Skip to main content

Chatbots Overview

What It Is

BotBat Chatbots are AI chatbots.
They are optimized for retrieval-based answers from your configured knowledge sources, not for full agent orchestration.

The chatbot module is focused on:

  • Knowledge collection (text, website, Q&A, files)
  • Knowledge-grounded answers
  • Language behavior controls
  • Safe lifecycle management

Agentic capabilities (conditional tools, human-in-the-loop, advanced orchestration) should be implemented in Workflows as a separate layer.

Scope Boundary

Use Chatbots when you need:

  • Fast knowledge-driven responses
  • Controlled and predictable support/FAQ behavior
  • One bot that can answer from configured sources

Use Workflows when you need:

  • Multi-step tool orchestration
  • Conditional tool routing
  • Human approvals/escalations
  • Complex action pipelines

Knowledge Sources

Each chatbot can use one or more of these sources:

  • Text content
  • Website URL
  • Q&A pairs
  • Uploaded/selected files

In the console, these appear as vertical source tabs with interactive completion indicators:

  • Filled source: green check icon
  • Not filled: orange circle icon

At least one source is required before create/update.

Validation Limits

Current limits are enforced in frontend and backend:

  • knowledgeContent: up to 200,000 characters
  • knowledgeFileKeys: up to 50 files
  • listOfQA: up to 300 completed Q&A pairs

Language & Translation Mode

  • language: default bot language (usually follows UI language at creation)
  • strictToLanguage:
    • false: translation mode enabled (bot replies in user message language)
    • true: language-restricted behavior

Lifecycle Status

Knowledge base lifecycle statuses:

  • Draft
  • Active
  • Training
  • OnHold

Behavior note:

  • OnHold bots must not respond.

Rebuild Behavior

Any chatbot create/update that changes knowledge fields triggers a knowledge-base rebuild in downstream services.
Status should be used operationally to reflect training and serving readiness.

Common Pitfalls

  • Treating Chatbots as full agents (they are AI chatbot-first)
  • Creating bots with no real knowledge source
  • Overloading with uncurated files/Q&A
  • Ignoring OnHold as an operational stop state

Screens In This Flow

List view showing chatbots with status badges
Create chatbot dialog with name and type selection
AI chatbot configuration panel with knowledge sections
Chatbot detail page with configuration tab open