From 9f6e58554edb1ad8f269b63d4d886f20f09b679b Mon Sep 17 00:00:00 2001 From: PVidyadhar Date: Mon, 20 Jul 2026 21:40:13 +0000 Subject: [PATCH] docs: add Amazon Bedrock Knowledge Base integration page Adds integration documentation for the Bedrock Knowledge Base retrieval tool available in google-adk-community. Enables ADK agents to perform RAG using Amazon Bedrock Managed Knowledge Bases with agentic retrieval. Related: google/adk-python-community PR (bedrock-kb-tool) --- docs/integrations/bedrock-knowledge-base.md | 132 ++++++++++++++++++++ 1 file changed, 132 insertions(+) create mode 100644 docs/integrations/bedrock-knowledge-base.md diff --git a/docs/integrations/bedrock-knowledge-base.md b/docs/integrations/bedrock-knowledge-base.md new file mode 100644 index 0000000000..e222e0e1c4 --- /dev/null +++ b/docs/integrations/bedrock-knowledge-base.md @@ -0,0 +1,132 @@ +--- +catalog_title: Amazon Bedrock Knowledge Base +catalog_description: RAG retrieval from Amazon Bedrock Managed Knowledge Bases for ADK agents +catalog_icon: /integrations/assets/bedrock-knowledge-base.png +catalog_tags: ["tools", "rag", "aws"] +--- + +# Amazon Bedrock Knowledge Base + +
+ Supported in ADKPython +
+ +Connect your ADK agents to [Amazon Bedrock Managed Knowledge Bases](https://docs.aws.amazon.com/bedrock/latest/userguide/knowledge-base.html) for retrieval-augmented generation (RAG). Agents can search enterprise documents and get grounded answers without hallucinating. + +## Why Bedrock Knowledge Bases for ADK? + +Amazon Bedrock Managed Knowledge Bases provide fully managed RAG infrastructure — no vector store to provision, no embeddings to configure, automatic scaling. Combined with ADK agents, your agent can: + +- **Search enterprise documents** (PDFs, web pages, databases) in natural language +- **Use agentic retrieval** for multi-hop reasoning across documents +- **Get grounded answers** with source citations +- **Scale automatically** without managing infrastructure + +## Use cases + +- **Enterprise Q&A agents**: Answer questions from internal documentation, policies, and knowledge bases +- **Customer support agents**: Retrieve relevant help articles and product information +- **Research assistants**: Search across large document collections with multi-hop reasoning +- **Compliance agents**: Look up regulatory documents and provide cited answers + +## Prerequisites + +- AWS account with Amazon Bedrock access +- A Bedrock Managed Knowledge Base created (via [AWS Console](https://console.aws.amazon.com/bedrock/home#/knowledge-bases) or Terraform) +- AWS credentials configured (environment variables, IAM role, or AWS profile) +- Python 3.10+ + +## Installation + +```bash +pip install google-adk-community boto3>=1.43.2 +``` + +## Use with agent + +```python +from google.adk.agents import Agent +from google.adk_community.tools.bedrock_kb import bedrock_kb_retrieve + +# Create an agent with Bedrock KB retrieval +agent = Agent( + model="gemini-2.0-flash", + tools=[bedrock_kb_retrieve], + instruction="You are a helpful assistant. Use bedrock_kb_retrieve to search the knowledge base when answering questions about company policies or documentation.", +) +``` + +The agent will automatically call `bedrock_kb_retrieve` when it needs information from the knowledge base. + +### Configuration via environment variables + +```bash +export KNOWLEDGE_BASE_ID="YOUR_KB_ID" +export AWS_REGION="us-west-2" +export USE_AGENTIC_RETRIEVAL="true" # Multi-hop reasoning (default) +``` + +### Configuration via function arguments + +```python +# Pass knowledge_base_id directly (overrides env var) +result = bedrock_kb_retrieve( + query="What is our refund policy?", + knowledge_base_id="YOUR_KB_ID", + max_results=5, +) +``` + +## Available tools + +Tool | Description +---- | ----------- +`bedrock_kb_retrieve` | Searches a Bedrock Managed Knowledge Base and returns relevant passages with sources and scores. Supports agentic retrieval (multi-hop reasoning) with automatic fallback to standard search. + +### Tool parameters + +Parameter | Type | Description +--------- | ---- | ----------- +`query` | `str` | The natural language question or search query (required) +`knowledge_base_id` | `str` | Bedrock KB ID. Defaults to `KNOWLEDGE_BASE_ID` env var +`max_results` | `int` | Maximum results to return. Defaults to 5 + +## Retrieval modes + +### Agentic retrieval (default) + +Uses `AgenticRetrieveStream` — the model reasons over multiple retrieval passes, decomposes complex queries, and applies managed reranking for better results. + +```bash +export USE_AGENTIC_RETRIEVAL="true" +``` + +### Standard retrieval + +Uses `Retrieve` with `managedSearchConfiguration` — single-pass semantic search. + +```bash +export USE_AGENTIC_RETRIEVAL="false" +``` + +## IAM permissions + +Your AWS credentials need: + +```json +{ + "Effect": "Allow", + "Action": [ + "bedrock:Retrieve", + "bedrock:AgenticRetrieveStream" + ], + "Resource": "arn:aws:bedrock:REGION:ACCOUNT:knowledge-base/KB_ID" +} +``` + +## Resources + +- [Amazon Bedrock Knowledge Bases documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/knowledge-base.html) +- [Create a managed knowledge base](https://docs.aws.amazon.com/bedrock/latest/userguide/kb-managed-create.html) +- [AgenticRetrieveStream API](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_agent-runtime_AgenticRetrieveStream.html) +- [GitHub: adk-python-community](https://github.com/google/adk-python-community)