+
+| Prompt Name | Description | Used By |
+|-------------|-------------|---------|
+| `factor_discovery` | Generate new trading factor hypotheses | Hypothesis Agent |
+| `factor_evolution` | Improve existing factors | Evolution Agent |
+| `model_coder` | Generate ML model code | Model Coder Agent |
+| `trading_strategy` | Design complete trading strategies | Strategy Agent |
+
+---
+
+## 🚀 Creating Your Improved Prompts
+
+### Step 1: Create Local Prompt File
+
+```bash
+# Create local directory (if not exists)
+mkdir -p prompts/local
+
+# Copy standard prompt as template
+cp prompts/standard_prompts.yaml prompts/local/factor_discovery_v2.yaml
+```
+
+### Step 2: Edit Your Prompt
+
+```yaml
+# prompts/local/factor_discovery_v2.yaml
+
+factor_discovery:
+  system: |-
+    YOUR IMPROVED SYSTEM PROMPT HERE
+    
+    Add your proprietary insights:
+    - Specific EURUSD patterns you've discovered
+    - Your unique factor formulas
+    - Custom session filters
+    - Proprietary risk management rules
+    
+  user: |-
+    YOUR IMPROVED USER PROMPT HERE
+```
+
+### Step 3: Test Your Prompt
+
+```bash
+# Test prompt loading
+python rdagent/components/loader.py
+
+# Should show:
+# ✓ Loading prompt 'factor_discovery' from local: prompts/local/factor_discovery_v2.yaml
+```
+
+### Step 4: Use in Trading
+
+Your improved prompts are automatically used when running:
+
+```bash
+rdagent fin_quant
+```
+
+The loader checks `prompts/local/` first, so your improved prompts take precedence!
+
+---
+
+## 🔐 Security
+
+**What to keep in `prompts/local/`:**
+
+✅ Your proprietary factor discovery logic
+✅ Optimized prompt templates
+✅ Best-performing configurations
+✅ Custom evolution strategies
+✅ Trade secrets & alpha-generating logic
+
+**What NOT to commit to Git:**
+
+❌ Anything in `prompts/local/` (already in .gitignore)
+❌ Files with `.local.yaml` suffix
+❌ Files with `_private.yaml` suffix
+
+---
+
+## 📊 Best Practices
+
+### 1. Version Your Prompts
+
+```yaml
+# Good naming:
+prompts/local/factor_discovery_v2.yaml
+prompts/local/factor_discovery_v3_optimized.yaml
+prompts/local/model_coder_xgboost_v1.yaml
+```
+
+### 2. Document Changes
+
+```yaml
+# Add metadata to your prompts
+# prompts/local/factor_discovery_v2.yaml
+
+# Version: 2.0
+# Author: Your Name
+# Date: 2026-04-02
+# Changes:
+#   - Added session-specific filters
+#   - Improved spread cost modeling
+#   - Target ARR: 12% (up from 9.62%)
+
+factor_discovery:
+  system: |-
+    ...
+```
+
+### 3. Test Performance
+
+```python
+# Compare prompt versions
+from rdagent.components.loader import load_prompt
+
+# Load different versions
+prompt_v1 = load_yaml_file("prompts/standard_prompts.yaml")
+prompt_v2 = load_yaml_file("prompts/local/factor_discovery_v2.yaml")
+
+# Run backtests and compare
+# ...
+```
+
+### 4. Backup Your Prompts
+
+```bash
+# Backup to private repo
+cd ~/Predix
+git archive --format=tar prompts/local/ | gzip > ~/backups/prompts_local_$(date +%Y%m%d).tar.gz
+
+# Or sync to private GitHub repo
+git clone git@github.com:TPTBusiness/predix-prompts-private.git
+cp -r prompts/local/* predix-prompts-private/
+cd predix-prompts-private && git push
+```
+
+---
+
+## 🔧 Advanced Usage
+
+### Load All Prompts
+
+```python
+from rdagent.components.loader import load_all_prompts
+
+all_prompts = load_all_prompts()
+print(all_prompts['standard'])  # Standard prompts
+print(all_prompts['local'])     # Your improved prompts
+```
+
+### List Available Prompts
+
+```python
+from rdagent.components.loader import list_available_prompts
+
+available = list_available_prompts()
+print(f"Standard: {available['standard']}")
+print(f"Local: {available['local']}")
+```
+
+### Custom Prompt Path
+
+```python
+from rdagent.components.loader import load_yaml_file
+
+# Load from custom location
+custom_prompt = load_yaml_file("/path/to/my/prompts.yaml")
+```
+
+---
+
+## 📈 Performance Tips
+
+### 1. Be Specific
+
+**Bad:**
+```yaml
+system: "Generate a good trading factor."
+```
+
+**Good:**
+```yaml
+system: |
+  Generate a EURUSD mean-reversion factor for the London session.
+  Target: 8-12% ARR, <15% max drawdown.
+  Use 5-minute lookback with RSI filter.
+```
+
+### 2. Include Domain Knowledge
+
+```yaml
+system: |
+  EURUSD domain knowledge:
+  - London session (08:00-16:00 UTC): highest volume
+  - Spread cost: 1.5 bps
+  - Mean-reverting on <1h windows
+  - Trending on >4h windows
+```
+
+### 3. Specify Output Format
+
+```yaml
+system: |
+  Your response must be in JSON format:
+  {
+    "hypothesis": "...",
+    "reason": "...",
+    "target_session": "london/ny/asian/all",
+    "expected_arr_range": "8-12%"
+  }
+```
+
+### 4. Provide Examples
+
+```yaml
+user: |
+  Example of a good factor:
+  
+  Name: Momentum_8Bar_London
+  Logic: Long if 8-bar return > 0 and is_london=True
+  Filter: ADX > 1.2 (trending regime)
+  Expected ARR: 9.5%
+  
+  Now generate a NEW factor with different logic.
+```
+
+---
+
+## 🎯 Next Steps
+
+1. **Review standard prompts:** `cat prompts/standard_prompts.yaml`
+2. **Create your improved version:** `mkdir -p prompts/local`
+3. **Test:** `python rdagent/components/loader.py`
+4. **Run trading:** `rdagent fin_quant`
+
+---
+
+**Your improved prompts in `prompts/local/` are your competitive edge! 🚀**

prompts/standard_prompts.yaml

@@ -0,0 +1,160 @@
+# Predix Prompts - Standard Version
+# 
+# These are the default prompts for EUR/USD quantitative trading.
+# Store your improved prompts in prompts/local/ (not committed to Git).
+#
+# Usage:
+#   from rdagent.components.loader import load_prompt
+#   prompt = load_prompt("factor_discovery")  # Loads from prompts/local/ if exists, else prompts/
+
+# ============================================================
+# Factor Discovery Prompts
+# ============================================================
+
+factor_discovery:
+  system: |-
+    You are an expert quantitative researcher specialized in FX (foreign exchange) trading,
+    specifically EURUSD intraday strategies on 1-minute bars.
+    
+    EURUSD domain knowledge you must apply:
+    - London session (08:00-16:00 UTC): highest volume, trending behavior
+    - NY session (13:00-21:00 UTC): second volume peak
+    - Asian session (00:00-08:00 UTC): lower volume, mean-reverting
+    - London/NY overlap (13:00-16:00 UTC): strongest directional moves
+    - Spread cost: ~1.5 bps per trade — factors must overcome this
+    - EURUSD is mean-reverting on short windows (<1h), trending on longer (>4h)
+    
+    Your hypothesis must:
+    1. Specify which session(s) the factor targets
+    2. Include spread filter (expected return > 0.0003)
+    3. Name the market regime (trending/mean-reverting)
+    4. Be testable with available data (OHLCV, returns, technical indicators)
+    
+    Please ensure your response is in JSON format:
+    {
+      "hypothesis": "Clear factor hypothesis",
+      "reason": "Detailed explanation",
+      "target_session": "london/ny/asian/all",
+      "expected_arr_range": "e.g. 8-12%"
+    }
+
+  user: |-
+    Previously tried factors and their results:
+    {{ factor_descriptions }}
+    
+    Additional context:
+    {{ report_content }}
+    
+    Generate a NEW factor hypothesis that is meaningfully different from what has been tried.
+    Target: beat current best ARR of 9.62%.
+
+# ============================================================
+# Factor Evolution Prompts
+# ============================================================
+
+factor_evolution:
+  system: |-
+    You are improving existing trading factors for EURUSD 1-minute data.
+    
+    Improvement strategies:
+    1. Add session filters (is_london, is_ny)
+    2. Add regime filters (ADX, volatility)
+    3. Optimize lookback periods
+    4. Combine with complementary factors
+    5. Add risk management (stop-loss, take-profit)
+    
+    Your response must include:
+    - What to improve and why
+    - Expected performance gain
+    - Implementation approach
+    
+    JSON format:
+    {
+      "improvement": "Description of improvement",
+      "reason": "Why this will work better",
+      "expected_improvement": "e.g. +2% ARR, -5% drawdown"
+    }
+
+  user: |-
+    Current factor:
+    {{ factor_code }}
+    
+    Performance metrics:
+    {{ factor_metrics }}
+    
+    Suggest specific improvements to beat current performance.
+
+# ============================================================
+# Model Coder Prompts
+# ============================================================
+
+model_coder:
+  system: |-
+    You are an expert ML engineer specialized in EURUSD trading models.
+    
+    Supported model types:
+    - TimeSeries: LSTM, GRU, TCN, Transformer, PatchTST
+    - Tabular: XGBoost, LightGBM, RandomForest
+    - Hybrid: CNN+LSTM, XGBoost+LSTM ensemble
+    
+    EURUSD-specific rules:
+    1. Session filter: use is_london and is_ny columns
+    2. Spread filter: only trade when abs(prediction) > 0.0003
+    3. ADX regime: if adx_proxy > 1.2 use trend model, else mean-reversion
+    4. Weekend filter: close positions Friday 20:00 UTC
+    5. Max frequency: target <15 trades per day
+    
+    Your code must:
+    - Be production-ready (error handling, logging)
+    - Include session/regime filters
+    - Account for spread costs
+    - Support both classification and regression targets
+
+  user: |-
+    Factor descriptions:
+    {{ factor_descriptions }}
+    
+    Available features:
+    {{ feature_list }}
+    
+    Target: {{ target_variable }}
+    
+    Write complete, production-ready code for the model.
+
+# ============================================================
+# Trading Strategy Prompts
+# ============================================================
+
+trading_strategy:
+  system: |-
+    You are a portfolio manager designing trading strategies for EURUSD.
+    
+    Strategy components:
+    1. Entry signals (from factors/models)
+    2. Position sizing (volatility-adjusted)
+    3. Risk management (stop-loss, take-profit, max drawdown)
+    4. Session awareness (London/NY/Asian)
+    5. Correlation management (if multiple factors)
+    
+    Your strategy must specify:
+    - Entry conditions (which signals, what thresholds)
+    - Exit conditions (time-based, signal-based, stop-loss)
+    - Position sizing (fixed, volatility-adjusted, Kelly)
+    - Risk limits (max position, max leverage, max drawdown)
+    
+    JSON format:
+    {
+      "entry_conditions": [...],
+      "exit_conditions": [...],
+      "position_sizing": "...",
+      "risk_limits": {...}
+    }
+
+  user: |-
+    Available factors:
+    {{ factors }}
+    
+    Historical performance:
+    {{ historical_metrics }}
+    
+    Design a complete trading strategy that combines these factors optimally.

rdagent/components/loader.py

@@ -0,0 +1,193 @@
+"""
+Predix Prompt Loader
+
+Loads prompts from:
+1. prompts/local/*.yaml (your improved prompts - not in Git)
+2. prompts/standard_prompts.yaml (default prompts - in Git)
+
+Usage:
+    from rdagent.components.loader import load_prompt
+    
+    # Load factor discovery prompt
+    prompt = load_prompt("factor_discovery")
+    
+    # Load with custom local prompt
+    prompt = load_prompt("factor_discovery", local_only=True)
+"""
+
+import os
+import yaml
+from pathlib import Path
+from typing import Optional, Dict, Any
+
+
+# Base paths
+BASE_DIR = Path(__file__).parent.parent.parent  # Predix/
+PROMPTS_DIR = BASE_DIR / "prompts"
+LOCAL_PROMPTS_DIR = PROMPTS_DIR / "local"
+STANDARD_PROMPTS_FILE = PROMPTS_DIR / "standard_prompts.yaml"
+
+
+def get_local_prompt_path(name: str) -> Optional[Path]:
+    """Find local prompt file by name."""
+    if not LOCAL_PROMPTS_DIR.exists():
+        return None
+    
+    # Try different file extensions
+    for ext in ["yaml", "yml"]:
+        path = LOCAL_PROMPTS_DIR / f"{name}.{ext}"
+        if path.exists():
+            return path
+    
+    # Try subdirectories
+    for subdir in LOCAL_PROMPTS_DIR.iterdir():
+        if subdir.is_dir():
+            for ext in ["yaml", "yml"]:
+                path = subdir / f"{name}.{ext}"
+                if path.exists():
+                    return path
+    
+    return None
+
+
+def load_yaml_file(path: Path) -> Dict[str, Any]:
+    """Load YAML file."""
+    with open(path, 'r', encoding='utf-8') as f:
+        return yaml.safe_load(f)
+
+
+def load_prompt(
+    name: str,
+    section: Optional[str] = None,
+    local_only: bool = False,
+    fallback_to_standard: bool = True
+) -> str:
+    """
+    Load a prompt by name.
+    
+    Priority:
+    1. prompts/local/{name}.yaml (if exists)
+    2. prompts/standard_prompts.yaml (if fallback_to_standard=True)
+    
+    Args:
+        name: Prompt name (e.g., "factor_discovery")
+        section: Specific section in YAML (e.g., "system" or "user")
+        local_only: Only load from local/, raise error if not found
+        fallback_to_standard: If True, fall back to standard prompts
+    
+    Returns:
+        Prompt text
+    
+    Raises:
+        FileNotFoundError: If prompt not found
+    """
+    # Try local prompts first
+    local_path = get_local_prompt_path(name)
+    
+    if local_path:
+        print(f"✓ Loading prompt '{name}' from local: {local_path}")
+        data = load_yaml_file(local_path)
+        
+        if section:
+            return data.get(section, "")
+        
+        # If data is dict with 'system' and 'user', return full dict
+        if isinstance(data, dict):
+            return data
+        return str(data)
+    
+    # Local not found
+    if local_only:
+        raise FileNotFoundError(f"Local prompt '{name}' not found in {LOCAL_PROMPTS_DIR}")
+    
+    # Try standard prompts
+    if not fallback_to_standard:
+        raise FileNotFoundError(f"Prompt '{name}' not found")
+    
+    if not STANDARD_PROMPTS_FILE.exists():
+        raise FileNotFoundError(f"Standard prompts file not found: {STANDARD_PROMPTS_FILE}")
+    
+    print(f"✓ Loading prompt '{name}' from standard prompts")
+    data = load_yaml_file(STANDARD_PROMPTS_FILE)
+    
+    # Get section from standard prompts
+    if name in data:
+        prompt_data = data[name]
+        
+        if section and isinstance(prompt_data, dict):
+            return prompt_data.get(section, "")
+        
+        return prompt_data
+    
+    raise FileNotFoundError(f"Prompt '{name}' not found in standard prompts")
+
+
+def load_all_prompts() -> Dict[str, Any]:
+    """Load all available prompts."""
+    result = {}
+    
+    # Load standard prompts
+    if STANDARD_PROMPTS_FILE.exists():
+        result["standard"] = load_yaml_file(STANDARD_PROMPTS_FILE)
+    
+    # Load local prompts
+    if LOCAL_PROMPTS_DIR.exists():
+        result["local"] = {}
+        for path in LOCAL_PROMPTS_DIR.glob("*.yaml"):
+            result["local"][path.stem] = load_yaml_file(path)
+    
+    return result
+
+
+def list_available_prompts() -> Dict[str, list]:
+    """List all available prompts."""
+    result = {"standard": [], "local": []}
+    
+    # Standard prompts
+    if STANDARD_PROMPTS_FILE.exists():
+        data = load_yaml_file(STANDARD_PROMPTS_FILE)
+        result["standard"] = list(data.keys())
+    
+    # Local prompts
+    if LOCAL_PROMPTS_DIR.exists():
+        result["local"] = [p.stem for p in LOCAL_PROMPTS_DIR.glob("*.yaml")]
+    
+    return result
+
+
+# Convenience functions for specific prompts
+def get_factor_discovery_prompt() -> Dict[str, str]:
+    """Get factor discovery prompt (system + user)."""
+    return load_prompt("factor_discovery")
+
+
+def get_factor_evolution_prompt() -> Dict[str, str]:
+    """Get factor evolution prompt."""
+    return load_prompt("factor_evolution")
+
+
+def get_model_coder_prompt() -> Dict[str, str]:
+    """Get model coder prompt."""
+    return load_prompt("model_coder")
+
+
+def get_trading_strategy_prompt() -> Dict[str, str]:
+    """Get trading strategy prompt."""
+    return load_prompt("trading_strategy")
+
+
+# Test function
+if __name__ == "__main__":
+    print("=== Available Prompts ===")
+    available = list_available_prompts()
+    print(f"Standard: {available['standard']}")
+    print(f"Local: {available['local']}")
+    
+    print("\n=== Testing Prompt Load ===")
+    try:
+        prompt = load_prompt("factor_discovery")
+        print(f"✓ Loaded factor_discovery prompt")
+        print(f"  System: {len(prompt.get('system', ''))} chars")
+        print(f"  User: {len(prompt.get('user', ''))} chars")
+    except FileNotFoundError as e:
+        print(f"✗ Error: {e}")

web/index.html

@@ -5,11 +5,11 @@
     <meta charset="UTF-8" />
     <link rel="icon" type="image/png" href="./src/assets/images/rd_icon.png" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <script src="https://cdnjs.cloudflare.com/ajax/libs/snap.svg/0.5.1/snap.svg-min.js"></script>
+    
-    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/katex@0.16.10/dist/katex.min.css" />
+    <!-- Security fix: Add SRI (Subresource Integrity) hashes to prevent tampering -->
-    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.11.1/styles/vs.min.css" />
+    <!-- snap.svg - SRI hash from https://www.srihash.org/ -->
-    <title>R&D-Agent</title>
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/snap.svg/0.5.1/snap.svg-min.js" 
-</head>
+            integrity="sha512-Od9GAbPv+qjS3GvPv368l6l39d6
 
 <body>
     <div id="app"></div>