This example demonstrates the use of Amazon Bedrock Agents multi-agent collaboration with its built-in Routing Classifier feature. By simply enabling that mode for your supervisor, Bedrock automatically routes to the correct collaborating sub-agent using LLM intent classification optimized to route with sub-second latency. Contrast that with a traditional supervisor that must go through its own orchestration loop, a more expensive proposition that can take 3-6 seconds depending on which LLM you are using. This feature is most valuable when trying to build a unified customer experience across a set of sub-agents. In our example, we have 3 collaborators: one for general Contract questions, one for handling conversations about Existing Contracts, and another for dealing with New Contracts.
Try sample prompts:
- "I need help with a purchase agreement."
- "Can you show me the status of contract #12345?"
Each of these gets routed quickly to the right sub-agent for subsequent processing. Conversation switching is seamless.
Routing also reverts automatically to full Supervisor mode if the request is truly not mapping cleanly to a single collaborator.
Caution
The sample contract templates are not legal advice, are for illustrative purposes only, and should not be relied upon without consulting the user's own attorney.
- Clone and install repository
git clone https://github.com/awslabs/amazon-bedrock-agent-samples
cd amazon-bedrock-agent-samples
python3 -m venv .venv
source .venv/bin/activate
pip3 install -r src/requirements.txt- Deploy Amazon Bedrock Agents
cd examples/multi-agent-collaboration/contract_assistant_agent/
python3 main.py --recreate_agents "true"- Invoke
python3 main.py --recreate_agents "false"- Cleanup
python3 main.py --clean_up "true"This project is licensed under the Apache-2.0 License.
The sample contract template is licensed under CC-0.