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Adds awareness of Oracle Cloud Infrastructure to any plugin that referenced at least two of the major cloud vendors already. Skills updated to include OCI services. Also updated some of the other cloud references. Signed-off-by: Avi Miller <me@dje.li>
LLM Application Development Plugin for Claude Code
Build production-ready LLM applications, advanced RAG systems, and intelligent agents with modern AI patterns.
Version 2.0.0 Highlights
- LangGraph Integration: Updated from deprecated LangChain patterns to LangGraph StateGraph workflows
- Modern Model Support: Claude Opus 4.6/Sonnet 4.6/Haiku 4.5 and GPT-5.2/GPT-5-mini
- Voyage AI Embeddings: Recommended embedding models for Claude applications
- Structured Outputs: Pydantic-based structured output patterns
Features
Core Capabilities
- RAG Systems: Production retrieval-augmented generation with hybrid search
- Vector Search: Pinecone, Qdrant, Weaviate, Milvus, pgvector optimization
- Agent Architectures: LangGraph-based agents with memory and tool use
- Prompt Engineering: Advanced prompting techniques with model-specific optimization
Key Technologies
- LangChain 1.x / LangGraph for agent workflows
- Voyage AI, OpenAI, and open-source embedding models
- HNSW, IVF, and Product Quantization index strategies
- Async patterns with checkpointers for durable execution
Agents
| Agent | Description |
|---|---|
ai-engineer |
Production-grade LLM applications, RAG systems, and agent architectures |
prompt-engineer |
Advanced prompting techniques, constitutional AI, and model optimization |
vector-database-engineer |
Vector search implementation, embedding strategies, and semantic retrieval |
Skills
| Skill | Description |
|---|---|
langchain-architecture |
LangGraph StateGraph patterns, memory, and tool integration |
rag-implementation |
RAG systems with hybrid search and reranking |
llm-evaluation |
Evaluation frameworks for LLM applications |
prompt-engineering-patterns |
Chain-of-thought, few-shot, and structured outputs |
embedding-strategies |
Embedding model selection and optimization |
similarity-search-patterns |
Vector similarity search implementation |
vector-index-tuning |
HNSW, IVF, and quantization optimization |
hybrid-search-implementation |
Vector + keyword search fusion |
Commands
| Command | Description |
|---|---|
/llm-application-dev:langchain-agent |
Create LangGraph-based agent |
/llm-application-dev:ai-assistant |
Build AI assistant application |
/llm-application-dev:prompt-optimize |
Optimize prompts for production |
Installation
/plugin install llm-application-dev
Requirements
- LangChain >= 1.2.0
- LangGraph >= 0.3.0
- Python 3.11+
Changelog
2.0.0 (January 2026)
- Breaking: Migrated from LangChain 0.x to LangChain 1.x/LangGraph
- Breaking: Updated model references to Claude 4.6 and GPT-5.2
- Added Voyage AI as primary embedding recommendation for Claude apps
- Added LangGraph StateGraph patterns replacing deprecated
initialize_agent() - Added structured outputs with Pydantic
- Added async patterns with checkpointers
- Fixed security issue: replaced unsafe code execution with AST-based safe math evaluation
- Updated hybrid search with modern Pinecone client API
1.2.2
- Minor bug fixes and documentation updates
License
MIT License - See the plugin configuration for details.