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91 lines
3.9 KiB
Markdown
91 lines
3.9 KiB
Markdown
# LLM Application Development Plugin for Claude Code
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Build production-ready LLM applications, advanced RAG systems, and intelligent agents with modern AI patterns.
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## Version 2.0.0 Highlights
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- **LangGraph Integration**: Updated from deprecated LangChain patterns to LangGraph StateGraph workflows
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- **Modern Model Support**: Claude Opus/Sonnet/Haiku 4.5 and GPT-5.2/GPT-5.2-mini
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- **Voyage AI Embeddings**: Recommended embedding models for Claude applications
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- **Structured Outputs**: Pydantic-based structured output patterns
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## Features
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### Core Capabilities
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- **RAG Systems**: Production retrieval-augmented generation with hybrid search
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- **Vector Search**: Pinecone, Qdrant, Weaviate, Milvus, pgvector optimization
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- **Agent Architectures**: LangGraph-based agents with memory and tool use
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- **Prompt Engineering**: Advanced prompting techniques with model-specific optimization
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### Key Technologies
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- LangChain 1.x / LangGraph for agent workflows
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- Voyage AI, OpenAI, and open-source embedding models
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- HNSW, IVF, and Product Quantization index strategies
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- Async patterns with checkpointers for durable execution
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## Agents
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| Agent | Description |
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| -------------------------- | -------------------------------------------------------------------------- |
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| `ai-engineer` | Production-grade LLM applications, RAG systems, and agent architectures |
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| `prompt-engineer` | Advanced prompting techniques, constitutional AI, and model optimization |
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| `vector-database-engineer` | Vector search implementation, embedding strategies, and semantic retrieval |
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## Skills
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| Skill | Description |
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| ------------------------------ | ----------------------------------------------------------- |
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| `langchain-architecture` | LangGraph StateGraph patterns, memory, and tool integration |
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| `rag-implementation` | RAG systems with hybrid search and reranking |
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| `llm-evaluation` | Evaluation frameworks for LLM applications |
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| `prompt-engineering-patterns` | Chain-of-thought, few-shot, and structured outputs |
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| `embedding-strategies` | Embedding model selection and optimization |
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| `similarity-search-patterns` | Vector similarity search implementation |
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| `vector-index-tuning` | HNSW, IVF, and quantization optimization |
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| `hybrid-search-implementation` | Vector + keyword search fusion |
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## Commands
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| Command | Description |
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| -------------------------------------- | ------------------------------- |
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| `/llm-application-dev:langchain-agent` | Create LangGraph-based agent |
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| `/llm-application-dev:ai-assistant` | Build AI assistant application |
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| `/llm-application-dev:prompt-optimize` | Optimize prompts for production |
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## Installation
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```bash
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claude --plugin-dir /path/to/llm-application-dev
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```
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Or copy to your project's `.claude-plugin/` directory.
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## Requirements
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- LangChain >= 1.2.0
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- LangGraph >= 0.3.0
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- Python 3.11+
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## Changelog
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### 2.0.0 (January 2026)
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- **Breaking**: Migrated from LangChain 0.x to LangChain 1.x/LangGraph
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- **Breaking**: Updated model references to Claude 4.5 and GPT-5.2
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- Added Voyage AI as primary embedding recommendation for Claude apps
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- Added LangGraph StateGraph patterns replacing deprecated `initialize_agent()`
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- Added structured outputs with Pydantic
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- Added async patterns with checkpointers
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- Fixed security issue: replaced unsafe code execution with AST-based safe math evaluation
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- Updated hybrid search with modern Pinecone client API
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### 1.2.2
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- Minor bug fixes and documentation updates
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## License
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MIT License - See the plugin configuration for details.
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