crewAI/crewai_tools/tools/contextualai_create_agent_tool

ContextualAICreateAgentTool

Description

This tool is designed to integrate Contextual AI's enterprise-grade RAG agents with CrewAI. This tool enables you to create a new Contextual RAG agent. It uploads your documents to create a datastore and returns the Contextual agent ID and datastore ID.

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

from crewai_tools import ContextualAICreateAgentTool

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

# Create agent with documents
result = tool._run(
    agent_name="Financial Analysis Agent",
    agent_description="Agent for analyzing financial documents",
    datastore_name="Financial Reports",
    document_paths=["/path/to/report1.pdf", "/path/to/report2.pdf"],
)
print(result)

Parameters

• api_key: Your Contextual AI API key
• agent_name: Name for the new agent
• agent_description: Description of the agent's purpose
• datastore_name: Name for the document datastore
• document_paths: List of file paths to upload

Example result:

Successfully created agent 'Research Analyst' with ID: {created_agent_ID} and datastore ID: {created_datastore_ID}. Uploaded 5 documents.

You can use ContextualAIQueryTool with the returned IDs to query the knowledge base and retrieve relevant information from your documents.

Key Features

• Complete Pipeline Setup: Creates datastore, uploads documents, and configures agent in one operation
• Document Processing: Leverages Contextual AI's powerful parser to ingest complex PDFs and documents
• Vector Storage: Use Contextual AI's datastore for large document collections

Use Cases

• Set up new RAG agents from scratch with complete automation
• Upload and organize document collections into structured datastores
• Create specialized domain agents for legal, financial, technical, or research workflows

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