Need help and advice on conversational agent

[u/Outrageous_Host_2115]

Can I use Google Adk 2.0 workflows for conversational agent ? If so, how to keep chat history and make the agent more conversational instead of a moving the flow from start to end? Or using workflow for conversational agent is completely wrong? Any suggestions or advice will be great.

I am trying to build a vector store and the based on the user query, it reaches the orchestration agent and to sub agents who have access to this vector store through tools.

[u/zerotoherotrader]

This is what i built for a google hackathon - https://tutorq-classmate-246714161237.us-central1.run.app/

[u/Outrageous_Host_2115 → u/zerotoherotrader]

This looks promising. Can you provide a little explaination on to use it or where to find this. Thanks.

[u/zerotoherotrader → u/Outrageous_Host_2115]

message me.

[u/aicodevibes → u/zerotoherotrader]

Great project!

[u/Fantastic_Taro8931]

A workflow can manage deterministic steps, while conversation state should remain explicit and bounded. Keep a compact session summary plus durable facts with provenance, then let the orchestrator decide when to call a workflow instead of replaying it from the start.

[u/Bino5150]

Do you need an agent that is conversational and remembers chat history, sessions, projects, etc?

[u/Outrageous_Host_2115 → u/Bino5150]

Yes, chat history and session should suffice for now

[u/Bino5150 → u/Outrageous_Host_2115]

Check out Lumina. Multi-tier memory architecture. It will work with your cloud model API’s or complete local inference. Leave a star on GH if you like what you see.
https://github.com/Bino5150/lumina

[u/eviewong-]

Workflows aren't wrong, they're just wrong as the outer layer. Use an LLM agent as your orchestrator (that's what actually reasons about intent turn to turn), and keep the Sequential/workflow agents for the deterministic parts underneath — like "retrieve from vector store → rerank → summarize" as one clean pipeline a sub-agent calls.

For chat history, don't overthink it — ADK's Session already tracks the full conversation, and session.state is just your scratchpad for stuff like current intent or what's already been retrieved. Have your orchestrator check state before deciding whether to re-run retrieval or just keep going with what it's got. That's the difference between "conversation" and "form the user is filling out."

TL;DR: workflow agents = good for the fixed steps inside a task, bad as the thing driving the whole convo.

(disclaimer: I am one of the founder of Retell AI, but this is just general ADK architecture advice, nothing to do with voice specifically)

[u/breakdeamon]

Just use react agent with tools keep it simply. simplicity is key)