Agent Library
The CAP Agent Library provides a collection of pre-built agents and templates that you can use as starting points for your own implementations. Each agent is designed to showcase different capabilities and architectural patterns.
CAP Engine Implementations
| Engine | Description | Key Features | Use Cases |
|---|---|---|---|
| CAP Engine Lite CE | Lightweight version of CAP Engine optimized for personal and research use | - LangGraph orchestration - Document indexing - Retrieval capabilities | - Research projects - Personal assistants - Learning implementations |
| CAP Engine LangGraph MCP | Universal Assistant implementation using Model Context Protocol | - Multi-agent patterns - External tool integration - Context management | - Enterprise assistants - Tool orchestration - Complex workflows |
| CAP Engine LangGraph Lite | Retrieval-based chatbot template with vector storage | - Vector search - Document retrieval - Conversation management | - Knowledge bases - Documentation helpers - Support systems |
| CAP Engine Software Engineering Agent | AI software engineer | - develop new features - fix bugs - parallel repository processing | - deploy - smooth chat interface - Support systems |
All CAP Engines are LangGraph implementations.
LangGraph Reference Implementations
Conversation Agents
| Agent | Description | Key Features |
|---|---|---|
| Customer Support Agent | Multi-persona support system with routing | - Role-based routing - Support specialization - Human handoff |
| Multi-Agent Collaboration | Framework for agent cooperation | - Inter-agent communication - Task delegation - Shared context |
Retrieval & Research
| Agent | Description | Key Features |
|---|---|---|
| Agentic RAG | Advanced retrieval-augmented generation | - Dynamic retrieval - Context evaluation - Answer synthesis |
| Self-RAG | Self-reflective retrieval system | - Quality assessment - Answer verification - Iterative improvement |
Task Planning
| Agent | Description | Key Features |
|---|---|---|
| Plan and Execute | Task decomposition and execution | - Goal breakdown - Sequential execution - Progress tracking |
| Reflection Agent | Self-improving task execution | - Performance analysis - Strategy adjustment - Learning from mistakes |
Getting Started
- Choose an agent template that matches your use case
- Follow the setup instructions in the respective repository
- Customize the agent's behavior and capabilities
- Deploy using our deployment guides
Need Help?
- Contact our team for implementation support
- Join our community forums for discussions
- Check out tutorials for detailed guides