--- title: Using LlamaIndex Tools description: Learn how to integrate LlamaIndex tools with CrewAI agents to enhance search-based queries and more. --- ## Using LlamaIndex Tools !!! info "LlamaIndex Integration" CrewAI seamlessly integrates with LlamaIndex’s comprehensive toolkit for RAG (Retrieval-Augmented Generation) and agentic pipelines, enabling advanced search-based queries and more. Here are the available built-in tools offered by LlamaIndex. ```python from crewai import Agent from crewai_tools import LlamaIndexTool # Example 1: Initialize from FunctionTool from llama_index.core.tools import FunctionTool your_python_function = lambda ...: ... og_tool = FunctionTool.from_defaults(your_python_function, name="", description='') tool = LlamaIndexTool.from_tool(og_tool) # Example 2: Initialize from LlamaHub Tools from llama_index.tools.wolfram_alpha import WolframAlphaToolSpec wolfram_spec = WolframAlphaToolSpec(app_id="") wolfram_tools = wolfram_spec.to_tool_list() tools = [LlamaIndexTool.from_tool(t) for t in wolfram_tools] # Example 3: Initialize Tool from a LlamaIndex Query Engine query_engine = index.as_query_engine() query_tool = LlamaIndexTool.from_query_engine( query_engine, name="Uber 2019 10K Query Tool", description="Use this tool to lookup the 2019 Uber 10K Annual Report" ) # Create and assign the tools to an agent agent = Agent( role='Research Analyst', goal='Provide up-to-date market analysis', backstory='An expert analyst with a keen eye for market trends.', tools=[tool, *tools, query_tool] ) # rest of the code ... ``` ## Steps to Get Started To effectively use the LlamaIndexTool, follow these steps: 1. **Package Installation**: Confirm that the `crewai[tools]` package is installed in your Python environment. ```shell pip install 'crewai[tools]' ``` 2. **Install and Use LlamaIndex**: Follow LlamaIndex documentation [LlamaIndex Documentation](https://docs.llamaindex.ai/) to set up a RAG/agent pipeline.