Llamaindex agent
Skill a5c-ai/babysitter/library/specializations/ai-agents-conversational/skills/llamaindex-agent
Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration
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LlamaIndex agent and query engine setup for RAG-powered agents
SKILL.md
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LlamaIndex Agent Skill
Capabilities
- Set up LlamaIndex query engines
- Configure ReAct agents with tools
- Implement OpenAI function calling agents
- Design sub-question query engines
- Set up multi-document agents
- Implement chat engines with memory
Target Processes
- rag-pipeline-implementation
- knowledge-base-qa
Implementation Details
Agent Types
- ReActAgent: Reasoning and acting agent
- OpenAIAgent: Function calling agent
- StructuredPlannerAgent: Plan-and-execute style
- SubQuestionQueryEngine: Complex query decomposition
Query Engine Types
- VectorStoreIndex query engine
- Summary index query engine
- Knowledge graph query engine
- SQL query engine
Configuration Options
- LLM selection
- Tool definitions
- Memory configuration
- Verbose/debug settings
- Query transform modules
Best Practices
- Appropriate index selection
- Clear tool descriptions
- Memory for multi-turn
- Monitor query performance
Dependencies
- llama-index
- llama-index-agent-openai