BedrockKBRetrieverTool

The BedrockKBRetrieverTool enables CrewAI agents to retrieve information from Amazon Bedrock Knowledge Bases using natural language queries.

Installation

pip install 'crewai[tools]'

Requirements

AWS credentials configured (either through environment variables or AWS CLI)
boto3 and python-dotenv packages
Access to Amazon Bedrock Knowledge Base

Usage

Here's how to use the tool with a CrewAI agent:

from crewai import Agent, Task, Crew
from crewai_tools.aws.bedrock.knowledge_base.retriever_tool import BedrockKBRetrieverTool

# Initialize the tool
kb_tool = BedrockKBRetrieverTool(
    knowledge_base_id="your-kb-id",
    number_of_results=5
)

# Create a CrewAI agent that uses the tool
researcher = Agent(
    role='Knowledge Base Researcher',
    goal='Find information about company policies',
    backstory='I am a researcher specialized in retrieving and analyzing company documentation.',
    tools=[kb_tool],
    verbose=True
)

# Create a task for the agent
research_task = Task(
    description="Find our company's remote work policy and summarize the key points.",
    agent=researcher
)

# Create a crew with the agent
crew = Crew(
    agents=[researcher],
    tasks=[research_task],
    verbose=2
)

# Run the crew
result = crew.kickoff()
print(result)

Tool Arguments

Argument	Type	Required	Default	Description
knowledge_base_id	str	Yes	None	The unique identifier of the knowledge base (0-10 alphanumeric characters)
number_of_results	int	No	5	Maximum number of results to return
retrieval_configuration	dict	No	None	Custom configurations for the knowledge base query
guardrail_configuration	dict	No	None	Content filtering settings
next_token	str	No	None	Token for pagination

Environment Variables

BEDROCK_KB_ID=your-knowledge-base-id  # Alternative to passing knowledge_base_id
AWS_REGION=your-aws-region            # Defaults to us-east-1
AWS_ACCESS_KEY_ID=your-access-key     # Required for AWS authentication
AWS_SECRET_ACCESS_KEY=your-secret-key # Required for AWS authentication

Response Format

The tool returns results in JSON format:

{
  "results": [
    {
      "content": "Retrieved text content",
      "content_type": "text",
      "source_type": "S3",
      "source_uri": "s3://bucket/document.pdf",
      "score": 0.95,
      "metadata": {
        "additional": "metadata"
      }
    }
  ],
  "nextToken": "pagination-token",
  "guardrailAction": "NONE"
}

Advanced Usage

Custom Retrieval Configuration

kb_tool = BedrockKBRetrieverTool(
    knowledge_base_id="your-kb-id",
    retrieval_configuration={
        "vectorSearchConfiguration": {
            "numberOfResults": 10,
            "overrideSearchType": "HYBRID"
        }
    }
)

policy_expert = Agent(
    role='Policy Expert',
    goal='Analyze company policies in detail',
    backstory='I am an expert in corporate policy analysis with deep knowledge of regulatory requirements.',
    tools=[kb_tool]
)

Supported Data Sources

Amazon S3
Confluence
Salesforce
SharePoint
Web pages
Custom document locations
Amazon Kendra
SQL databases

Use Cases

Enterprise Knowledge Integration

Enable CrewAI agents to access your organization's proprietary knowledge without exposing sensitive data
Allow agents to make decisions based on your company's specific policies, procedures, and documentation
Create agents that can answer questions based on your internal documentation while maintaining data security

Specialized Domain Knowledge

Connect CrewAI agents to domain-specific knowledge bases (legal, medical, technical) without retraining models
Leverage existing knowledge repositories that are already maintained in your AWS environment
Combine CrewAI's reasoning with domain-specific information from your knowledge bases

Data-Driven Decision Making

Ground CrewAI agent responses in your actual company data rather than general knowledge
Ensure agents provide recommendations based on your specific business context and documentation
Reduce hallucinations by retrieving factual information from your knowledge bases

Scalable Information Access

Access terabytes of organizational knowledge without embedding it all into your models
Dynamically query only the relevant information needed for specific tasks
Leverage AWS's scalable infrastructure to handle large knowledge bases efficiently

Compliance and Governance

Ensure CrewAI agents provide responses that align with your company's approved documentation
Create auditable trails of information sources used by your agents
Maintain control over what information sources your agents can access

4.8 KiB Raw Blame History