Implement hierarchical configuration for LLM parameters with support for:
- Temperature control (0.0-2.0) to adjust response creativity
- Custom base_url for proxy servers and alternative endpoints
- 4-tier priority: request params > provider env > global env > defaults
Add helper functions in utils.py, update API schemas and handlers,
support environment variables (LLM_TEMPERATURE, OPENAI_TEMPERATURE, etc.),
and provide comprehensive documentation with examples.
- Support LLM_PROVIDER env var to override default provider (openai/gpt-4o-mini)
- Add optional 'provider' parameter to API endpoints for per-request overrides
- Implement provider validation to ensure API keys exist
- Update documentation and examples with new configuration options
Closes the need to hardcode providers in config.yml
Add comprehensive Docker deployment configuration with:
- New .dockerignore and .llm.env.example files
- Enhanced Dockerfile with multi-stage build and optimizations
- Detailed README with setup instructions and environment configurations
- Improved requirements.txt with Gunicorn
- Better error handling in async_configs.py
BREAKING CHANGE: Docker deployment now requires .llm.env file for API keys
