crewAI/crewai_tools/tools/contextualai_query_tool/README.md

ContextualAIQueryTool

Description

This tool is designed to integrate Contextual AI's enterprise-grade RAG agents with CrewAI. Run this tool to query existing Contextual AI RAG agents that have been pre-configured with documents and knowledge bases.

Installation

To incorporate this tool into your project, follow the installation instructions below:

pip install 'crewai[tools]' contextual-client

Note: You'll need a Contextual AI API key. Sign up at app.contextual.ai to get your free API key.

Example

Make sure you have already created a Contextual agent and ingested documents into the datastore before using this tool.

from crewai_tools import ContextualAIQueryTool

# Initialize the tool
tool = ContextualAIQueryTool(api_key="your_api_key_here")

# Query the agent with IDs
result = tool._run(
    query="What are the key findings in the financial report?",
    agent_id="your_agent_id_here",
    datastore_id="your_datastore_id_here"  # Optional: for document readiness checking
)
print(result)

The result will contain the generated answer to the user's query.

Parameters

Initialization:

• api_key: Your Contextual AI API key

Query (_run method):

• query: The question or query to send to the agent
• agent_id: ID of the existing Contextual AI agent to query (required)
• datastore_id: Optional datastore ID for document readiness verification (if not provided, document status checking is disabled with a warning)

Key Features

• Document Readiness Checking: Automatically waits for documents to be processed before querying
• Grounded Responses: Built-in grounding ensures factual, source-attributed answers

Use Cases

• Query pre-configured RAG agents with document collections
• Access enterprise knowledge bases through user queries
• Build specialized domain experts with access to curated documents

For more detailed information about Contextual AI's capabilities, visit the official documentation.