Request for Genie Agent Mode API with Streaming & Reasoning Trace Support

asfriz
New Contributor II

Hi everyone,

Genie Agent Mode has been incredibly impressive and is one of the best tools we’ve come across, especially in how it handles multi-step reasoning and delivers structured end-to-end insights.

We’re currently building a frontend application and would love to use Genie Agent Mode as the backend engine. However, we’ve hit a key limitation:

Agent Mode is not available via API, and its capabilities are restricted to the UI.

What we need

To integrate this into a production application, we’re specifically looking for:

1. Agent Mode API access

- Ability to send prompts programmatically
- Execute full Agent workflows outside the UI

2. Reasoning trace / intermediate steps

Structured breakdown of the agent’s internal process, including:

- Question understanding
- Query generation
- Iterative refinement steps
- Final answer synthesis
- Additionally, lightweight status updates during execution such as:

“Understanding question…”
“Running queries…”
“Analyzing results…”

These intermediate updates are extremely valuable for frontend UX and transparency.

3. Streaming support (real-time response)

- Responses delivered in incremental chunks (similar to a typing effect) rather than a single final response
- Ability to stream partial outputs to the frontend 
- This allows users to:

- See answers forming in real time
- Stay engaged during longer-running queries
- Combine streamed output with live status updates

Genie Conversation APIs are helpful, but they don’t replicate the multi-step reasoning and iterative behavior of Agent Mode.

This would unlock a huge opportunity to build real-time data applications directly on Databricks.

Would love to know if this is on the roadmap.

Thanks!

Ankitkalra40
New Contributor

Hi Asfriz,

Genie Agent mode is currently unavailable via direct API. This capability is something we are also eagerly waiting for.

For now, you can try building an Agent Supervisor which has your Genie space served as a tool & utilize the orchestrator model to mimic the Genie Agent mode. I know this might not be exactly what you are looking for but we tried this & were able to get significantly better response (both quality & structure) for one of our implementations. 
Since all of this will be managed by mlflow traces & LLM judges, management of intermediate steps will also be relatively easy. Refer to this for more details: Agent Evaluation (MLflow 2) | Databricks on AWS

Also, this new release might be coming sooner than expected with the DAIS going on.

Databricks recently announced 3 new Genie capabilities: https://www.databricks.com/blog/introducing-genie-one-genie-ontology-and-genie-agents 

Would love to connect further on this use case.

Regards,

Ankit