LangChain
Skill Verified ActiveFramework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.
To provide developers with a robust and flexible framework for building sophisticated LLM applications, agents, and RAG systems, streamlining the development process from prototyping to production.
Features
- Framework for LLM applications (agents, chains, RAG)
- Multi-provider LLM support (OpenAI, Anthropic, Google)
- Extensive integrations (500+ tools, vector stores)
- Support for ReAct agents and tool calling
- Memory management for conversational context
- Vector store retrieval for RAG pipelines
Use Cases
- Building chatbots with conversation memory
- Implementing retrieval-augmented generation (RAG) pipelines
- Creating agents with tool-using capabilities
- Rapid prototyping of LLM-powered applications
- Production deployments with observability (LangSmith)
Non-Goals
- Specific LLM model training or fine-tuning
- Deep dive into individual vector database management
- Standalone deployment of applications (focus on framework)
- Low-level AI research beyond application development
Workflow
- Define LLM models and tools
- Construct chains or agents for task execution
- Integrate memory for conversational context
- Implement RAG pipelines with document loading, splitting, embedding, and retrieval
- Execute and observe application behavior using LangSmith
Practices
- LLM Application Development
- Agent Design
- RAG Implementation
- Tool Integration
- Observability
Prerequisites
- Python 3.10+
- LLM provider API keys (OpenAI, Anthropic, etc.)
- Optional: Vector database setup
- Optional: LangSmith API key for tracing
Scope
- info:Tool surface sizeWhile not explicitly counting tools, the documentation showcases numerous integrations and patterns, suggesting a large but well-categorized surface area.
Installation
First, add the marketplace
/plugin marketplace add Orchestra-Research/AI-Research-SKILLs/plugin install AI-Research-SKILLs@ai-research-skillsQuality Score
VerifiedTrust Signals
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