Documentation Index
Fetch the complete documentation index at: https://botpress.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
Zai provides methods for classifying, validating, and organizing data using an LLM.
Check a condition
zai.check() asks the LLM a yes/no question about some input and returns true or false:
import { adk } from "@botpress/runtime"
const emailBody = "Click here for a FREE iPhone! Limited time only!!!"
const isSpam = await adk.zai.check(emailBody, "is this spam?")
// true
.result() for the Boolean plus the LLM’s reasoning:
const { output } = await adk.zai.check(emailBody, "is this spam?").result()
// output.value → true
// output.explanation → "The message uses urgency tactics and promises free rewards..."
Label content
zai.label() applies multiple Boolean labels to content:
const result = await adk.zai.label(emailBody, {
spam: "is this email spam?",
urgent: "does this require immediate attention?",
promotional: "is this promotional content?",
})
// { spam: true, urgent: false, promotional: true }
Filter an array
zai.filter() keeps items that match a condition:
const comments = [
"Great product, I love it!",
"This is terrible spam content",
"Very helpful review, thank you",
]
const clean = await adk.zai.filter(comments, "is not spam or inappropriate")
// ["Great product, I love it!", "Very helpful review, thank you"]
Sort items
zai.sort() orders items using natural language criteria:
const tasks = [
"Update documentation",
"Fix critical security bug",
"Add new feature",
"System is down - all users affected",
]
const prioritized = await adk.zai.sort(tasks, "by urgency and impact, most urgent first")
// ["System is down...", "Fix critical security bug", "Add new feature", "Update documentation"]
Rate items
zai.rate() scores items on a 1-5 scale. Pass a string for a single criterion:
const reviews = [
"Amazing product! Best purchase ever!",
"It's okay, nothing special",
"Terrible quality, broke immediately",
]
const ratings = await adk.zai.rate(reviews, "Rate the sentiment")
// [5, 3, 1]
total:
const essays = ["... first essay ...", "... second essay ..."]
const ratings = await adk.zai.rate(essays, {
grammar: "Rate the grammar and spelling",
clarity: "Rate how clear and well-organized the writing is",
argumentation: "Rate the strength of arguments and evidence",
})
// [
// { grammar: 4, clarity: 5, argumentation: 3, total: 12 },
// { grammar: 3, clarity: 4, argumentation: 4, total: 11 },
// ]
Group items
zai.group() categorizes items into groups. With just instructions, it discovers groups on its own:
const messages = [
"I can't log in to my account",
"How do I reset my password?",
"When will my order arrive?",
"The app keeps crashing",
]
const groups = await adk.zai.group(messages, {
instructions: "Group by type of customer issue",
})
// { "Login Issues": [...], "Shipping Questions": [...], "Technical Errors": [...] }
initialGroups:
const articles = [
"How to build a React app",
"Python machine learning tutorial",
"Understanding Docker containers",
]
const groups = await adk.zai.group(articles, {
instructions: "Categorize by technology",
initialGroups: [
{ id: "frontend", label: "Frontend Development" },
{ id: "backend", label: "Backend Development" },
{ id: "ml", label: "Machine Learning" },
],
})
| Option | Type | Description |
|---|
instructions | string | How to group the items |
initialGroups | Array<{id, label}> | Predefined categories to use instead of discovering them |
maxGroups | number | Upper limit on groups. Smaller groups merge at the end until within the limit |
minElements | number | Minimum items per group. Groups below the threshold have their elements redistributed |
tokensPerElement | number | Max tokens per item |
chunkLength | number | Max tokens per chunk for large inputs |
