Best Practices for Robust Multi-Step Data Capture (Qualification Flow) with Interruption Handling &
Hey VF community! Building a VF agent to capture Project Type (text) -> Budget (num) -> Timeline (text) sequentially. Need advice on the most robust/current best practices.
Goal: Reliable capture, even with user interruptions/questions.
Issues:
Single AI/Agent Step: Prone to skipping steps or hallucinating (e.g., tries scheduling). Unreliable for guaranteeing all 3 captures.
Multi-Step (Ask -> Capture -> Check Valid): Better structure, but implementation questions:
Asking: Use simple Talk -> Prompt or full Agent/AI step just to ask each question?
Capture Number (Budget): Best practice? Custom entity (Type: Number)? How to reliably save to {var}? (My UI needs a Set step after Capture using {{entityName.value}} - is this the correct standard?)
Capture Text (Project/Timeline): Capture (Entire reply) with direct "Save to..." variable mapping. Is this optimal?
Checking Validity (After Text Capture): Once Project/Timeline text is captured, what's the best way to check if it's a valid answer vs. an interruption/question? Condition (Prompt: YES/NO) or Business Logic?
Handling Interruptions: How to best use KB to answer off-topic questions during a Capture step, then loop back to re-attempt the same capture? Does Talk -> Prompt have KB access for this, or must I use Agent/AI step for the handler?
Final API Q:
To reliably get final variables (like {outcome}) via Dialog API post-conversation, is the standard still: Call /interact first, then immediately GET /state?
Trying to build a production-ready flow that avoids common pitfalls. What's the recommended structure the pros use today?
4 Replies
Is this voice only or text based?
text based
why don't you DM me.
@Simo I have done exactly that in my last project
I needed to gather information into structured JSON format from multistep conversation, handling fallbacks / unwated scenarios and exit the conversation, when specific conditions were met
I think there is a step for this in VF, but I am not sure, if it works well enough...you can do this with infinite loop onto a LLM model and capture step, whereas the LLM call must be in structured format and will update its response/properties, based on the conversation history and latest user answer