llamaindex-agent

Solid

LlamaIndex agent and query engine setup for RAG-powered agents

AI & Automation 1,160 stars 71 forks Updated today MIT

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Skill 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

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

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