feat: Add comprehensive dynamic configuration system v3.3.0

## Major Features Added

### 🎯 Dynamic Configuration System
- **Environment-aware model selection**: DEFAULT_MODEL with 'pro'/'flash' shortcuts
- **Configurable thinking modes**: DEFAULT_THINKING_MODE_THINKDEEP for extended reasoning
- **All tool schemas now dynamic**: Show actual current defaults instead of hardcoded values
- **Enhanced setup workflow**: Copy from .env.example with smart customization

### 🔧 Model & Thinking Configuration
- **Smart model resolution**: Support both shortcuts ('pro', 'flash') and full model names
- **Thinking mode optimization**: Only apply thinking budget to models that support it
- **Flash model compatibility**: Works without thinking config, still beneficial via system prompts
- **Dynamic schema descriptions**: Tool parameters show current environment values

### 🚀 Enhanced Developer Experience
- **Fail-fast Docker setup**: GEMINI_API_KEY required upfront in docker-compose
- **Comprehensive startup logging**: Shows current model and thinking mode defaults
- **Enhanced get_version tool**: Reports all dynamic configuration values
- **Better .env documentation**: Clear token consumption details and model options

### 🧪 Comprehensive Testing
- **Live model validation**: New simulator test validates Pro vs Flash thinking behavior
- **Dynamic configuration tests**: Verify environment variable overrides work correctly
- **Complete test coverage**: All 139 unit tests pass, including new model config tests

### 📋 Configuration Files Updated
- **docker-compose.yml**: Fail-fast API key validation, thinking mode support
- **setup-docker.sh**: Copy from .env.example instead of manual creation
- **.env.example**: Detailed documentation with token consumption per thinking mode
- **.gitignore**: Added test-setup/ for cleanup

### 🛠 Technical Improvements
- **Removed setup.py**: Fully Docker-based deployment (no longer needed)
- **REDIS_URL smart defaults**: Auto-configured for Docker, still configurable for dev
- **All tools updated**: Consistent dynamic model parameter descriptions
- **Enhanced error handling**: Better model resolution and validation

## Breaking Changes
- Removed setup.py (Docker-only deployment)
- Model parameter descriptions now show actual defaults (dynamic)

## Migration Guide
- Update .env files using new .env.example format
- Use 'pro'/'flash' shortcuts or full model names
- Set DEFAULT_THINKING_MODE_THINKDEEP for custom thinking depth

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

config.py

@@ -13,15 +13,15 @@ import os
 # Version and metadata
 # These values are used in server responses and for tracking releases
 # IMPORTANT: This is the single source of truth for version and author info
-# setup.py imports these values to avoid duplication
-__version__ = "3.2.0"  # Semantic versioning: MAJOR.MINOR.PATCH
-__updated__ = "2025-06-10"  # Last update date in ISO format
+__version__ = "3.3.0"  # Semantic versioning: MAJOR.MINOR.PATCH
+__updated__ = "2025-06-11"  # Last update date in ISO format
 __author__ = "Fahad Gilani"  # Primary maintainer
 
 # Model configuration
-# GEMINI_MODEL: The Gemini model used for all AI operations
+# DEFAULT_MODEL: The default model used for all AI operations
 # This should be a stable, high-performance model suitable for code analysis
-GEMINI_MODEL = "gemini-2.5-pro-preview-06-05"
+# Can be overridden by setting DEFAULT_MODEL environment variable
+DEFAULT_MODEL = os.getenv("DEFAULT_MODEL", "gemini-2.5-pro-preview-06-05")
 
 # Token allocation for Gemini Pro (1M total capacity)
 # MAX_CONTEXT_TOKENS: Total model capacity
@@ -48,6 +48,11 @@ TEMPERATURE_BALANCED = 0.5  # For general chat
 # Used when brainstorming, exploring alternatives, or architectural discussions
 TEMPERATURE_CREATIVE = 0.7  # For architecture, deep thinking
 
+# Thinking Mode Defaults
+# DEFAULT_THINKING_MODE_THINKDEEP: Default thinking depth for extended reasoning tool
+# Higher modes use more computational budget but provide deeper analysis
+DEFAULT_THINKING_MODE_THINKDEEP = os.getenv("DEFAULT_THINKING_MODE_THINKDEEP", "high")
+
 # MCP Protocol Limits
 # MCP_PROMPT_SIZE_LIMIT: Maximum character size for prompts sent directly through MCP
 # The MCP protocol has a combined request+response limit of ~25K tokens.