This skill automates the creation of a robust, multi-environment architecture for LangChain applications, enabling seamless transitions between development, staging, and production tiers. It implements a hierarchical configuration system using YAML and Pydantic for type-safety, integrates secure secrets management via GCP or local environment variables, and provides environment-aware LLM factories. This ensures that your AI agents use the appropriate models, caching strategies, and tracing projects based on their deployment context, significantly reducing configuration errors and security risks.
Key Features
01Pre-configured Docker Compose setup for local development with Redis integration
02Type-safe settings management using Pydantic and Pydantic-Settings
03Environment-aware LLM factory for switching providers and models dynamically
04Hierarchical YAML configuration with environment-specific overrides
050 GitHub stars
06Secure secrets handling with GCP Secret Manager and local .env support
