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.
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.
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
- Behavioral inconsistency in edge cases
- Unreliable function calls
- Difficult to maintain
- Conversation state tracking problems
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:| State | Purpose | Tools Available |
|---|---|---|
| Lead Qualification | Gather customer info | No booking functions |
| Appointment Scheduling | Book the meeting | Booking functions enabled, context from qualification available |
- Predictable Behavior: Each state has a clear, focused purpose
- Easier Debugging: Issues isolated to specific states
- Better Function Control: Tools available only when appropriate
- Scalable Design: Add new states without affecting existing ones
- Team Collaboration: Different team members can work on different states