BerriAI / litellm
github.com·3d ago
Developer Tools
Databricks Blog·Sep 8·5 min read
Build durable agents with Temporal and Lakebase
TL;DR
A durable personal-loan underwriting agent was developed using Temporal for execution and Lakebase for operational state management, ensuring resilience during process interruptions. This implementation allows agents to maintain progress and evidence across sessions and deployments.
✦ Why It Matters
Implement durable agents in your applications to enhance resilience and user experience during process interruptions.
Key Takeaways
- Utilize Temporal for managing long-running processes.
- Implement Lakebase for storing operational state and evidence.
- Leverage Change Data Feed for real-time data updates.
- Ensure agents can resume sessions across different deployments.
Full Summary
The implementation focuses on a personal-loan underwriting agent that must gather evidence and apply policies while potentially facing delays and interruptions. Temporal is utilized for durable execution, allowing the agent to resume operations even after failures.
Lakebase Postgres serves as the queryable operational state, where evidence, decisions, and metrics are stored. A synced table connects underwriting policies from Unity Catalog to Lakebase, enabling efficient data management.
The integration of Lakebase Change Data Feed allows for real-time updates to Delta history tables. This architecture ensures that the agent can survive beyond the initial request, allowing users to return and continue their sessions seamlessly, thus enhancing user experience and operational reliability.