mirror of
https://github.com/wshobson/agents.git
synced 2026-03-18 09:37:15 +00:00
086557180a
- Claude Opus 4.5 → Opus 4.6, Claude Sonnet 4.5 → Sonnet 4.6 (Haiku stays 4.5) - Update claude-sonnet-4-5 model IDs to claude-sonnet-4-6 in code examples - Update SWE-bench stat from 80.9% to 80.8% for Opus 4.6 - Update GPT refs: GPT-5 → GPT-5.2, GPT-4o → gpt-5.2, GPT-4o-mini → GPT-5-mini - Fix GPT-5.2-mini → GPT-5-mini (correct model name per OpenAI) - Bump marketplace to v1.5.2 and affected plugin versions
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.