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Found 11 Skills
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.
Production-grade AI agent patterns with MCP integration, agentic RAG, handoff orchestration, multi-layer guardrails, observability, token economics, ROI frameworks, and build-vs-not decision guidance (modern best practices)
Integration patterns for LangChain4j with Spring Boot. Auto-configuration, dependency injection, and Spring ecosystem integration. Use when embedding LangChain4j into Spring Boot applications.
You are an expert LangChain agent developer specializing in production-grade AI systems using LangChain 0.1+ and LangGraph.
You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and AI-powered applications. Design comprehensive AI assistant solutions with natur
Expert guidance for LlamaIndex development including RAG applications, vector stores, document processing, query engines, and building production AI applications.
Generate production-ready fal.ai workflow JSON files. Use when user requests "create workflow", "chain models", "multi-step generation", "image to video pipeline", or complex AI generation pipelines.
Comprehensive guide for building production-grade LLM applications using LangChain's chains, agents, memory systems, RAG patterns, and advanced orchestration
This skill should be used when the user asks to "create custom DSPy module", "design a DSPy module", "extend dspy.Module", "build reusable DSPy component", mentions "custom module patterns", "module serialization", "stateful modules", "module testing", or needs to design production-quality custom DSPy modules with proper architecture, state management, and testing.
LLM and ML model deployment for inference. Use when serving models in production, building AI APIs, or optimizing inference. Covers vLLM (LLM serving), TensorRT-LLM (GPU optimization), Ollama (local), BentoML (ML deployment), Triton (multi-model), LangChain (orchestration), LlamaIndex (RAG), and streaming patterns.
Create production-ready skills from expert knowledge. Extracts domain expertise and system ontologies, uses scripts for deterministic work, loads knowledge progressively. Use when building skills that must work reliably in production.