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Adoption Paths

Lexigram is designed for incremental adoption. You don’t need to install everything at once — start with the core and add packages as your application grows.

The minimal foundation: dependency injection, application structure, and a Result type.

  • lexigram + lexigram-contracts — Core: DI container, Application abstraction, Configuration, structured logging, Result type
  • Add lexigram-web → Build an HTTP API with routing, middleware, request validation, and error handling
  • Configuration via YAML files, structured logging built in

Add persistence, caching, authentication, and developer tooling.

  • Add lexigram-sql → Database persistence with migrations, repositories, and query building
  • Add lexigram-cache → Response caching, session store, rate limiter backing
  • Add lexigram-auth → JWT authentication, RBAC, route guards, password hashing
  • Add lexigram-cli → Development server, database migrations, code scaffolding
  • Add lexigram-testing → Fakes, test beds, and compliance test suites

Search, file storage, background jobs, event-driven architecture, notifications, and multi-tenancy.

  • Add lexigram-search → Full-text search with Meilisearch, Elasticsearch, or Typesense
  • Add lexigram-storage → File uploads, CDN integration, presigned URLs
  • Add lexigram-tasks → Background job processing, cron scheduling, task queues
  • Add lexigram-events → Event-driven architecture, CQRS, domain events
  • Add lexigram-notification → Email, SMS, and push notification delivery
  • Add lexigram-webhook → Outbound webhook dispatch with retry and signing
  • Add lexigram-monitor + lexigram-resilience → Health checks, metrics, circuit breakers, retry policies
  • Add lexigram-tenancy → Multi-tenant SaaS support with data isolation

Add LLM integration, RAG, agents, memory, and production AI infrastructure.

  • Add lexigram-ai-llm → LLM integration with provider routing (OpenAI, Anthropic, Google, local)
  • Add lexigram-ai-rag + lexigram-vector → RAG pipeline with document ingestion, chunking, embedding, and hybrid search
  • Add lexigram-ai-agents + lexigram-ai-skills → AI agents with tool use, multi-step reasoning, and sub-agent delegation
  • Add lexigram-ai-memory + lexigram-ai-session → Persistent conversation history, episodic and semantic memory
  • Add lexigram-ai-mcp → MCP server and client — expose agents as MCP tools, connect to external MCP servers
  • Add lexigram-ai-workers + lexigram-ai-observability + lexigram-ai-feedback → Background processing, token usage tracking, cost attribution, feedback collection
Starting a new project?
├── Prototype or microservice → **Tier 1**
├── Standard web app or API → **Tier 2**
├── Scaling app with advanced needs → **Tier 3**
└── Building AI features → **Tier 2 first**, then **Tier 4**

Each tier is a superset of the one before it. You can move between tiers as your requirements evolve — no rewrite needed.


See Choosing Backends to pick the right infrastructure for each package, and Compatibility & Dependencies for version requirements and known constraints.