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Babysitter llamaindex-agent

LlamaIndex agent and query engine setup for RAG-powered agents

install
source · Clone the upstream repo
git clone https://github.com/a5c-ai/babysitter
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/ai-agents-conversational/skills/llamaindex-agent" ~/.claude/skills/a5c-ai-babysitter-llamaindex-agent && rm -rf "$T"
manifest: library/specializations/ai-agents-conversational/skills/llamaindex-agent/SKILL.md
tags
#rag-setup#llama-index#query-engine#agent-configuration#re-act-agent
source content

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

  1. ReActAgent: Reasoning and acting agent
  2. OpenAIAgent: Function calling agent
  3. StructuredPlannerAgent: Plan-and-execute style
  4. 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