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Documentation Index

Fetch the complete documentation index at: https://documentation.uponai.com/llms.txt

Use this file to discover all available pages before exploring further.

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Introduction

UponAI offers two approaches for building conversational agents, each suited to different complexity levels and use cases.

Single Prompt Agent

One comprehensive prompt defines all agent behavior. Best for simple conversations, prototypes, and agents with fewer than 5 functions.

Multi-Prompt Agent

Conversations are organized into a structured tree of states, each with its own focused prompt and behavior.

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Single Prompt Agent

Use one prompt to define everything your agent does. Simple to set up and great for straightforward use cases. Best for:
  • Simple, linear conversations
  • Prototypes and early testing
  • Agents with fewer than 5 functions
Limitations at scale: As complexity grows, single prompt agents can run into issues:
  • Behavioral inconsistency in edge cases
  • Unreliable function calls
  • Difficult to maintain
  • Conversation state tracking problems
If your prompt exceeds 1000 words or uses more than 5 functions, consider switching to a Multi-Prompt Agent.

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Multi-Prompt Agent

Organizes conversations into a structured tree of states. Each state has its own focused prompt, tools, and transition logic. Real-World Example — Lead Qualification:
StatePurposeTools Available
Lead QualificationGather customer infoNo booking functions
Appointment SchedulingBook the meetingBooking functions enabled, context from qualification available
Benefits of Multi-Prompt Structure:
  1. Predictable Behavior: Each state has a clear, focused purpose
  2. Easier Debugging: Issues isolated to specific states
  3. Better Function Control: Tools available only when appropriate
  4. Scalable Design: Add new states without affecting existing ones
  5. Team Collaboration: Different team members can work on different states
Start with our templates to see multi-prompt best practices in action, then customize for your use case.

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Step 1: Creating a Prompt

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Creating a Prompt Within Your Agent

The single prompt approach allows you to define your agent’s behavior with one comprehensive prompt.
It’s straightforward and great for simple use cases.

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How to Write a Single Prompt

Good prompt writing is the most important part of building your agent—it can make your agent work great or not so much.
This guide shows you what we’ve learned about writing prompts that agents can follow better and more consistently.
Note: This guide is updated regularly as we learn new things. If you have ideas or feedback, please share them with us.
To see examples of good prompts, check out the templates in your Dashboard by creating a new agent and selecting a template.

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Breaking Prompts into Sections

When writing prompts, it’s best to break them into smaller sections.
This makes them easier for you to edit and easier for the LLM to understand. 
## Identify

You are a friendly AI assistant for UponAI. ....

## Style Guardrails
Be concise: ...
Be conversational: ...

...

## Response Guideline

Return dates in their spoken forms: ...
Ask up to one question at a time: ...

...

## Task

1. Greet the user

...

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Tasks

When writing your prompt you’ll want to write your tasks, or what you want the agent to ask or do, in number order like you would steps. This helps the agent space stuff out and not ask everything in one long question. 
## Task

You are a friendly AI assistant for UponAI. ....
1. Ask for user's name.
2. Ask if user needs a refund, need a replacement, or just retriving information.
   - if user needs a refund, transition to refund state.
   - if user needs a replacement, transition to replacement state.
3. If user is just retriving information, ask for the order number.

...
If your agent doesn’t stop and proceeds to ask all steps as one large question consider editing the prompt and and spelling out exactly what you want. 
## Task

1. Inform user why you are calling.
2. Ask user's name.

Wait for user response

3. Ask if user needs a refund, need a replacement, or just retriving information.

Wait for user response
   - if user needs a refund, transition to refund state.
   - if user needs a replacement, transition to replacement state.


4. Ask for the order number.

Wait for user response

...

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Prompting More In-depth

It’s recommended to include a prompt as a guideline for the LLM to follow. This ensures that the agent can consistently reply with the correct format. When writing prompts you may have to spell things out for the agent to get the best results. Example:

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Appointment or Demo Booking Request Handling

If a customer requests to book an appointment or demo, follow these steps:
  1. Ask for full name.
  2. Ask for preferred date and time.
  3. Invoke check_available_appointments and return available slots.
  4. Ask for company name.
  5. Ask for full email address:
    • If spelled out: n-a-m-e-@-dot-com → interpret as name@domain.com.
    • “name at” → interpret as name@
    • “dot com” → interpret as .com
  6. Ask for purpose of the appointment.
  7. Ask for best phone number:
    • Accepted formats: 4158923245, (415) 892-3245, 415-892-3245
    • Pronounce as: "four one five - eight nine two - three two four five"
    • Important: Keep spaces around the dash when speaking
  8. Reconfirm preferred date and time if needed.
  9. Confirm all details (name, purpose, date, time, email address, phone) with the caller.
  10. Invoke book_appointment function.
Tip: If the agent says a phrase or phone number too quickly, instruct it to repeat slowly.